This paper contains the implementation of the BeeAdhoc algorithm for data routing in mobile Ad Hoc Network (MANet). The algorithm was inspired by the foraging behaviour of honey bees and its implementation mimics this behaviour. The integration was done on Network Simulator version 2 (NS-2.34) where different scenarios were considered in comparison with other existing state-of-the-art routing algorithms that have been implemented in the chosen simulator. The comparison was carried out between DSR, DSDV, AOMDV which are all multipath routing algorithms as the BeeAdhoc; this gave a better insight to the different behaviour of the algorithms on a common application environment. Throughput, end-to-end delay and routing overhead constitute the indices used for the performance evaluation. Experimental results showed the best performance of BeeAdhoc over, DSDV and AOMDV algorithms.
This document summarizes a research paper that proposes a hybrid evolutionary clustering approach for optimized routing in mobile ad hoc networks. It uses particle swarm optimization (PSO) and ant colony optimization (ACO) to perform spatial clustering of nodes. Greedy routing is then used to find routes, and when dead ends are encountered, genetic algorithms are applied to find alternative routes. The approach aims to improve greedy routing performance and recovery from dead ends by avoiding the use of floating nodes. Simulation results showed improved greedy routing and fewer concave nodes compared to other methods.
Implementation of Optimized Ant Based Routing Algorithm for ManetIRJET Journal
This document presents an implementation and evaluation of the Ant-Based Routing Algorithm (ARA) for mobile ad hoc networks (MANETs).
It first provides background on swarm intelligence and ant colony optimization techniques. It then surveys various existing ant-based routing protocols. The ARA protocol uses forward and backward ants to discover and maintain multiple paths between nodes.
The document describes simulating ARA in NS2 for different network sizes and times. It evaluates ARA's performance based on throughput, packet delivery ratio, routing overhead, and energy consumption. The results show that ARA achieves high throughput and packet delivery ratio for all network conditions. It also significantly reduces routing overhead compared to other protocols. ARA also performs well in terms of
The document describes an elephant swarm optimization technique for wireless sensor networks using a cross-layer approach. Elephants exhibit intelligent social behaviors like memory, group leadership, and problem-solving in large herds. The authors propose incorporating these behaviors into a wireless sensor network using a cross-layer system architecture. This would optimize routing, MAC, and radio layers to enhance network lifetime and throughput. Experimental results show the elephant swarm optimization increases network lifetime by about 26.8% compared to particle swarm optimization.
Simulation of Route Optimization with load balancing Using AntNet SystemIOSR Journals
This document summarizes a research paper that simulates route optimization and load balancing in computer networks using the AntNet routing algorithm. The AntNet algorithm is based on the behavior of ants and uses forward and backward ants to collect information and update routing tables. The simulation tested the AntNet algorithm against a generic algorithm without AntNet. The results showed that AntNet performed better in terms of throughput, average packet delivery, distance, delay, and failed packets. Specifically, when the simulation speed was 1000 and total packets were 100, AntNet delivered all packets with less delay and distance compared to the generic algorithm which failed 2 packets. This demonstrates that the AntNet algorithm can effectively optimize routes and balance network load.
Cluster based wireless sensor network routings ieeeTAIWAN
The document proposes using an artificial bee colony (ABC) algorithm to form clusters in a wireless sensor network (WSN) in order to minimize energy consumption. The ABC algorithm is applied to select cluster heads that are uniformly distributed, unlike in the popular LEACH protocol. Simulation results show the proposed WSNCABC approach extends network lifetime compared to LEACH and direct communication by balancing energy usage across nodes.
Mitigation of sink hole attack in manet using acoIJARIIT
MANET (Mobile ad hoc network) is the emerging and most demanding technology of wireless network. Because of
self-deliberate property, the network points behave as router or source and the nodes keep moving freely in the network area.
MANET plays a significant role in connection less infrastructure. Securing a network is the fundamental issue in MANET for
securing the susceptible information from hackers. MANET has different attacks that are routing protocol attacks. The sink
hole is known as the severe one from all the attacks in MANET. It generally attracts the neighbour’s nodes towards itself and
transmits the bogus or fake routing path. This attack decreases the network lifetime and increases the network overhead by
boosting energy consumption and later destroys the network. In the proposed work, the routing protocol is being optimized by
utilizing ACO (Ant Colony Optimization) with NN (Neural Network) for achieving enhanced performance as compared to
existing work. Different parameters, namely, Bit error rate, throughput, an end to end delay and energy consumption are used
for calculating the performance of the proposed wok in MANET or to check the effect of Sinkhole attack. The environment
created by simulating the work has 50 to 100 nodes. The width and height of the network is 1000 nodes
A genetic algorithm approach for predicting ribonucleic acid sequencing data ...TELKOMNIKA JOURNAL
Malaria larvae accept explosive variable lifecycle as they spread across numerous mosquito vector stratosphere. Transcriptomes arise in thousands of diverse parasites. Ribonucleic acid sequencing (RNA-seq) is a prevalent gene expression that has led to enhanced understanding of genetic queries. RNA-seq tests transcript of gene expression, and provides methodological enhancements to machine learning procedures. Researchers have proposed several methods in evaluating and learning biological data. Genetic algorithm (GA) as a feature selection process is used in this study to fetch relevant information from the RNA-Seq Mosquito Anopheles gambiae malaria vector dataset, and evaluates the results using kth nearest neighbor (KNN) and decision tree classification algorithms. The experimental results obtained a classification accuracy of 88.3 and 98.3 percents respectively.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document summarizes a research paper that proposes a hybrid evolutionary clustering approach for optimized routing in mobile ad hoc networks. It uses particle swarm optimization (PSO) and ant colony optimization (ACO) to perform spatial clustering of nodes. Greedy routing is then used to find routes, and when dead ends are encountered, genetic algorithms are applied to find alternative routes. The approach aims to improve greedy routing performance and recovery from dead ends by avoiding the use of floating nodes. Simulation results showed improved greedy routing and fewer concave nodes compared to other methods.
Implementation of Optimized Ant Based Routing Algorithm for ManetIRJET Journal
This document presents an implementation and evaluation of the Ant-Based Routing Algorithm (ARA) for mobile ad hoc networks (MANETs).
It first provides background on swarm intelligence and ant colony optimization techniques. It then surveys various existing ant-based routing protocols. The ARA protocol uses forward and backward ants to discover and maintain multiple paths between nodes.
The document describes simulating ARA in NS2 for different network sizes and times. It evaluates ARA's performance based on throughput, packet delivery ratio, routing overhead, and energy consumption. The results show that ARA achieves high throughput and packet delivery ratio for all network conditions. It also significantly reduces routing overhead compared to other protocols. ARA also performs well in terms of
The document describes an elephant swarm optimization technique for wireless sensor networks using a cross-layer approach. Elephants exhibit intelligent social behaviors like memory, group leadership, and problem-solving in large herds. The authors propose incorporating these behaviors into a wireless sensor network using a cross-layer system architecture. This would optimize routing, MAC, and radio layers to enhance network lifetime and throughput. Experimental results show the elephant swarm optimization increases network lifetime by about 26.8% compared to particle swarm optimization.
Simulation of Route Optimization with load balancing Using AntNet SystemIOSR Journals
This document summarizes a research paper that simulates route optimization and load balancing in computer networks using the AntNet routing algorithm. The AntNet algorithm is based on the behavior of ants and uses forward and backward ants to collect information and update routing tables. The simulation tested the AntNet algorithm against a generic algorithm without AntNet. The results showed that AntNet performed better in terms of throughput, average packet delivery, distance, delay, and failed packets. Specifically, when the simulation speed was 1000 and total packets were 100, AntNet delivered all packets with less delay and distance compared to the generic algorithm which failed 2 packets. This demonstrates that the AntNet algorithm can effectively optimize routes and balance network load.
Cluster based wireless sensor network routings ieeeTAIWAN
The document proposes using an artificial bee colony (ABC) algorithm to form clusters in a wireless sensor network (WSN) in order to minimize energy consumption. The ABC algorithm is applied to select cluster heads that are uniformly distributed, unlike in the popular LEACH protocol. Simulation results show the proposed WSNCABC approach extends network lifetime compared to LEACH and direct communication by balancing energy usage across nodes.
Mitigation of sink hole attack in manet using acoIJARIIT
MANET (Mobile ad hoc network) is the emerging and most demanding technology of wireless network. Because of
self-deliberate property, the network points behave as router or source and the nodes keep moving freely in the network area.
MANET plays a significant role in connection less infrastructure. Securing a network is the fundamental issue in MANET for
securing the susceptible information from hackers. MANET has different attacks that are routing protocol attacks. The sink
hole is known as the severe one from all the attacks in MANET. It generally attracts the neighbour’s nodes towards itself and
transmits the bogus or fake routing path. This attack decreases the network lifetime and increases the network overhead by
boosting energy consumption and later destroys the network. In the proposed work, the routing protocol is being optimized by
utilizing ACO (Ant Colony Optimization) with NN (Neural Network) for achieving enhanced performance as compared to
existing work. Different parameters, namely, Bit error rate, throughput, an end to end delay and energy consumption are used
for calculating the performance of the proposed wok in MANET or to check the effect of Sinkhole attack. The environment
created by simulating the work has 50 to 100 nodes. The width and height of the network is 1000 nodes
A genetic algorithm approach for predicting ribonucleic acid sequencing data ...TELKOMNIKA JOURNAL
Malaria larvae accept explosive variable lifecycle as they spread across numerous mosquito vector stratosphere. Transcriptomes arise in thousands of diverse parasites. Ribonucleic acid sequencing (RNA-seq) is a prevalent gene expression that has led to enhanced understanding of genetic queries. RNA-seq tests transcript of gene expression, and provides methodological enhancements to machine learning procedures. Researchers have proposed several methods in evaluating and learning biological data. Genetic algorithm (GA) as a feature selection process is used in this study to fetch relevant information from the RNA-Seq Mosquito Anopheles gambiae malaria vector dataset, and evaluates the results using kth nearest neighbor (KNN) and decision tree classification algorithms. The experimental results obtained a classification accuracy of 88.3 and 98.3 percents respectively.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Every cluster comprise of a leader which is known as cluster head. The cluster head will be chosen by the sensor nodes in the individual cluster or be pre-assigned by the user. The main advantages of clustering are the transmission of aggregated data to the base station, offers scalability for huge number of nodes and trims down energy consumption. Fundamentally, clustering could be classified into centralized clustering, distributed clustering and hybrid clustering. In centralized clustering, the cluster head is fixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps on shifting form node to node within the cluster on the basis of some parameters. Hybrid clustering is the combination of both centralized clustering and distributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks. A research on the well evaluated distributed clustering algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) and its followers are portrayed artistically. To overcome the drawbacks of these existing algorithms a hybrid distributed clustering model has been proposed for attaining energy efficiency to a larger scale.
This document proposes a hybrid optimization algorithm using ant colony optimization and particle swarm optimization to solve the multiobjective multicast routing problem in wireless sensor networks. The goal is to optimize two objectives simultaneously - end-to-end delay and total transmitted power. ACO and PSO are combined to find Pareto-optimal solutions efficiently. Simulation results show the algorithm can find near-optimal solutions for minimizing delay and power consumption when routing data from a source to multiple destinations in wireless sensor networks.
IMPROVEMENTS IN ROUTING ALGORITHMS TO ENHANCE LIFETIME OF WIRELESS SENSOR NET...IJCNCJournal
Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited
computation, communication, memory, and energy resources that are being used fora huge range of
applications. Clustering in WSNs is an effective way to minimize the energy consumption of sensor nodes.
In this paper improvements in various parameters are compared for three different routing algorithms.
First, it is started with Low Energy Adaptive Cluster Hierarchy (LEACH)which is a famed clustering
mechanism that elects a CH based on the probability model. Then, work describes a Fuzzy logic system
initiated CH selection algorithm for LEACH. Then Artificial Bee Colony (ABC)which is an optimisation
protocol owes its inspiration to the exploration behaviour of honey bees. In this study ABC optimization
algorithm is proposed for fuzzy rule selection. Then, the results of the three routing algorithms are
compared with respect to various parameters
OPTIMAL CLUSTERING AND ROUTING FOR WIRELESS SENSOR NETWORK BASED ON CUCKOO SE...ijassn
The document describes a proposed approach for optimal clustering and routing in wireless sensor networks based on cuckoo search and multi-objective genetic algorithms. The cuckoo search algorithm is used to create clusters with sensor nodes within an egg laying radius of a trigger node, selected based on residual energy. Within each cluster, a multi-objective genetic algorithm with Pareto ranking is used to select an optimal node for data forwarding, aiming to maximize network lifetime and minimize transmission delay. The proposed approach combines cuckoo search for energy-efficient clustering with multi-objective optimization for optimal intra-cluster routing, seeking to prolong network lifetime, reduce packet loss, and improve throughput compared to existing techniques like LEACH.
1) The document presents a firefly-optimized routing algorithm for mobile ad hoc networks (MANETs). It aims to improve route acquisition efficiency over MANETs using the firefly algorithm.
2) The proposed algorithm models firefly behavior to select optimal routes. Fireflies communicate via flashing lights, and the algorithm models this to determine the best next hop.
3) Simulation results show the firefly-optimized routing algorithm outperforms AOMDV in terms of packet delivery ratio, packet loss, throughput, and end-to-end delay. The algorithm adapts well to dynamic network changes.
HERF: A Hybrid Energy Efficient Routing using a Fuzzy Method in Wireless Sens...ijdpsjournal
Wireless Sensor Network (WSN) is one of the major research areas in computer network field today.Data
dissemination is an important task performed by wireless sensor networks. The routing algorithms of this
network depend on a number of factors such as application areas, usage condition, power, aggregation
parameters. With respect to these factors, different algorithms are recommended. One of the most
important features of routing algorithms is their flexibility and ability to self-organize themselves
according to such parameters. The existence of flexibility in routing protocols can satisfy calls for on
demand and table driven methods. Switching between these two methods would be impossible except by
compatibility between nodes' and switcher. Energy is another significant factor in wireless sensor
networks due to limited battery power and their exchangeability. To arrive at a network with mentioned
features, we have proposed an algorithm for hybrid energy efficient routing in wireless sensor networks
which uses two algorithms, i.e. EF-Tree (Earliest-First Tree) and SID (Source-Initiated Dissemination) to
disseminate data, and employs a fuzzy method to choose cluster head, and to switch between two
methods, i.e. SID and EF-Tree. In this routing, the whole network is clustered and the appropriate clusterhead
is selected according to fuzzy variables. Then, analyzing the changes in fuzzy variables and If fuzzy,
then rule, one routing in EF-Tree or SID is chosen for information transmission. The results of
simulations indicate that HERF has improved energy efficiency.
This document summarizes a research paper that proposes using a genetic algorithm to efficiently cluster wireless sensor nodes. The genetic algorithm aims to minimize the total communication distance between sensors and the base station in order to prolong the network lifetime. Simulation results showed that the genetic algorithm can quickly find good clustering solutions that reduce energy consumption compared to previous clustering methods. The full paper provides details on wireless sensor networks, related clustering algorithms, genetic algorithms, and the proposed genetic algorithm-based clustering method.
Paper 3 energy efficient bee routing algorithm in wireless mobileSpandan Spandy
This document describes an energy efficient bee routing algorithm for wireless mobile networks. It discusses how bee colony optimization can inspire an energy-efficient routing protocol. The key points are:
1) The algorithm uses two agent types - scouts to discover paths and foragers to evaluate paths based on predicted energy consumption and delay.
2) It aims to find the optimal path between source and destination that consumes the least amount of energy overall.
3) The algorithm calculates energy consumption at each node and for the entire path to determine the "goodness ratio" and select the best path.
4) The algorithm was simulated in NS2 and results showed it improves metrics like routing overhead, delivery ratio, and energy
Data Dissemination in Wireless Sensor Networks: A State-of-the Art SurveyCSCJournals
A wireless sensor network is a network of tiny nodes with wireless sensing capacity for data collection processing and further communicating with the Base Station this paper discusses the overall mechanism of data dissemination right from data collection at the sensor nodes, clustering of sensor nodes, data aggregation at the cluster heads and disseminating data to the Base Station the overall motive of the paper is to conserve energy so that lifetime of the network is extended this paper highlights the existing algorithms and open research gaps in efficient data dissemination.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
This document summarizes and compares various clustering protocols for wireless sensor networks. It discusses clustering parameters like number of clusters and node mobility. It also classifies clustering algorithms into two main categories: probabilistic (e.g. LEACH) and non-probabilistic (e.g. weight-based and graph-based). Popular probabilistic protocols like LEACH, EEHC and HEED are described. Non-probabilistic protocols discussed include those based on node proximity, weights, and biologically inspired approaches. Overall, the document provides an overview of different clustering algorithm types and compares their advantages and disadvantages.
Optimization of workload prediction based on map reduce frame work in a cloud...eSAT Journals
Abstract Nowadays cloud computing is emerging Technology. It is used to access anytime and anywhere through the internet. Hadoop is an open-source Cloud computing environment that implements the Googletm MapReduce framework. Hadoop is a framework for distributed processing of large datasets across large clusters of computers. This paper proposes the workload of jobs in clusters mode using Hadoop. MapReduce is a programming model in hadoop used for maintaining the workload of the jobs. Depend on the job analysis statistics the future workload of the cluster is predicted for potential performance optimization by using genetic algorithm. Key Words: Cloud computing, Hadoop Framework, MapReduce Analysis, Workload
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
This document is a thesis submitted by Rahul Gupta to Thapar University in partial fulfillment of the requirements for a Master of Technology degree in Computer Science and Applications. The thesis is supervised by Dr. Rajesh Kumar and proposes a Firefly Algorithm based optimized routing protocol for Mobile Ad-Hoc Networks (MANETs) to address issues with dynamic topology changes and limited resources in MANETs. The thesis provides background on MANETs, routing protocols, swarm intelligence and the Firefly Algorithm. It then describes the proposed Firefly based routing algorithm and evaluates its performance compared to the Ad-Hoc On-Demand Multipath Distance Vector routing protocol through network simulation experiments.
A NOVEL ROUTING PROTOCOL FOR TARGET TRACKING IN WIRELESS SENSOR NETWORKSIJCNCJournal
Wireless sensor networks (WSNs) are large scale integration consists of hundreds or thousands or more
number of sensor nodes. They are tiny, low cost, low weight, and limited battery, primary storage,
processing power. They have wireless capabilities to monitor physical or environmental conditions. This
paper compared the performance analysis of some existing routing protocols for target tracking
application with proposed hierarchical binary tree structure to store the routing information. The sensed
information is stored in controlled way at multiple sensor nodes (e.g. node, parent node and grandparent
node) which deployed using complete binary tree data structure. This reduces traffic implosion and
geographical overlapping. Simulation result showed improved network lifetime by 20%, target detection
probability by 25%, and reduces error rate by 20%, energy efficiency, fault tolerance, and routing
efficiency. We have evaluated our proposed algorithm using NS2.
A Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Rout...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Eff...CSCJournals
The objective of this paper is to develop a mechanism to increase the lifetime of homogeneous wireless sensor networks (WSNs) through minimizing long range communication, efficient data delivery and energy balancing. Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. To achieve energy balancing and maximizing network lifetime we divided the whole network into different clusters. In cluster based architecture, the role of aggregator node is very crucial because of extra processing and long range communication. Once the aggregator node becomes non functional, it affects the whole cluster. We introduced a candidate cluster head node on the basis of node density. We proposed a modified cluster based WSN architecture by introducing a server node (SN) that is rich in terms of resources. This server node (SN) takes the responsibility of transmitting data to the base station over longer distances from the cluster head. We proposed cluster head selection algorithm based on residual energy, distance, reliability and degree of mobility. The proposed method can save overall energy consumption and extend the lifetime of the sensor network and also addresses robustness against even/uneven node deployment.
Comparison of different Ant based techniques for identification of shortest p...IOSR Journals
This document compares different ant colony optimization (ACO) techniques for identifying the shortest path in a distributed network. ACO is based on the behavior of ants finding food sources and uses pheromone trails to probabilistically determine paths. The document reviews several ACO algorithms and techniques, including Max-Min, rank-based, and fuzzy rule-based approaches. It then implements an efficient ACO algorithm that performs better at finding the shortest path compared to other existing ACO techniques.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
STUDY AND PERFORMANCE EVALUATION OF ANTHOCNET AND BEEHOCNET NATURE INSPIRED M...IAEME Publication
This document discusses nature-inspired routing protocols for mobile ad hoc networks (MANETs) and summarizes the Anthocnet and Beehocnet routing protocols. It begins by providing background on MANETs and swarm intelligence approaches. It then describes how Anthocnet uses forward and backward ants to discover and maintain routes similarly to ant colony behavior. Beehocnet is proposed as an extension using different agent types like packers, scouts, and foragers inspired by honeybee behavior. The document evaluates the performance of these protocols through simulation using the NS-2 network simulator.
PERFORMANCE ANALYSIS OF ANTHOCNET ROUTING PROTOCOL FOR HYBRID AD HOC NETWORKKhushbooGupta145
This document summarizes a research paper that analyzes the performance of the AntHocNet routing protocol for hybrid ad hoc networks. AntHocNet is a bio-inspired routing protocol based on ant colony optimization. It is an adaptive hybrid algorithm that combines reactive and proactive routing. The document provides background on mobile ad hoc networks and routing protocols. It describes how AntHocNet works, comparing it to other routing protocols like AODV and DSR. The paper then discusses the network simulation setup used to evaluate and compare the performance of AntHocNet, AODV and DSR based on metrics like packet delivery ratio, end-to-end delay, and throughput. The simulation was conducted in NS2 with
Every cluster comprise of a leader which is known as cluster head. The cluster head will be chosen by the sensor nodes in the individual cluster or be pre-assigned by the user. The main advantages of clustering are the transmission of aggregated data to the base station, offers scalability for huge number of nodes and trims down energy consumption. Fundamentally, clustering could be classified into centralized clustering, distributed clustering and hybrid clustering. In centralized clustering, the cluster head is fixed. The rest of the nodes in the cluster act as member nodes. In distributed clustering, the cluster head is not fixed. The cluster head keeps on shifting form node to node within the cluster on the basis of some parameters. Hybrid clustering is the combination of both centralized clustering and distributed clustering mechanisms. This paper gives a brief overview on clustering process in wireless sensor networks. A research on the well evaluated distributed clustering algorithm Low Energy Adaptive Clustering Hierarchy (LEACH) and its followers are portrayed artistically. To overcome the drawbacks of these existing algorithms a hybrid distributed clustering model has been proposed for attaining energy efficiency to a larger scale.
This document proposes a hybrid optimization algorithm using ant colony optimization and particle swarm optimization to solve the multiobjective multicast routing problem in wireless sensor networks. The goal is to optimize two objectives simultaneously - end-to-end delay and total transmitted power. ACO and PSO are combined to find Pareto-optimal solutions efficiently. Simulation results show the algorithm can find near-optimal solutions for minimizing delay and power consumption when routing data from a source to multiple destinations in wireless sensor networks.
IMPROVEMENTS IN ROUTING ALGORITHMS TO ENHANCE LIFETIME OF WIRELESS SENSOR NET...IJCNCJournal
Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited
computation, communication, memory, and energy resources that are being used fora huge range of
applications. Clustering in WSNs is an effective way to minimize the energy consumption of sensor nodes.
In this paper improvements in various parameters are compared for three different routing algorithms.
First, it is started with Low Energy Adaptive Cluster Hierarchy (LEACH)which is a famed clustering
mechanism that elects a CH based on the probability model. Then, work describes a Fuzzy logic system
initiated CH selection algorithm for LEACH. Then Artificial Bee Colony (ABC)which is an optimisation
protocol owes its inspiration to the exploration behaviour of honey bees. In this study ABC optimization
algorithm is proposed for fuzzy rule selection. Then, the results of the three routing algorithms are
compared with respect to various parameters
OPTIMAL CLUSTERING AND ROUTING FOR WIRELESS SENSOR NETWORK BASED ON CUCKOO SE...ijassn
The document describes a proposed approach for optimal clustering and routing in wireless sensor networks based on cuckoo search and multi-objective genetic algorithms. The cuckoo search algorithm is used to create clusters with sensor nodes within an egg laying radius of a trigger node, selected based on residual energy. Within each cluster, a multi-objective genetic algorithm with Pareto ranking is used to select an optimal node for data forwarding, aiming to maximize network lifetime and minimize transmission delay. The proposed approach combines cuckoo search for energy-efficient clustering with multi-objective optimization for optimal intra-cluster routing, seeking to prolong network lifetime, reduce packet loss, and improve throughput compared to existing techniques like LEACH.
1) The document presents a firefly-optimized routing algorithm for mobile ad hoc networks (MANETs). It aims to improve route acquisition efficiency over MANETs using the firefly algorithm.
2) The proposed algorithm models firefly behavior to select optimal routes. Fireflies communicate via flashing lights, and the algorithm models this to determine the best next hop.
3) Simulation results show the firefly-optimized routing algorithm outperforms AOMDV in terms of packet delivery ratio, packet loss, throughput, and end-to-end delay. The algorithm adapts well to dynamic network changes.
HERF: A Hybrid Energy Efficient Routing using a Fuzzy Method in Wireless Sens...ijdpsjournal
Wireless Sensor Network (WSN) is one of the major research areas in computer network field today.Data
dissemination is an important task performed by wireless sensor networks. The routing algorithms of this
network depend on a number of factors such as application areas, usage condition, power, aggregation
parameters. With respect to these factors, different algorithms are recommended. One of the most
important features of routing algorithms is their flexibility and ability to self-organize themselves
according to such parameters. The existence of flexibility in routing protocols can satisfy calls for on
demand and table driven methods. Switching between these two methods would be impossible except by
compatibility between nodes' and switcher. Energy is another significant factor in wireless sensor
networks due to limited battery power and their exchangeability. To arrive at a network with mentioned
features, we have proposed an algorithm for hybrid energy efficient routing in wireless sensor networks
which uses two algorithms, i.e. EF-Tree (Earliest-First Tree) and SID (Source-Initiated Dissemination) to
disseminate data, and employs a fuzzy method to choose cluster head, and to switch between two
methods, i.e. SID and EF-Tree. In this routing, the whole network is clustered and the appropriate clusterhead
is selected according to fuzzy variables. Then, analyzing the changes in fuzzy variables and If fuzzy,
then rule, one routing in EF-Tree or SID is chosen for information transmission. The results of
simulations indicate that HERF has improved energy efficiency.
This document summarizes a research paper that proposes using a genetic algorithm to efficiently cluster wireless sensor nodes. The genetic algorithm aims to minimize the total communication distance between sensors and the base station in order to prolong the network lifetime. Simulation results showed that the genetic algorithm can quickly find good clustering solutions that reduce energy consumption compared to previous clustering methods. The full paper provides details on wireless sensor networks, related clustering algorithms, genetic algorithms, and the proposed genetic algorithm-based clustering method.
Paper 3 energy efficient bee routing algorithm in wireless mobileSpandan Spandy
This document describes an energy efficient bee routing algorithm for wireless mobile networks. It discusses how bee colony optimization can inspire an energy-efficient routing protocol. The key points are:
1) The algorithm uses two agent types - scouts to discover paths and foragers to evaluate paths based on predicted energy consumption and delay.
2) It aims to find the optimal path between source and destination that consumes the least amount of energy overall.
3) The algorithm calculates energy consumption at each node and for the entire path to determine the "goodness ratio" and select the best path.
4) The algorithm was simulated in NS2 and results showed it improves metrics like routing overhead, delivery ratio, and energy
Data Dissemination in Wireless Sensor Networks: A State-of-the Art SurveyCSCJournals
A wireless sensor network is a network of tiny nodes with wireless sensing capacity for data collection processing and further communicating with the Base Station this paper discusses the overall mechanism of data dissemination right from data collection at the sensor nodes, clustering of sensor nodes, data aggregation at the cluster heads and disseminating data to the Base Station the overall motive of the paper is to conserve energy so that lifetime of the network is extended this paper highlights the existing algorithms and open research gaps in efficient data dissemination.
INCREASING WIRELESS SENSOR NETWORKS LIFETIME WITH NEW METHODijwmn
One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the
performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to
use node energy supply effectively and increasing network lifetime. As a consequence, it is crucial to use
routing algorithms result in decrease energy consumption and better bandwidth utilization. The purpose of
this paper is to increase Wireless Sensor Networks lifetime using LEACH-algorithm. So before clustering
Network environment, it is divided into two virtual layers (using distance between sensor nodes and base
station) and then regarding to sensors position in each of two layers, residual energy of sensor and
distance from base station is used in clustering. In this article, we compare proposed algorithm with wellknown LEACH and ELEACH algorithms in homogenous environment (with equal energy for all sensors)
and heterogeneous one (energy of half of sensors get doubled), also for static and dynamic situation of base
station. Results show that our proposed algorithm delivers improved performance.
This document summarizes and compares various clustering protocols for wireless sensor networks. It discusses clustering parameters like number of clusters and node mobility. It also classifies clustering algorithms into two main categories: probabilistic (e.g. LEACH) and non-probabilistic (e.g. weight-based and graph-based). Popular probabilistic protocols like LEACH, EEHC and HEED are described. Non-probabilistic protocols discussed include those based on node proximity, weights, and biologically inspired approaches. Overall, the document provides an overview of different clustering algorithm types and compares their advantages and disadvantages.
Optimization of workload prediction based on map reduce frame work in a cloud...eSAT Journals
Abstract Nowadays cloud computing is emerging Technology. It is used to access anytime and anywhere through the internet. Hadoop is an open-source Cloud computing environment that implements the Googletm MapReduce framework. Hadoop is a framework for distributed processing of large datasets across large clusters of computers. This paper proposes the workload of jobs in clusters mode using Hadoop. MapReduce is a programming model in hadoop used for maintaining the workload of the jobs. Depend on the job analysis statistics the future workload of the cluster is predicted for potential performance optimization by using genetic algorithm. Key Words: Cloud computing, Hadoop Framework, MapReduce Analysis, Workload
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
This document is a thesis submitted by Rahul Gupta to Thapar University in partial fulfillment of the requirements for a Master of Technology degree in Computer Science and Applications. The thesis is supervised by Dr. Rajesh Kumar and proposes a Firefly Algorithm based optimized routing protocol for Mobile Ad-Hoc Networks (MANETs) to address issues with dynamic topology changes and limited resources in MANETs. The thesis provides background on MANETs, routing protocols, swarm intelligence and the Firefly Algorithm. It then describes the proposed Firefly based routing algorithm and evaluates its performance compared to the Ad-Hoc On-Demand Multipath Distance Vector routing protocol through network simulation experiments.
A NOVEL ROUTING PROTOCOL FOR TARGET TRACKING IN WIRELESS SENSOR NETWORKSIJCNCJournal
Wireless sensor networks (WSNs) are large scale integration consists of hundreds or thousands or more
number of sensor nodes. They are tiny, low cost, low weight, and limited battery, primary storage,
processing power. They have wireless capabilities to monitor physical or environmental conditions. This
paper compared the performance analysis of some existing routing protocols for target tracking
application with proposed hierarchical binary tree structure to store the routing information. The sensed
information is stored in controlled way at multiple sensor nodes (e.g. node, parent node and grandparent
node) which deployed using complete binary tree data structure. This reduces traffic implosion and
geographical overlapping. Simulation result showed improved network lifetime by 20%, target detection
probability by 25%, and reduces error rate by 20%, energy efficiency, fault tolerance, and routing
efficiency. We have evaluated our proposed algorithm using NS2.
A Fast Convergence and Quick Route Updates Based Energy Aware Tree-Based Rout...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A QoI Based Energy Efficient Clustering for Dense Wireless Sensor Networkijassn
In a wireless sensor network Quality of Information (QoI), Energy Efficiency, Redundant data avoidance,
congestion control are the important metrics that affect the performance of wireless sensor network. As
many approaches were proposed to increase the performance of a wireless sensor network among them
clustering is one of the efficient approaches in sensor network. Many clustering algorithms concentrate
mainly on power Optimization like FSCH, LEACH, and EELBCRP. There is necessity of the above
metrics in wireless sensor network where nodes are densely deployed in a given network area. As the nodes
are deployed densely there is maximum possibility of nodes appear in the sensing region of other nodes. So
there exists an option that nodes have to send the information that is already reached the base station by its
own cluster members or by members of other clusters. This mechanism will affect the QoI, Energy factor
and congestion control of the wireless sensor networks. Even though clustering uses TDMA (Time Division
Multiple Access) for avoiding congestion control for intra clustering data transmission, but it may fail in
some critical situation. This paper proposed a energy efficient clustering which avoid data redundancy in a
dense sensor network until the network becomes sparse and hence uses the TDMA efficiently during high
density of the nodes.
Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Eff...CSCJournals
The objective of this paper is to develop a mechanism to increase the lifetime of homogeneous wireless sensor networks (WSNs) through minimizing long range communication, efficient data delivery and energy balancing. Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. To achieve energy balancing and maximizing network lifetime we divided the whole network into different clusters. In cluster based architecture, the role of aggregator node is very crucial because of extra processing and long range communication. Once the aggregator node becomes non functional, it affects the whole cluster. We introduced a candidate cluster head node on the basis of node density. We proposed a modified cluster based WSN architecture by introducing a server node (SN) that is rich in terms of resources. This server node (SN) takes the responsibility of transmitting data to the base station over longer distances from the cluster head. We proposed cluster head selection algorithm based on residual energy, distance, reliability and degree of mobility. The proposed method can save overall energy consumption and extend the lifetime of the sensor network and also addresses robustness against even/uneven node deployment.
Comparison of different Ant based techniques for identification of shortest p...IOSR Journals
This document compares different ant colony optimization (ACO) techniques for identifying the shortest path in a distributed network. ACO is based on the behavior of ants finding food sources and uses pheromone trails to probabilistically determine paths. The document reviews several ACO algorithms and techniques, including Max-Min, rank-based, and fuzzy rule-based approaches. It then implements an efficient ACO algorithm that performs better at finding the shortest path compared to other existing ACO techniques.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
STUDY AND PERFORMANCE EVALUATION OF ANTHOCNET AND BEEHOCNET NATURE INSPIRED M...IAEME Publication
This document discusses nature-inspired routing protocols for mobile ad hoc networks (MANETs) and summarizes the Anthocnet and Beehocnet routing protocols. It begins by providing background on MANETs and swarm intelligence approaches. It then describes how Anthocnet uses forward and backward ants to discover and maintain routes similarly to ant colony behavior. Beehocnet is proposed as an extension using different agent types like packers, scouts, and foragers inspired by honeybee behavior. The document evaluates the performance of these protocols through simulation using the NS-2 network simulator.
PERFORMANCE ANALYSIS OF ANTHOCNET ROUTING PROTOCOL FOR HYBRID AD HOC NETWORKKhushbooGupta145
This document summarizes a research paper that analyzes the performance of the AntHocNet routing protocol for hybrid ad hoc networks. AntHocNet is a bio-inspired routing protocol based on ant colony optimization. It is an adaptive hybrid algorithm that combines reactive and proactive routing. The document provides background on mobile ad hoc networks and routing protocols. It describes how AntHocNet works, comparing it to other routing protocols like AODV and DSR. The paper then discusses the network simulation setup used to evaluate and compare the performance of AntHocNet, AODV and DSR based on metrics like packet delivery ratio, end-to-end delay, and throughput. The simulation was conducted in NS2 with
This document reviews the use of ant colony optimization algorithms for wireless sensor networks. It begins with background on wireless sensor networks and important concepts like sensor nodes, clusters, cluster heads, and base stations. It then discusses routing protocols for wireless sensor networks including location-based, data-centric, mobility-based, and multipath-based protocols. The document provides an overview of ant colony optimization algorithms and reviews several related works that have applied these algorithms to problems in wireless sensor networks, such as sensor wakeup control and increasing network lifetime. It concludes by discussing techniques like data mining and ant colony optimization that could be used to improve wireless sensor network performance.
Ant Colony Optimization for Wireless Sensor Network: A Reviewiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Study on security and quality of service implementations in p2 p overlay netw...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Routing Enhancement of MANETs using Hybrid Protocol Combined with PBOIJERA Editor
Mobile ad hoc Networks (MANETs) show an astonishing qualities in the concept of networks which are used without wires. MANETs experience numerous communication medium restrictions such as constrained storage of memory and development of effectual routing protocols. Furthermore, multihop routing mechanism employed in MANETs gives rise to the contention in the channel and jamming within the network. This limits the effectiveness of the network which reduces the energy efficiency of the network and also lessens the routing performance of MANETs. Hence, the major matter in MANETs is to minimize the congestion and contention in order to enhance the routing mechanism. Hence, in this paper, a novel protocol is put into practice having an enhanced route discovery mechanism which is implemented in order to avoid the congestion during the routing. The proposed protocol chooses the route for the transference of information on the basis of load within the traffic on the node and then resets the route with the change in topology. The protocol is then integrated with the proposed algorithm Pollination Based Optimization (PBO) algorithm. This is an efficient technique for transmission that requires a link for longer period of time. The simulator used for the simulation of the work is Network Simulator-2 (NS-2). Simulation results have been carried out showing that the route optimization and enhancement in the route discovery using Pollination Based Optimization (PBO) algorithm.
An Energy-Efficient Min-Max Optimization with RSA Security in Wireless Sensor...IJMTST Journal
A Novel Energy-efficient Min-max Optimization (NEMO) is proposed to improve the data delivery
performance and provide security in WSN. The NEMO scheme is applied in the virtual grid environment to
periodically collect the data from source node to the mobile sink through the cell headers. Here the movement
of sink is in controlled fashion and collects the data from the border line cell headers. For efficient data
delivery Fruit Fly Optimization (FFO) algorithm is applied here to find the best path by using the fitness value
calculated between the nodes based on the distance. The optimal path is chosen by first calculating the
minimum hop count paths and then finds the maximum of total fitness value along those paths. In that way
best path is selected by considering the shortest path which improves the data delivery performance and
also it minimizes the energy consumption. The proposed scheme enables the sensor nodes to maintain the
optimal path towards the latest location of mobile sink by using the FFO algorithm which leads to maximize
the network lifetime in wireless sensor networks. RSA digital signature is used to provide the security
between the intermediate nodes during the data delivery. The source node generates the keys and broadcast
it to all other nodes in the network. Source node signs the data using its private key and the intermediate
nodes verifies the data using the source’s public key which is already broadcasted by the source node. If the
data is valid then it forwards to the next intermediate nodes and till the sink node gets the data, forwarding
takes place. Else the data packets are dropped and inform that node as misbehaving node and the source
chooses the next best path without having that misbehaving node in the path..
This document describes a study that designed and implemented a Mobile AntNet routing algorithm for mobile ad hoc networks based on the original AntNet algorithm. The researchers used the NS-2 simulator to model the Mobile AntNet algorithm and compare its performance to other routing protocols. Simulation results showed that the Mobile AntNet algorithm performed well in terms of throughput, packet loss, and ability to handle node failures in the mobile ad hoc network environment.
Network Lifespan Maximization For Wireless Sensor Networks Using Nature-Inspi...IOSR Journals
This document proposes an Elephant Based Swarm Optimization (EBSO) approach to maximize the lifespan of wireless sensor networks. It models the wireless sensor network and describes elephants' social behavior that is inspiring the approach. Elephants exhibit unselfish behavior, strong memory, and ability to communicate and survive in large groups. The EBSO approach aims to adopt these behaviors through a cross-layer optimization of routing, MAC scheduling, and radio link parameters. It compares EBSO to LEACH and PSO protocols, showing EBSO extends network lifetime by balancing energy usage across nodes.
IRJET- A Study in Wireless Sensor Network (WSN) using Artificial Bee Colony (...IRJET Journal
This document discusses using an artificial bee colony (ABC) algorithm with dynamic technique for wireless sensor networks (WSN). The ABC algorithm is an optimization algorithm inspired by bee colonies that can be applied to cluster formation in WSNs. The paper proposes studying WSNs using both the ABC algorithm and dynamic technique to analyze and compare the two approaches. It provides background on WSN topologies, an overview of how the ABC algorithm works, and a review of related literature applying ABC and other algorithms to improve energy efficiency and lifespan in WSNs.
This document summarizes a research paper that proposes enhancing classification schemes for spatial data mining using bio-inspired optimization approaches. The paper aims to compare the performance of a hybrid K-means and Ward's clustering method optimized with honeybee optimization and firefly optimization algorithms. Spatial data mining involves discovering patterns in spatial databases, which can be more difficult than other data types due to complex spatial relationships. The paper outlines spatial data mining and clustering techniques. It then proposes a hybrid clustering algorithm combined with honeybee optimization and firefly optimization to enhance classification performance measured by precision, recall, and other metrics.
Ant colony optimization based routing algorithm in various wireless sensor ne...Editor Jacotech
Wireless Sensor Network has several issues and challenges due to limited battery backup, limited computation capability, and limited computation capability. These issues and challenges must be taken care while designing the algorithms to increase the Network lifetime of WSN. Routing, the act of moving information across an internet world from a source to a destination is one of the vital issue associated with Wireless Sensor Network. The Ant Colony Optimization (ACO) algorithm is a probabilistic technique for solving computational problems that can be used to find optimal paths through graphs. The short route will be increasingly enhanced therefore become more attractive. The foraging behavior and optimal route finding capability of ants can be the inspiration for ACO based algorithm in WSN. The nature of ants is to wander randomly in search of food from their nest. While moving, ants lay down a pheromone trail on the ground. This chemical pheromone has the ability to evaporate with the time. Ants have the ability to smell pheromone. When selecting their path, they tend to select, probably the paths that has strong pheromone concentrations. As soon as an ant finds a food source, carries some of it back to the nest. While returning, the quantity of chemical pheromone that an ant lay down on the ground may depend on the quantity and quality of the food. The pheromone trails will lead other ants towards the food source. The path which has the strongest pheromone concentration is followed by the ant which is the shortest paths between their nest and food source. This paper surveys the ACO based routing in various Networking domains like Wireless Sensor Networks and Mobile Ad Hoc Networks.
Ant Colony Optimization Based Energy Efficient on-Demand Multipath Routing Sc...ijsrd.com
Reliable transmission has become one of the major aspects of a wireless sensor network. The current paper provides an Ant Colony Optimization based method for providing multi path routes. These routes are provided on-demand, hence they can be used in any dynamic system. The advantage of this system is that it can provide near optimal results within the stipulated time.
This document presents an implementation of an ant colony optimization adaptive network-on-chip routing framework using a network information region. The proposed method combines backward ant mechanism with a network information region framework to improve network performance, area efficiency, and reduce congestion. Simulation results show that updating routing tables is faster with the proposed method, leading to improved network performance and area efficiency while reducing congestion compared to other approaches.
Route optimization in manets with aco and ga eSAT Journals
This document summarizes a research paper that proposes a hybrid optimization algorithm called GA-API for route optimization in mobile ad hoc networks (MANETs). The GA-API algorithm combines ant colony optimization (ACO), specifically the artificial prey inspired (API) algorithm, with a genetic algorithm (GA). API is used first to find multiple feasible paths between source and destination nodes in the MANET. These paths are then input to the GA, which forms a population of routing solutions. The GA explores this solution space using genetic operators like crossover and mutation to find new paths. Promising solutions from the GA are then fed back to API to avoid it getting stuck in local optima. The goal of the hybrid GA-API algorithm is
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
This document compares the performance of three routing protocols for mobile ad hoc networks (MANETs) - DSDV, AODV, and an ant colony optimization (ACO) based protocol. It presents the results of simulations run using the NS-2 network simulator. The simulations varied the number of nodes and compared the end-to-end delay, packet delivery ratio, and packet delivery fraction of the three protocols. The results showed that as network complexity increased with more nodes, the ACO based protocol performed better than AODV and DSDV in terms of lower delay and higher delivery rates, particularly for larger network sizes.
AN EFFICIENT ROUTING PROTOCOL FOR MOBILE AD HOC NETWORK FOR SECURED COMMUNICA...pijans
Security and reliable communication is challenging task in mobile Ad Hoc network. Through mobility of
network device compromised with attack and loss of data. For the prevention of attack and reliable
communication, various authors proposed a method of secured routing protocol such as SAODV and SBRP
(secured backup routing protocol). The process of these methods work along with route discovery and
route maintains, discovery and route maintained needed more power consumption for that process. The
power of devices is decrease during such process and network lifetimes expire. In this paper, we modified
the secured stateless protocol for secured routing and minimized the utilization of power during path
discovering and establishment. For the authentication of group node used group signature technique and
sleep mode threshold concept for power minimization. Our proposed technique is simulated in ns-2 and
compare to other routing protocol gives a better performance in comparison to energy consumption and
throughput of network.
Similar to Optimal Data Collection from a Network using Probability Collectives (Swarm Based) (20)
Exploratory study on the use of crushed cockle shell as partial sand replacem...IJRES Journal
The increasing demand for natural river sand supply for the use in construction industry along
with the issue of environmental problem posed by the dumping of cockle shell, a by-product from cockle
business have initiated research towards producing a more environmental friendly concrete. This research
explores the potential use of cockle shell as partial sand replacement in concrete production. Cockle shell used
in this experimental work were crushed to smaller size almost similar to sand before mixed in concrete. A total
of six concrete mixtures were prepared with varying the percentages of cockle shell viz. 0%, 5%, 10%, 15%,
20% and 25%. All the specimens were subjected to continuous water curing. The compressive strength test was
conducted at 28 days in accordance to BS EN 12390. Finding shows that integration of suitable content of
crushed cockle shell of 10% as partial sand replacement able to enhance the compressive strength of concrete.
Adopting crushed cockle shell as partial sand replacement in concrete would reduce natural river sand
consumption as well as reducing the amount of cockle shell disposed as waste.
Congenital Malaria: Correlation of Umbilical Cord Plasmodium falciparum Paras...IJRES Journal
The vertical (trans-placental) transmission of the parasite Plasmodium falciparum from
pregnant mother to fetus during gestational period was investigated in a clinical research involving 43 full term
pregnant women in selected Hospitals in Jimeta Yola, Adamawa State Nigeria. During the observational study,
parasitemia was determined by light microscopic examination of umbilical and maternal peripheral blood film
for the presence of the trophozoites of Plasmodium falciparum. Correlational analysis was then carried on the
result obtained at p<0.05.><0.05) was established between maternal peripheral blood and umbilical cord
blood parasitemia with Pearson’s correlation coefficient of 0.762. Thus, in a malaria endemic area like Yola,
Adamawa State, Nigeria, with a stable transmission of parasite, there is a high probability of vertical
transmission of Plasmodium falciparum parasite from mother to fetus during gestation that can be followed by
the presentation of the symptoms of malaria by the newborn and other malaria related complications. Families
are advised to consistently sleep under appropriately treated insecticide mosquito net to avoid mosquito bite and
subsequent infestation.
Review: Nonlinear Techniques for Analysis of Heart Rate VariabilityIJRES Journal
Heart rate variability (HRV) is a measure of the balance between sympathetic mediators of heart
rate that is the effect of epinephrine and norepinephrine released from sympathetic nerve fibres acting on the
sino-atrial and atrio-ventricular nodes which increase the rate of cardiac contraction and facilitate conduction at
the atrio-ventricular node and parasympathetic mediators of heart rate that is the influence of acetylcholine
released by the parasympathetic nerve fibres acting on the sino-atrial and atrio-ventricular nodes leading to a
decrease in the heart rate and a slowing of conduction at the atrio-ventricular node. Sympathetic mediators
appear to exert their influence over longer time periods and are reflected in the low frequency power(LFP) of
the HRV spectrum (between 0.04Hz and 0.15 Hz).Vagal mediators exert their influence more quickly on the
heart and principally affect the high frequency power (HFP) of the HRV spectrum (between 0.15Hz and 0.4
Hz). Thus at any point in time the LFP:HFP ratio is a proxy for the sympatho- vagal balance. Thus HRV is a
valuable tool to investigate the sympathetic and parasympathetic function of the autonomic nervous system.
Study of HRV enhance our understanding of physiological phenomenon, the actions of medications and disease
mechanisms but large scale prospective studies are needed to determine the sensitivity, specificity and predictive
values of heart rate variability regarding death or morbidity in cardiac and non-cardiac patients. This paper
presents the linear and nonlinear to analysis the HRV.
Dynamic Modeling for Gas Phase Propylene Copolymerization in a Fluidized Bed ...IJRES Journal
The document presents a dynamic two-phase model for a fluidized bed reactor used to produce polypropylene. The model divides the reactor into an emulsion phase and bubble phase, with reaction assumed to occur in both phases. Simulation results show the temperature profile is lower than previous single-phase models due to considering both phases. Approximately 13% of the produced polymer comes from the bubble phase, demonstrating the importance of accounting for both phases.
Study and evaluation for different types of Sudanese crude oil propertiesIJRES Journal
Sudanese crude oil is regarded as one of the sweet types of crude in the world, Sulphur containing
compounds are un desirable in petroleum because they de activate the catalyst during the refining processes and
are the main source of acid rains and environmental pollution.(Mark Cullen 2001),Since it contains considerable
amount of salts and acids, it negatively impact the production facilities and transportation lines with corrosive
materials. However it suffers other problems in flow properties represented by the high viscosity and high
percentage of wax. Samples were collected after the initial and final treatment at CPF, and tested for
physical and chemical properties.wax content is in the range 23-31 weight % while asphalting content is about
0.1 weight% . Resin content is 13-7 weight % and deposits are 0.01 weight%. The carbon number distribution in
the crude is in the range 7-35 carbon atoms. The pour point vary between 39°C-42°C and the boiling point is in
the range 70 °C - 533 °C.
A Short Report on Different Wavelets and Their StructuresIJRES Journal
This article consists of basics of wavelet analysis required for understanding of and use of wavelet
theory. In this article we briefly discuss about HAAR wavelet transform their space and structures.
A Case Study on Academic Services Application Using Agile Methodology for Mob...IJRES Journal
Recently, Mobile Cloud Computing reveals many modern development areas in the Information
Technology industry. Several software engineering frameworks and methodologies have been developed to
provide solutions for deploying cloud computing resources on mobile application development. Agile
methodology is one of the most commonly used methodologies in the field. This paper presents the MCCAS a
Web and Mobile application that provide feature for the Palestinian higher education/academic institutions. An
Agile methodology was used in the development of the MCCAS but in parallel with emphasis on Cloud
computing resources deployment. Also many related issues is discussed such as how software engineering
modern methodologies (advances) influenced the development process.
Wear Analysis on Cylindrical Cam with Flexible RodIJRES Journal
Firstly, the kinetic equation of spatial cylindrical cam with flexible rod has been established. Then, an
accurate cylindrical cam mechanism model has been established based on the spatial modeling software
Solidworks. The dynamic effect of flexible rod on mechanical system was studied in detail based on the
mechanical system dynamics analytical software Adams, and Archard wear model is used to predict the wear of
the cam. We used Ansys to create finite element model of the cam link, extracted the first five order mode to
export into Adams. The simulation results show that the dynamic characteristics of spatial cylindrical cam
mechanical system with flexible rod is closed to ideal mechanism. During the cam rotate one cycle, the collision
in the linkage with a clearance occurs in some special location, others still keep a continuous contact, and the
prediction of wear loss is smaller than rigid body.
DDOS Attacks-A Stealthy Way of Implementation and DetectionIJRES Journal
Cloud Computing is a new paradigm provides various host service [paas, saas, Iaas over the internet.
According to a self-service,on-demand and pay as you use business model,the customers will obtain the cloud
resources and services.It is a virtual shared service.Cloud Computing has three basic abstraction layers System
layer(Virtual Machine abstraction of a server),Platform layer(A virtualized operating system, database and
webserver of a server and Application layer(It includes Web Applications).Denial of Service attack is an attempt
to make a machine or network resource unavailable to the intended user. In DOS a user or organization is
deprived of the services of a resource they would normally expect to have.A Successful DOS attack is a highly
noticeable event impacting the entire online user base.DOS attack is found by First Mathematical Metrical
Method (Rate Controlling,Timing Window,Worst Case and Pattern Matching)DOS attack not only affect the
Quality of the service and also affect the performance of the server. DDOS attacks are launched from Botnet-A
large Cluster of Connected device(cellphone,pc or router) infected with malware that allow remote control by an
attacker. Intruder using SIPDAS in DDOS to perform attack.SIPDAS attack strategies are detected using Heap
Space Monitoring Algorithm.
An improved fading Kalman filter in the application of BDS dynamic positioningIJRES Journal
Aiming at the poor dynamic performance and low navigation precision of traditional fading
Kalman filter in BDS dynamic positioning, an improved fading Kalman filter based on fading factor vector is
proposed. The fading factor is extended to a fading factor vector, and each element of the vector corresponds to
each state component. Based on the difference between the actual observed quantity and the predicted one, the
value of the vector is changed automatically. The memory length of different channel is changed in real time
according to the dynamic property of the corresponding state component. The actual observation data of BDS is
used to test the algorithm. The experimental results show that compared with the traditional fading Kalman filter
and the method of the third references, the positioning precision of the algorithm is improved by 46.3% and
23.6% respectively.
Positioning Error Analysis and Compensation of Differential Precision WorkbenchIJRES Journal
The document analyzes positioning errors in differential precision workbenches and proposes a compensation method. It discusses sources of error in workbench transmission systems and guides. Through theoretical analysis and experimentation, it is shown that positioning errors increase with travel distance due to factors like guideway errors. A method is developed to sample positioning at multiple points, compare values to identify errors, and implement reverse error correction through motion control cards. This allows positioning accuracy better than 15 micrometers over 150mm of travel to be achieved. The compensation method can improve precision for a range of machine tool designs.
Status of Heavy metal pollution in Mithi river: Then and NowIJRES Journal
The Mithi River runs through the heart of suburban Mumbai. Its path of flow has been severely
damaged due to industrialization and urbanization. The quality of water has been deteriorating ever since. The
Municipal and industrial effluents are discharged in unchecked amounts. The municipal discharge comprises
untreated domestic and sewage wastes whereas the industries are majorly discharge chemicals and other toxic
effluents which are responsible in increasing the metal load of the river. In the current study, the water is
analysed for heavy metals- Copper, Cadmium, Chromium, Lead and Nickel. It also includes a brief
understanding on the fluctuations that have occurred in the heavy metal pollution, through the compilation of
studies carried out in the area previously.
The Low-Temperature Radiant Floor Heating System Design and Experimental Stud...IJRES Journal
In order to analyze the temperature distribution of the low-temperature radiant floor heating system
that uses the condensing wall-hung boiler as the heat source, the heating system is designed according to a typical
house facing south in Shanghai. The experiments are carried out to study the effects of the supply water
temperature on the thermal comfort of the system. Eventually, the supply water temperature that makes people in
the room feel more comfortable is obtained. The result shows that in the condition of that the outside temperature
is 8~15℃ and the relative humidity is 30~70%RH, the temperature distribution in the room is from high to low
when the height is from bottom to top. The floor surface temperature is highest, but its uniformity is very poor.
When the heating system reaches the steady state, the air temperature of the room is uniform. When the supply
water temperature is 63℃ The room is relatively comfortable at the above experimental condition.
Experimental study on critical closing pressure of mudstone fractured reservoirsIJRES Journal
This study examines the critical closing pressure of fractures in mudstone reservoir cores from the Daqing oilfield in China. Laboratory experiments subjected fractured and unfractured mudstone cores to increasing external pressures while measuring permeability. The critical closing pressure is defined as the pressure when fractured core permeability matches unfractured permeability, indicating fracture closure. Results show fractured cores have higher permeability than unfractured cores due to fractures. Permeability generally decreases exponentially with increasing pressure. By calculating sensitivity equations relating permeability and production pressure difference, the study estimates critical closing pressures under reservoir conditions are lower than values from external pressure experiments. The study provides guidance but notes limitations in fully simulating complex in-situ stress conditions.
Correlation Analysis of Tool Wear and Cutting Sound SignalIJRES Journal
With the classic signal analysis and processing method, the cutting of the audio signal in time
domain and frequency domain analysis. We reached the following conclusions: in the time domain analysis,
cutting audio signals mean and the variance associated with tool wear state change occurred did not change
significantly, and tool wear is not high degree of correlation, and the mean-square value of the audio signal
changes in the size and tool wear the state has a good relationship.
Reduce Resources for Privacy in Mobile Cloud Computing Using Blowfish and DSA...IJRES Journal
Mobile cloud computing in light of the increasing popularity among users of mobile smart
technology which is the next indispensable that enables users to take advantage of the storage cloud computing
services. However, mobile cloud computing, the migration of information on the cloud is reliable their privacy
and security issues. Moreover, mobile cloud computing has limitations in resources such as power energy,
processor, Memory and storage. In this paper, we propose a solution to the problem of privacy with saving and
reducing resources power energy, processor and Memory. This is done through data encryption in the mobile
cloud computing by symmetric algorithm and sent to the private cloud and then the data is encrypted again and
sent to the public cloud through Asymmetric algorithm. The experimental results showed after a comparison
between encryption algorithms less time and less time to decryption are as follows: Blowfish algorithm for
symmetric and the DSA algorithm for Asymmetric. The analysis results showed a significant improvement in
reducing the resources in the period of time and power energy consumption and processor.
Resistance of Dryland Rice to Stem Borer (Scirpophaga incertulas Wlk.) Using ...IJRES Journal
Rice stem borer is one of the important pests that attack plants so as to reduce production. One way
to control pests is to use organic fertilizers that make the plant stronger and healthier. This study was conducted
to determine the effects of organic fertilizers with various doses without the use of pesticides in controlling stem
borer, Scirpophaga incertulas. Methods using split-split plot design which consists of two levels of the whole
plot factor (solid and liquid organic fertilizers), two levels of the subplot factor (conventional and industry,
Tiens and Mitraflora), and four levels of the sub-subplot factor of conventional and industry (5, 10, 15, 20
tonnes/ha), and one level of the sub-subplot factor of Tiens and Mitraflora (each 2 ml/l). Based on the results
Statistical analysis there were no significant differences among treatments and this shows that the use of organic
fertilizers that only a dose of 5 tonnes/ha is sufficient available nutrients that make plants more robust and
resistant to control stem borer, besides that can reduce production costs and friendly to the environment when
compared with using inorganic fertilizers.
A novel high-precision curvature-compensated CMOS bandgap reference without u...IJRES Journal
A novel high-precision curvature-compensated bandgap reference (BGR) without using op-amp
is presented in this paper. It is based on second-order curvature correction principle, which is a weighted sum of
two voltage curves which have opposite curvature characteristic. One voltage curve is achieved by first-order
curvature-compensated bandgap reference (FCBGR) without using op-amp and the other found by using W
function is achieved by utilizing a positive temperature coefficient (TC) exponential current and a linear
negative TC current to flow a linear resistor. The exponential current is gained by using anegative TC voltage to
control a MOSFET in sub-threshold region. In the temperature ranging from -40℃ to 125℃, experimental
results implemented with SMIC 0.18μm CMOS process demonstrate that the presented BGR can achieve a TC
as low as 2.2 ppm/℃ and power-supply rejection ratio(PSRR)is -69 dB without any filtering capacitor at 2.0 V.
While the range of the supply voltage is from 1.7 to 3.0 V, the output voltage line regulation is about1 mV/ V
and the maximum TC is 3.4 ppm/℃.
Structural aspect on carbon dioxide capture in nanotubesIJRES Journal
In this work we reported the carbon dioxide adsorption (CO2) in six different nanostructures in order
to investigate the capturing capacity of the materials at nanoscale. Here we have considered the three different
nanotubes including zinc oxide nanotube (ZnONT), silicon carbide nanotube (SiCNT) and single walled carbon
nanotube (SWCNT). Three different chiralities such as zigzag (9,0), armchair (5,5) and chiral (6,4) having
approximately same diameter are analyzed. The adsorption binding energy values under various cases are
estimated with density functional theory (DFT). We observed CO2 molecule chemisorbed on ZnONT and
SiCNT’s whereas the physisorption is predominant in CNT. To investigate the structural aspect, the tubes with
defects are studied and compared with defect free tubes. We have also analyzed the electrical properties of tubes
from HOMO, LUMO energies. Our results reveal the defected structure enhance the CO2 capture and is
predicted to be a potential candidate for environmental applications.
Thesummaryabout fuzzy control parameters selected based on brake driver inten...IJRES Journal
In this paper, the brake driving intention identification parameters based on the fuzzy control are
summarized and analyzed, the necessary parameters based on the fuzzy control of the brake driving intention
recognition are found out, and I pointed out the commonly corrupt parameters, and through the relevant
parameters , I establish the corresponding driving intention model.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
1. International Journal of Research in Engineering and Science (IJRES)
ISSN (Online): 2320-9364, ISSN (Print): 2320-9356
www.ijres.org Volume 3 Issue 4 ǁ April. 2015 ǁ PP.49-58
www.ijres.org 49 | Page
Optimal Data Collection from a Network using Probability
Collectives (Swarm Based)
Abdulkadir Ahmed1
, Olalekan Ogunbiyi2
, Tahir Aduragba3
1
(Electrical and Computer Engineering, Kwara State University, Malete, Nigeria)
2
(Electrical and Computer Engineering, Kwara State University, Malete, Nigeria)
3
(Electrical and Computer Engineering, Kwara State University, Malete, Nigeria)
ABSTRACT: This paper contains the implementation of the BeeAdhoc algorithm for data routing in mobile Ad
Hoc Network (MANet). The algorithm was inspired by the foraging behaviour of honey bees and its
implementation mimics this behaviour. The integration was done on Network Simulator version 2 (NS-2.34)
where different scenarios were considered in comparison with other existing state-of-the-art routing algorithms
that have been implemented in the chosen simulator. The comparison was carried out between DSR, DSDV,
AOMDV which are all multipath routing algorithms as the BeeAdhoc; this gave a better insight to the different
behaviour of the algorithms on a common application environment. Throughput, end-to-end delay and routing
overhead constitute the indices used for the performance evaluation. Experimental results showed the best
performance of BeeAdhoc over, DSDV and AOMDV algorithms.
Keywords -BeeAdhoc, Network simulator, Probability collective, Routing, Swarm
I. INTRODUCTION
The Collective Intelligence (COIN) emerged in the technical report submitted to National Aeronautics and
Space Administration (NASA) by Wolpert and Tumer and in which they referred to it as any combination of
large, distributed collection of interacting computational processes in which there is little or no centralized
communication/control, together with a „global utility‟ function that rates the possible dynamic histories of the
collection [1].
Collective can be described as a group of self-motivated agents that maximise overall system performance
through improving on their local objectives [2, 3]. Probability Collectives (PC) is a framework of COIN used in
the modelling and control of distributed systems, its concept has been linked to Game theory, statistical physics
and optimization [4].
The approach of PC is an efficient means of sampling the joint probability space in order to convert the
problem under consideration into a convex space of probability distribution [2]. Approach of COIN is to design
a collective whereby every section is seen as an agent which gives an overall view of the system as a Multi-
Agent-System (MAS) [5].
Probability Collective (PC) as implemented in the COIN framework, allows each of the agents to select
actions from a group of available actions and receive reward based on the achieved objective due to the taken
action. The approach is an iterative one and reaches equilibrium in which at some point the agent‟s reward do
not increase any more for taking any action further. This equilibrium concept is known as Nash Equilibrium [3,
5, 6, 7]. According to [6, 7, 8] the advantages that could be derived from the use of PC include: It can be used to
solve problems with large number of variables, it can be used to handle constrained problems, it is a distributed
solution approach in which agents independently updates their probability distribution at any time instance and
can be applied to continuous, discrete or mixed variables, a failed agent can just be considered as one that does
not update its probability distribution and this do not have any effect on the other agents, the minimum value of
the global cost function can be derived by considering the Maxent Lagrangian equation for each agent. In view
of the above, a swarm-based system approach which focuses on honey bee behaviours was implemented in this
research.
The focus area for this research was on Ad-Hoc wireless network with mobility (MANet); an ad-hoc
network could be described as a network without any form of central control among the nodes, that is, no
installed infrastructure like routers are required. In this kind of setup the nodes serve as partial router and aid in
routing of information. This research implemented a swarm based system in routing data and comparing with
existing approaches.
The problem to be addressed in this work is that of routing and information collection in a network. This
includes the execution time of algorithms and its accompanying protocols, propagation delay, throughput and
energy consumption.
In response to the issues identified above, objectives were: to identify an appropriate modification to be
made to the algorithm, to implement the algorithm with an appropriate network protocol for simulation. It also
2. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 50 | Page
includes the incorporation of one or combination of the following features: improved resilience (i.e. faster
recovery from node/link failure), reduced energy consumption, higher throughput, and minimised execution
time.
1.1 Swarm intelligence
Swarm intelligence is the study of computational systems inspired by the „COllective INtelligence‟ (COIN).
COIN emerges through the cooperation of large numbers of homogeneous agents in the environment [9].
Literally, Swarm systems are those which mimic the behaviours of animals in optimising/solving real life
problems through simulations. Examples include schools of fish, flocks of birds, and colonies of ants. These
systems are decentralized, self-organizing and distributed in a problem domain [10]. Examples include Particle
Swarm Optimisation, Ant Colony Optimisation, Bacterial Foraging Optimisation and Bee Colony Optimisation.
Swarm based systems have been used to solve optimisation problems ranging from salesman problem to
routing of packets in data network. This research focused on the Honey Bee behaviour in the routing of packet
in a Mobile Ad Hoc Network.
The study of bee behaviour for optimisation processes did not kick off early enough because researchers do
not understand how information is being disseminated in the beehive. This became history when Nobel Laureate
„Karl Von Frisch‟ broke the jinx and structured it into a language in his book The Dance Language and
Orientation in Bees. He elaborated and explained the meanings of the dances given by the bees after each flight
back to the hive and after this, several works relating to the bee behaviour have been embarked upon.
BeeHives is one of the earliest works described in [11] that uses the honey bee behaviour to optimise the
energy consumption in routing of data in a wired data network. The work was compared with existing swarm
based system (AntNet, Distributed Genetic Algorithm (DGA)) using the Japanese Internet Backbone
(NTTNET) in OMNeT++ network simulator and was found to outperform others in most of the simulated
scenarios [11]. In the work, it was said that “Honey bees evaluate the quality of each discovered food site and
only perform a waggle dance for it on the dance floor if the quality is above a certain threshold” [11]. The dance
is abstracted into a routing table and it is used to keep track of the information received through all bees sent out
that arrives from different neighbours. Two types of bee agents are defined are short distance bee agent and
long distance bee agent; this was based on the study which revealed that more bees explore areas closest to the
hive and few going farther from the hive for exploration [11].
Short distance bee agent are only allowed to traverse few hops away from it node in gathering and
disseminating information to neighbouring nodes while the long distance bee agent can travel to all parts of the
network. The implementation assume network to be in partitions which results from the network topology as
foraging zones and foraging regions. Based on this, each node maintains information in its routing table about
routes that allow it communicate with all its zone members and a path to the representative node in the region
where it belongs for data meant for destinations beyond its coverage.
This mechanism allows the algorithm to reduce routing overhead and aid in efficient routing of data in the
network. The implementation on OMNeT++ which was compared with AntNet, Distributed Genetic Algorithm
(DGA) and Open Shortest Path First (OSPF), focused on energy consumption in routing of data in a wired
network. Beehive outperformed others in most of the simulated scenarios [11].
II. THE BEEADHOC ALGORITHM
This was inspired by the foraging behaviour of honey bees and its implementation is to optimise the routing
of data in a mobile Ad Hoc network. There are several existing algorithms such as DSR, DSDV, AODV;
designed for this type of environment and their respective performances would be compared.
BeeAdhoc routing algorithm is a reactive type of routing protocol in that paths/routes to a destination are
only discovered when there is a data to be delivered to that destination. It also uses the source routing options of
IP, in that the paths to a destination are embedded in the header of the packet which get reviewed as the packet
traverses the network.
This is implemented as a layer 3 protocol of the ISO/OSI standard and the idea of abstraction in the
standard makes the algorithm independent of lower or upper layer in addition to the ease of integration over any
platform. All nodes in its implementation are considered to be a hive and packets sent out also to be a bee. The
major mechanisms of the algorithm are the entrance, packing floor and the dance floor and also three major
types of bees are implemented.
2.1. Bee Types
The bee names are absorbed from the real honey bee colony; actually they refer to control packets and other
types used in the implementation. Three types of bees are used in this algorithm. These are the scout (for route
discovery), the forager (to transport data) and the packer (for data collection from the upper layer).
3. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 51 | Page
Packers: These are created at the packing floor whenever a packet/data arrives from the upper transport
layer (TCP/UDP) to hold the data pending when a forager to the desired destination is found. They remain in the
packing floor throughout their life time and are deleted immediately once the appropriate forager is found.
Scouts: This is similar to the route request packet used in other algorithms; it is also created in the packing
floor whenever a route to a destination is not available and it‟s used to find routes. It is a broadcast type of
packet to all neighbours, it has in the header the destination address and time to live (TTL) which are part of
regular IP header. The header option of BeeAdHoc also appends the route traversed so far and an ID to uniquely
identify each scout. All nodes that receives the scout will rebroadcast it if the destination address does not match
their address and also if the TTL has not expired. Once the scout arrives at the destination, it will be sent back to
the source using the reverse route. At the source it will be passed to the dance floor where a forager will be
created from it.
Foragers: These are the bees that transport actual packets in the network from the source node‟s hive to the
destination node‟s hive. They are kept in the dance floor. They also have an age tag attached and basically this
tag is used to note the age of the forager and this is decreased anytime it transport data until it gets to zero when
a new paths/routes will have to be requested if there‟s need to send data to the destination.
2.2. Algorithm Design and Operations
As stated earlier, each node on the network is seen as a bee hive through which the routing information is
generated and stored. Again, the nodes are independent of one another in that no control packets are exchanged
for routing to be possible.
The design focused on the ISO/OSI layer 3 (network layer) and as such interfaces to the upper transport and
lower MAC layer were part of the design. The packing floor interacts with the upper layer while the entrance
interacts with the lower layer. In between these two is the dance floor which contains the routing information.
The architectural overview is illustrated in Fig. 1.
III. ALGORITHM IMPLEMENTATION IN NS-2.34
As earlier stated, the algorithm here was based on the design from [12]; the focus area in the work discussed
there was on energy consumption of various algorithms in comparison with BeeAdhoc. The authors of the work
in [12] were contacted and the source code for their implementation was made available for use. Their
implementation was on NS-2.29, an older version compared to NS-2.34 used in this work.
On receipt of the source code, there were several compilation errors into NS-2.34 during the integration
stage; these were due to the upgrade in the library files present in NS-2.34 compared to NS-2.29. There were
also different types of special bees (throughput bee, energy bee, swarm bee etc) declared to enhance its energy
consumption which was the focus area of their work.
Fig. 1: Architecture Overview
In this implementation, all the library issues that gave compilation errors were resolved and missing
variables clearly identified and declared appropriately. Also the special bees usage was disabled to change the
focus area of the work presented here.
For this implementation, some of the simulator files need to be modified slightly in other for the algorithm
to be integrated. The modification involves in most cases a line of code defining the algorithm‟s variable and at
most a function section.
For the success of this research, we were able to integrate the BeeAdhoc algorithm in the chosen
simulator with appropriate modification to make it work. All the modifications made to the simulator files were
4. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 52 | Page
written by us and also the library issues mentioned above was debugged by us. A shell script was written to
automate the multiple runs of simulations of different scenarios. I also wrote a java program to parse the trace
files for analysis. The program was made to compute the throughput, end-to-end delay and routing overhead for
the different scenarios in a .csv file which was then used to generate all the graphs. Fig. 2 shows the flow of
event that led to the completion of this project.
Fig. 2: Project Tasks
3.1. Simulation Scenarios
The Beeadhoc algorithm was evaluated in NS-2.34 and results compared with other state-of-the-art routing
algorithms that already exist in the simulator. This section explains briefly the simulation scenarios,
performance metric and results.
The type of traffic that was simulated was Constant Bit Rate (CBR) over User Datagram Protocol (UDP).
The choice of this was made to aid in determining the actual routing packets used instead of using Transmission
Control Protocol (TCP) which could increase the overhead against our wish.
The random waypoint model feature of the simulator was used to generate node and their properties. The
nodes were generated with an initial random position and the mobility throughout the simulation run time was
made random as their respective position switching was randomised.
The simulator has several topology types that could be used; but for this work the simulation topology was
a flat grid that provides a flat surface area, which implies that the surface was free of any object that could
negatively affect the radio transmission power of the nodes. The topology area was made up of a square of 1000
x 1000 m2
for all simulation.
Apart from the scenarios where the number of nodes were varied and mobility speed, all other experiments
have the same number of nodes and uses same mobility speed. The nodes moves randomly to a different
location from the initial point at a fixed speed throughout the experiment and stay there based on the pause time
specified and then moves again.
The wireless radio antenna used was an Omni-antenna (transmitting to all direction) and it was centrally
place on the node with a height of 1.5m and the wireless technology adopted was the WaveLan DSSS which
operates with 915MHz frequency. This decision was also made because WaveLan operates only with one
frequency as stated above which ensures equity in radio transmission frequency of nodes with the same power.
Other parameters as used for the experimental simulations are as shown in Table 1.
It is worthy of note to say that different protocols were examined along with the Beeadhoc algorithm and in
few simulations DSDV and DSR were not used. This was because DSDV and DSR protocols were part of the
oldest available in the simulator and as such it gave segmentation faults during some of the simulations.
The fault was traced to NS-2.34 file named as ns-packet.tcl located in ns-lib and common folders. Further
study showed that the mentioned file has the packets structures of most algorithms defined in it; and modifying
it could affect the performance of other algorithms or even cause compilation error in NS-2.34.
The observed effect of the segmentation faults on the two algorithms (DSDV and DSR) was basically
transmission of lower number of packets than expected in some instances. This effect was seen to have partial
effect on the comparison; thereby all instances where the segmentation fault was observed were deleted from the
data taken for analysis and another instance ran to bring up the samples to the same number with other
algorithms.
3.2. Metrics for Performance Evaluation
Properties of the simulation that was used to evaluate performance of the various algorithms in comparison
to one another were defined to include throughput, end-to-end delay and routing overhead.
BeeAdhoc
Routing
Algorithm
Network
Simulator
NS-2.34
Shell
Script
Trace
File
.tr
Result
.csv
Java
Program
Result
Graphs
Scenarios
and TCL
Scripts
5. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 53 | Page
Throughput: This was defined in percentage as the number of received packets to the number of sent packets in
the application layer. The algorithm that has got the highest percentage value is rated the best performed one for
that particular scenario.
End-to-End Delay: This was defined as the average of the time it takes all sent packets to be received at the
destination. This time is stamped at the moment the packet leaves the sender to include all the delay in the queue
up to when it gets to the destination. Only the times spent by the received packets are considered and the total
sum of the time spent by all received packet is divided by the number of received packets. The algorithm with
the least time is evaluated to be the best performing one for the particular scenario.
Table 1: Simulation Parameters
Parameter Value
Protocols Examined AOMDV, BeeAdHoc, DSDV and DSR
Channel Used Wireless Channel
Network Interface Wireless Physical
MAC Type IEEE 802.11
Queue Type Drop-Tail or Priority Queue
Link Layer Type Used ARP to resolve IP addresses to MAC address
Antenna Type Omni Antenna
Default Wireless Physical Setting 914MHz Lucent WaveLAN DSSS
Queue Length 50 Packets
Number of Nodes 10, 20, 30, 40 and 50
Maximum Area 1000 X 1000 meters
Simulation Time Maximum of 20s
Pause Time 5s
Node Mobility Speed 20, 40, 60, 80, and 100 meters/s
Node Transmitting Range 150, 200, 250, 300 and 350 meters
Packet Size 512 Kb/s
Propagation Type Two Ray Ground
Node Movement Model Random Way Point
Routing Overhead: This was defined as the number of packets generated at the network layer which was tagged
RTR packets in ensuring that the packets get to the destination. This packets include route request, scouts etc.
that are used to find routes. The algorithm with the minimum number of routing overhead is rated the best
performing one again in the particular scenario.
IV. RESULTS ANALYSIS
In the simulated experiments, the traffic type explained above was setup. The source node was made
constant for all experiments and the destination nodes were randomized in multiple runs.
A shell (bash) script was used to aid in automation of multiple runs of each of the simulated scenarios and
generated the required trace files for analysis.
A java program was used to analyse the trace files generated from each runs of the respective scenarios. It
calculated the total number of sent packets, received packets, routing overhead, and the average end-to-end
delay and create a .csv file in which all the values were written from which the graphs were generated.
The points on the graphs are average of multiple runs ranging from 10 – 20 in most cases; this is aimed at
finding out the stochastic behaviour of the algorithm or environment.
4.1 Varying Number of Nodes
In this experiment, the numbers of nodes were varied from between 10 – 50 in different simulations, aimed
at observing the behaviour of the algorithms as the number of nodes increases with reference to the performance
metrics. It was expected that the routing overhead will increase and possibly with increased end-to-end delay as
the number nodes increases but the throughput was envisaged not to be affected by this variation.
From Fig. 3, it was observed that the throughput of Beeadhoc, DSR and AOMDV increases steadily on the
average as the number of nodes increases. DSDV had the worst performance in this regards.
The routing overhead are the control packets used by the algorithms to find routes/paths to the required
destination as based on their working mechanisms. It was expected that the routing overheads would increase as
the number of nodes increases as there would be more nodes to communicate with in the flooding processes.
Fig.4 shows the behaviour of the respective algorithms. All had experienced an increase in the routing
6. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 54 | Page
overheads, but DSR and DSDV had the best performance in this case. Beeadhoc also outperforms AOMDV on
the average.
Fig.3: Number of Nodes Vs Throughput
Fig.4: Number of Nodes Vs Routing Overhead
Fig.5: Number of Nodes Vs End-to-End Delay
Fig. 5 shows the behaviours of the algorithms when the average time it takes packets to be delivered at the
destinations was considered. Beeadhoc competed well with other state-of-the-art algorithms, though the time is
seen to increase as the number of nodes increases as expected at a steady pace. DSDV has an opposite behaviour
as the time reduces as the number of nodes increases, this could be tied down to the fact that it already stored
multiple routes to all nodes at the beginning and can easily switch on which paths to use as soon as there are
packets to be sent out instead of just searching for the routes as others would do.
4.2 Varying Nodes Mobility Speed
Node mobility changes network topology frequently and the aim of this experiment is to observe the
behaviour of the algorithms to changing topology. This is aimed at studying the adaptability of the algorithms.
Ordinarily, it would be expected that the throughput of the algorithms be affected negatively as the mobility
speed increases; this is because the topology changes and more packets would be expected to be dropped.
0
20
40
60
80
100
120
10 20 30 40 50
Throughput(%)
Number of Nodes (N)
AOMDV BEEADHOC DSDV DSR
0
50
100
150
200
250
300
350
10 20 30 40 50
RTROverheads(Packets)
Number of Nodes (N)
AOMDV BEEADHOC DSDV DSR
0
0.02
0.04
0.06
10 20 30 40 50
End-EndDelay(m/s)
Number of Nodes (N)
AOMDV BEEADHOC DSDV DSR
7. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 55 | Page
All the algorithms exhibit different behaviours in this regards, DSDV was seen not to be stable as it goes up
and down as the speed increases. Beeadhoc is the most adaptive algorithm to topology changes as the speed had
little impact on its throughput. Again, all the algorithms converge to between 18% - 25% when the speed was
80m/s and Beeadhoc and AOMDV was seen to have an improved throughput at higher speed beyond this point
as shown on Fig.6. This was repeated for higher speed to be sure of the reaction and the throughput actually
increases. This could be the instance of the simulator or that the algorithms actually adapts quickly to changes.
Routing overhead was expected to increase as the speed increases because known paths are to change as the
nodes moves around randomly with an increased speed and control packets for route discovery are expected to
increase on the overall.
DSDV seem not affected by this as shown in Fig. 7. Beeadhoc experiences an increased routing overhead as
the nodes mobility speeds increases as expected. AOMDV has a reverse behaviour compared to Beeadhoc, this
again could be tied to the fact that AOMDV uses routing table to store multiple paths to a destination and
alternate paths might be found without having to launch new route discovery control packets.
Fig.6: Node Mobility Vs Throughput
Fig.7: Node Mobility Vs Routing Overhead
End-to-End delay graph in Fig. 8 in comparison with the throughput graph in Fig. 7, it could be deduced
that Beeadhoc delayed the packets longer while it searches for new routes to the destination which gave it an
edge over others in better throughput but made it the worst performed in the delay chat.
Fig.8: Node Mobility Vs End-to-End Delay
4.3 Varying Number of Failed Nodes
Network failure was another way the algorithms adaptability features to network changes was verified. In
these experiments, nodes were randomly disabled from participating in any activity in the network after some
time. The number of failed nodes was varied and the results are shown in Fig. 9.
DSDV had the worst throughput over the range of failed nodes while the reaction of DSR, DSDV and
Beeadhoc competitively decreases along the failed node axis as shown in Fig. 9.
0
20
40
60
80
100
20 40 60 80 100
Throughput(%)
Node Mobility Speed (mtr/s)
AOMDV BEEADHOC DSDV DSR
0
50
100
150
200
20 40 60 80 100
RTROverheads
(Packets)
Node Mobility (mtr/s)
AOMDV BEEADHOC DSDV DSR
0
0.5
1
1.5
2
20 40 60 80 100
End-EndDelay(m/s)
Node Mobility (mtr/s)
AOMDV BEEADHOC DSDV DSR
8. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 56 | Page
This was the expected results because the failed nodes might have been actively involved in the routing of
packets before they went down coupled with the nodes mobility which remained constant. This implies the
network topology changing was affected by node failure only in this experiment.
AOMDV was the best performed algorithm in this regards and it maintains a very good throughput before it
eventually decreases when the number of failed nodes increases to 25 and 30 respectively
Fig.9: Network Failure Vs Throughput
4.4. Varying Radio Wireless Transmitting Range
In this experiment the radio transmission range of the nodes was varied, which in turns varies their
respective coverage in the simulated area. The varied transmission range was plotted against throughput and
routing overhead as depicted in Fig. 10 and 11 respectively.
It was expected that the throughput would be poor if the nodes transmission range could not allow them
exchange data as the case with when the transmission range was made 100m as shown in Fig. 10, and that the
effect of the range would not have any significant impact on the throughput once the nodes could communicate
with each other. This was evident from the outcome of Fig. 10; in this, all the algorithms converged at 0%
throughput when the nodes transmission range did not establish a connection between them and a drastic
positive improvement recorded immediately connection was established and this was constant afterwards on the
average for all protocols.
The outcome shown in Fig. 11 was the routing overhead against nodes radio transmission range. As
expected, at smaller coverage area more hops would be required to get to the destination which was randomly
selected and also exhibiting random movement within the simulated area.
This directly implies that more routing control packets would be required at smaller coverage radius which
is expected to reduce as the coverage radius of nodes increases. This assumption was true of Beeadhoc, DSR
displayed a fluctuating behaviour while AOMDV obeyed the assumption partly.
Fig.10: Radio Transmission Range Vs Throughput
0
50
100
150
150 200 250 300 350 400
Throughput(%)
Tx Range (in meters)
AOMDV BEEADHOC DSR
0
20
40
60
80
100
120
10 15 20 25 30
Throughput(%)
Network Failure (N)
AOMDV BEEADHOC DSDV DSR
9. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 57 | Page
Fig.11: Radio Transmission Range Vs Routing Overhead
V. CONCLUSION
In this project, Beeadhoc routing algorithm has been implemented in network simulator NS-2.34 for a
mobile Ad Hoc Network (MANet). Comparisons were made with other state-of-the-art routing algorithms,
varying different features which include radio transmission range, number of nodes, nodes mobility speeds and
number of failed nodes in several of the simulation instances considered.
The metrics used in the evaluation and analysis of the performance of the algorithms were throughput, end-
to-end delay and routing overheads. Optimal data collection from a network using BeeAdhoc Routing
Algorithm was successfully implemented and inferences from the experimental results indicate that: BeeAdhoc
algorithm generated greater throughput than 2 of the 4 existing algorithms (DSDV) when the nodes were
increased, BeeAdhoc algorithm yielded reduced overhead than 2 of the 4 existing algorithms (AOMDV), when
the nodes were increased, BeeAdhoc exhibited an increased End-to-Enddelay as the node number increased,
BeeAdhoc experienced decrease in its throughput as the number of failed nodes increases but still performed
better than DSDV.
Overall, the BeeAdhoc Routing performance was comparable to that of DSR and DSDV in throughput and
overhead but worse in delay. From the results obtained in all simulated experiments, BeeAdhoc could be used
for routing packets in Ad Hoc network whenever interest is on throughput, delay and overheads. This is because
its performance based on those metrics was better and compete reasonably with other algorithms.
REFERENCES
[1] D. H. Wolpert, K. Tumer, An Introduction to Collective Intelligence, Technical Report, NASA ARC-IC-99-63, NASA Ames
Research Centre, 1999.
[2] I. Kroo, Collectives and Complex Systems Design, VKI Lecture Series on Optimisation Methods and Tools for
Multicriteria/Multidisciplinary Design, 2004.
[3] D. H. Wolpert, Collective Intelligence, Computational Intelligence: The Experts Speak, Edited by D.B. Fogel and C. J. Robinson
(IEEE), 2003.
[4] H. A. Mohammed, H. K. Babak, A Distributed Probability Collectives Optimisation Method for Multicast in CDMA Wireless
Data Networks, Proc. 4th
IEEE International Symposium on Wireless Communication Systems, Article No. 4392414, pp. 617 –
621, 2007.
[5] A. J. Kulkarni, K. Tai, Probability Collectives: A Distributed Optimisation Approach for Constrained Problems, IEEE Congress
on Evolutionary Computation (CEC), pp. 1 – 8, 2010.
[6] A. J. Kulkarni, K. Tai, Probability Collectives: A Multi-Agent Approach for Solving Combinatorial Optimisation Problems,
Applications of Soft Computing, vol 10, no. 3, pp. 759 – 771, 2010.
[7] A. J. Kulkarni, K. Tai, Probability Collectives for Decentralised, Distributed Optimisation: A Collective Intelligence Approach,
Proc. IEEE International Conference on Systems, Man, and Cybernetics, pp. 1271 – 1275, 2008.
[8] D. Subramanian, P. Druschel, J. Chen, Ants and Reinforcement Learning: A Case Study in Routing in Dynamic Networks,
International Joint Conference on Artificial Intelligence (IJCAI), 1998.
[9] J. Brownlee, Clever Algorithms – Natured Inspired Programming Recipes, 2011
[10] C. E. Perkins and P. Bhagwat, Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers,
ACM-SIGCOMM, 1994.
[11] H. F. Wedde, M. Farooq, and Y. Zhang, BeeHive: An Efficient Fault-Tolerant Routing Algorithm Inspired by Honey Bee
Behaviour, 2004
[12] H. F. Wedde, M. Farooq, T. Pannenbaecker, B. Vogel, C. Mueller, J. Meth and R. Jeruschkat, BeeAdHoc: An Energy Efficient
Routing Algorithm for Mobile Ad Hoc Networks Inspired by Bee Behaviour, In: GECCO ACM, 2005.
[13] T. White, B. Pagurek, D. Deugo, Collective Intelligence and Priority in Networks, IEA/AIE '02 Proceedings of the 15th
International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems:
Developments in Applied Artificial Intelligence, 2002.
[14] J. Kil-Woong, Meta-Heuristic Algorithms for Channel Scheduling Problem in Wireless Sensor Networks, International Journal
of Communication Systems, John Wiley and Sons, Ltd, 2011.
[15] D. H. Wolpert, K. Tumer, J. Frank, Using Collective Intelligence to Route Internet Traffic, Proceedings of the 1998 Conference
on Advances in Neural Information Processing Systems II, 1999.
[16] P. D. Maio, Digital Ecosystems, Collective Intelligence, Ontology and the 2nd
Law of Thermodynamics, 2nd
IEEE International
Conference on Digital Ecosystems and Technologies (IEEE DEST 2008), pp 144 – 147, 2008.
0
100
200
300
400
150 200 250 300 350 400
RTROverheads(Packets)
Tx Range (in meters)
AOMDV BEEADHOC DSR
10. Optimal Data Collection from a Network using Probability Collectives (Swarm Based)
www.ijres.org 58 | Page
[17] J. A. Boyan, M. L. Littman, Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach,
Advances in Neural Information Processing Systems vol. 6, pp. 671 – 678, 1994.
[18] C. Chiang, H. Wu, W. Liu, M. Gerla, Routing in Clustered Multihop, Mobile Wireless Networks with Fading Channel,1997.
[19] G. S. Ryder, K. G. Ross, “A Probability Collectives Approach to Weighted Clustering Algorithms for Ad Hoc Networks, Proc.
3rd
IASTED International Conference on Communications and Computer Networks, pp. 94 – 99, 2005.
[20] D. S, P. Volf, M. Pechoucek, N. Suri, D. Nicholson, D. Woodhouse, Optimisation-based Collision Avoidance for Cooperating
Airplanes, IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology-Workshops, 2009.