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.
A novel hierarchical ant based qos aware intelligent routing scheme for manetsIJCNCJournal
MANET is a collection of mobile devices with no centralized control and no pre-existing infrastructures.
Due to the nodal mobility, supporting QoS during routing in this type of networks is a very challenging
task. To tackle this type of overhead many routing algorithms with clustering approach have been
proposed. Clustering is an effective method for resource management regarding network performance,
routing protocol design, QoS etc. Most of the flat network architecture contains homogeneous capacity of
nodes but in real time nodes are with heterogeneous capacity and transmission power. Hierarchical
routing provides routing through this kind of heterogeneous nodes. Here, routes can be recorded
hierarchically, across clusters to increase routing flexibility. Besides this, it increases scalability and
robustness of routes. In this paper, a novel ant based QoS aware routing is proposed on a three level
hierarchical cluster based topology in MANET which will be more scalable and efficient compared to flat
architecture and will give better throughput.
Optimized Robot Path Planning Using Parallel Genetic Algorithm Based on Visib...IJERA Editor
An analysis is made for optimized path planning for mobile robot by using parallel genetic algorithm. The
parallel genetic algorithm (PGA) is applied on the visible midpoint approach to find shortest path for mobile
robot. The hybrid ofthese two algorithms provides a better optimized solution for smooth and shortest path for
mobile robot. In this problem, the visible midpoint approach is used to make the effectiveness for avoiding
local minima. It gives the optimum paths which are always consisting on free trajectories. But the
proposedhybrid parallel genetic algorithm converges very fast to obtain the shortest route from source to
destination due to the sharing of population. The total population is partitioned into a number subgroups to
perform the parallel GA. The master thread is the center of information exchange and making selection with
fitness evaluation.The cell to cell crossover makes the algorithm significantly good. The problem converges
quickly with in a less number of iteration.
AN EFFICIENT ANT BASED QOS AWARE INTELLIGENT TEMPORALLY ORDERED ROUTING ALGOR...IJCNCJournal
This document summarizes an ant-based routing algorithm for mobile ad hoc networks that aims to improve network lifetime, reduce packet loss, and decrease average end-to-end delay. It combines aspects of Ant Colony Optimization and the Temporally Ordered Routing Algorithm (TORA). The algorithm is designed to find multiple paths between sources and destinations in the network while satisfying quality of service constraints like delay, bandwidth, energy consumption, and data rate. It is claimed to be suitable for real-time and multimedia applications in 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.
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.
The document summarizes an article from the International Journal on Information Theory that proposes an optimized routing and pin-constrained design approach for digital micro-fluidic biochips. The approach uses a multi-objective particle swarm optimization technique to concurrently route droplets with minimum electrode usage and interference. It then integrates the routing results with a masking-based algorithm to select compatible control sequences and reduce the number of required control pins without interference between electrodes. Experimental results on benchmark problems show significant reductions in control pins, cell usage, and routing time compared to other approaches.
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.
This document provides a survey of ant colony optimization (ACO) approaches for routing and load balancing in computer networks. It begins with an overview of ACO, explaining how artificial ants emulate real ants to solve optimization problems. The document then compares ACO approaches to traditional routing algorithms in terms of routing information, overhead, and adaptivity. A major issue for ACO called stagnation is discussed, where the algorithm becomes stuck on suboptimal solutions. The document surveys approaches to mitigate stagnation, including pheromone evaporation, aging, and privileged pheromone laying. It also reviews three major areas of ACO research for routing/load balancing and discusses new directions and open problems.
A novel hierarchical ant based qos aware intelligent routing scheme for manetsIJCNCJournal
MANET is a collection of mobile devices with no centralized control and no pre-existing infrastructures.
Due to the nodal mobility, supporting QoS during routing in this type of networks is a very challenging
task. To tackle this type of overhead many routing algorithms with clustering approach have been
proposed. Clustering is an effective method for resource management regarding network performance,
routing protocol design, QoS etc. Most of the flat network architecture contains homogeneous capacity of
nodes but in real time nodes are with heterogeneous capacity and transmission power. Hierarchical
routing provides routing through this kind of heterogeneous nodes. Here, routes can be recorded
hierarchically, across clusters to increase routing flexibility. Besides this, it increases scalability and
robustness of routes. In this paper, a novel ant based QoS aware routing is proposed on a three level
hierarchical cluster based topology in MANET which will be more scalable and efficient compared to flat
architecture and will give better throughput.
Optimized Robot Path Planning Using Parallel Genetic Algorithm Based on Visib...IJERA Editor
An analysis is made for optimized path planning for mobile robot by using parallel genetic algorithm. The
parallel genetic algorithm (PGA) is applied on the visible midpoint approach to find shortest path for mobile
robot. The hybrid ofthese two algorithms provides a better optimized solution for smooth and shortest path for
mobile robot. In this problem, the visible midpoint approach is used to make the effectiveness for avoiding
local minima. It gives the optimum paths which are always consisting on free trajectories. But the
proposedhybrid parallel genetic algorithm converges very fast to obtain the shortest route from source to
destination due to the sharing of population. The total population is partitioned into a number subgroups to
perform the parallel GA. The master thread is the center of information exchange and making selection with
fitness evaluation.The cell to cell crossover makes the algorithm significantly good. The problem converges
quickly with in a less number of iteration.
AN EFFICIENT ANT BASED QOS AWARE INTELLIGENT TEMPORALLY ORDERED ROUTING ALGOR...IJCNCJournal
This document summarizes an ant-based routing algorithm for mobile ad hoc networks that aims to improve network lifetime, reduce packet loss, and decrease average end-to-end delay. It combines aspects of Ant Colony Optimization and the Temporally Ordered Routing Algorithm (TORA). The algorithm is designed to find multiple paths between sources and destinations in the network while satisfying quality of service constraints like delay, bandwidth, energy consumption, and data rate. It is claimed to be suitable for real-time and multimedia applications in 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.
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.
The document summarizes an article from the International Journal on Information Theory that proposes an optimized routing and pin-constrained design approach for digital micro-fluidic biochips. The approach uses a multi-objective particle swarm optimization technique to concurrently route droplets with minimum electrode usage and interference. It then integrates the routing results with a masking-based algorithm to select compatible control sequences and reduce the number of required control pins without interference between electrodes. Experimental results on benchmark problems show significant reductions in control pins, cell usage, and routing time compared to other approaches.
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.
This document provides a survey of ant colony optimization (ACO) approaches for routing and load balancing in computer networks. It begins with an overview of ACO, explaining how artificial ants emulate real ants to solve optimization problems. The document then compares ACO approaches to traditional routing algorithms in terms of routing information, overhead, and adaptivity. A major issue for ACO called stagnation is discussed, where the algorithm becomes stuck on suboptimal solutions. The document surveys approaches to mitigate stagnation, including pheromone evaporation, aging, and privileged pheromone laying. It also reviews three major areas of ACO research for routing/load balancing and discusses new directions and open problems.
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
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed
Hybrid approaches in Network Optical Routing with QoS based on Genetic Algori...IDES Editor
Hybrid heuristics have been proposed by many
researches as a method to overcome problems in pure heuristic
implementation for multi-constrained QoS routing problems.
In this paper we present some hybrid approaches based on
Genetic Algorithms and Particle Swarm Optimization as well
as their performance to solve NP-complete routing problem. .
Solving QoS multicast routing problem using ACO algorithmAbdullaziz Tagawy
The document discusses using an ant colony optimization (ACO) algorithm to solve the quality of service (QoS) constrained multicast routing problem. The ACO algorithm is inspired by how real ants find the shortest path to food sources. In the algorithm, artificial ants probabilistically construct multicast trees and update pheromone values on the paths/edges to gradually converge on high quality solutions. The document provides details of the ACO algorithm and gives an example of applying it to find the shortest path between a source and destination node to demonstrate how it works.
This document summarizes a research paper that proposes using a cuckoo search algorithm to optimize routing in mobile ad hoc networks (MANETs). Specifically:
1) It enhances an existing Loyalty Pair Neighbors selection (LPNS) routing protocol using cuckoo search optimization to select stable neighbor nodes.
2) Cuckoo search is applied to select neighbor nodes based on hop count, energy level, and queue length to find optimal routes.
3) The proposed Enhanced LPNS with Cuckoo Search (ELPNS_Cuckoo) protocol is evaluated in simulations and shown to improve performance metrics like packet delivery ratio, throughput, and delay compared to the original LPNS protocol.
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.
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
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
Abstract In optical circuit switching the high values of blocking probability is resolved by dynamic wavelength routing algorithms with wavelength conversion. The aim of this paper is to study these algorithms. Then the algorithm is selected which gives good results with and without wavelength conversion. The selected algorithm is then checked for other parameters of networking namely throughput, packet delivery ratio, and delay. A comparative study is then carried out for increasing traffic. We try to prove that these algorithms satisfy the criteria of QoS parameters by this comparative study. The results of simulation show that the parameters follow the trend of blocking probability of the selected algorithm. Keywords: optical burst switching, throughput, packet delivery ratio, delay.
Review and Comparisons between Multiple Ant Based Routing Algorithms in Mobi...IJMER
Along with an increase in the use and development of various types of mobile ad hoc and
wireless sensor networks the necessity for presenting optimum routing in these networks is a topic yet to
be discussed and new algorithms are presented. Using ant colony optimization algorithm or ACO as a
routing method because of its structural similarities to these networks’ model, has had acceptable results
regarding different parameters especially quality of service (QoS). Considering the fact that many
articles have suggested and presented various models for ant based routing, the need for studying and comparing them can be felt. There are about 17 applied ant based routings, this article studies and compares the most important ant based algorithms so as to indicate the quality and importance of each of them under different conditions
Cluster head election using imperialist competitive algorithm (chei) for wire...ijmnct
One of the most important challenges of wireless sensor network is how to prolong its life time. The main
obstacle in these networks is the limited energy of nodes. We can overcome this problem by optimizing the
nodes' power consumption. The clustering mechanismis the one of the representative approachesto reduce
energy consumption, but optimum clustering of wireless sensor network is an NP-Hard problem. This
paper proposes a hybrid algorithm based on Imperialist competitive algorithm to overcome this clustering
problem. The proposed method, acts on one of the clusters in the network to choose the best sensor in
the cluster as a cluster head. To perform this action, the cluster is divided into several sub-clusters,
each of which has a cluster head. These cluster heads using Assimilation
policies, try to attract the regular nodes to themselves, and Using Imperialistic competition,
they compete with each other until one of these cluster heads is selected as the final cluster head. After this
stage, the algorithm work ends. This algorithm will balance the energy consumption in the network and
improve the network lifetime. To prove efficiency of proposed algorithm(CHEI), we simulated the proposed
algorithm compared with two clustering algorithms using the matlab
This document discusses using a learning automata approach to predict target locations in wireless sensor networks to reduce energy consumption and improve tracking accuracy. It proposes a learning automata based method that uses a target's movement history to predict its next location. Related works on target tracking techniques like tree-based, cluster-based, and prediction-based methods are summarized. Learning automata concepts are introduced. Simulation results are said to show the proposed method improves energy efficiency, reduces missed targets, and decreases transmitted packets compared to other methods.
Iaetsd modified artificial potential fields algorithm for mobile robot path ...Iaetsd Iaetsd
This document presents a modified artificial potential fields algorithm for mobile robot path planning in unknown and dynamic environments. The algorithm uses artificial potential fields to iteratively find optimal points to form a collision-free path from the start to destination. For static obstacles, potential values are used to identify clusters of points around the start and goal, and find a connecting midpoint. This process is repeated iteratively. For dynamic obstacles, Markov models are used to analyze obstacle behavior from sensor data and predict collision points. The robot's path is replanned as needed to avoid collisions based on feedback from sensors and odometry. Simulation results show the algorithm can efficiently plan paths in unknown environments and avoid both static and dynamic obstacles.
Mobile elements scheduling for periodic sensor applicationsijwmn
In this paper, we investigate the problem of designing the mobile elements tours such that the length of each tour is below a per-determined length and the depth of the multi-hop routing trees bounded by k. The path of the mobile element is designed to visit subset of the nodes (cache points). These cache points store other nodes data. To address this problem, we propose two heuristic-based solutions. Our solutions take into consideration the distribution of the nodes during the establishment of the tour. The results of our experiments indicate that our schemes significantly outperforms the best comparable scheme in the literature.
Path constrained data gathering scheme for wireless sensor networks with mobi...ijwmn
This document summarizes a research paper on using mobile elements to gather data in wireless sensor networks. The paper proposes a heuristic algorithm called Graph Partitioning (GP) to address the K-Hop tour planning (KH-tour) problem of designing the shortest possible tour for a mobile element to visit a subset of sensor nodes called caching points, such that any node is at most k hops from the tour.
The GP algorithm works by first partitioning the sensor network graph into partitions where the depth of each partition is bounded by k hops. It then identifies the minimum number of caching points needed in each partition. Finally, it constructs the mobile element's tour to visit all the identified caching points.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
The document summarizes three algorithms for multi-robot path planning: Bacteria Foraging Optimization (BFO), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). BFO is inspired by how bacteria like E. coli search for food by swimming and tumbling. ACO is based on how ants deposit and follow pheromone trails to find food sources. PSO mimics the movement of bird flocking and fish schooling. The document provides details on the mechanisms and equations used in each algorithm's approach to finding optimal paths for multiple robots.
AN INITIAL PEER CONFIGURATION ALGORITHM FOR MULTI-STREAMING PEER-TO-PEER NETW...ijp2p
The growth of the Internet technology enables us to use network applications for streaming audio and
video.Especially, real-time streaming services using peer-to-peer (P2P) technology are currently
emerging.An important issue on P2P streaming is how to construct a logical network (overlay network) on
a physical network (IP network). In this paper, we propose an initial peer configuration algorithm for a
multi-streaming peer-to-peer network. The proposed algorithm is based on a mesh-pull approach where
any node has multiple parent and child nodes as neighboring nodes, and content transmitted between these
neighboring nodes depends on their parent-child relationships. Our simulation experiments show that the
proposed algorithm improves the number of joining node and traffic load.
Techniques for Optimal Maintenance SchedulingIOSR Journals
This document presents techniques for optimizing maintenance scheduling to minimize total maintenance costs. It describes developing a mathematical model to determine optimal preventive maintenance periods and number of maintenance workers. The model minimizes total costs, which include downtime, wages, and maintenance setup costs, subject to equipment availability constraints. An example application to mine power equipment is provided to illustrate the optimization technique. The results show optimal preventive maintenance intervals for different equipment groups and that a workforce of 7 workers achieves the minimum total annual maintenance cost rate of $625.70.
Efficient Fpe Algorithm For Encrypting Credit Card NumbersIOSR Journals
This document proposes an efficient format-preserving encryption (FPE) algorithm for encrypting credit card numbers. The algorithm uses AES-128 encryption and adds two additional steps to retain the plaintext format of 16 decimal digits. Specifically, it divides the 128-bit ciphertext into blocks, performs an XOR operation between blocks, and then converts the resulting hexadecimal values to decimal digits. This allows encryption without changing the database structure or queries. The proposed algorithm is faster and requires no additional storage compared to existing FPE techniques like prefix encryption, cycle walking, or Feistel networks. It provides an efficient way to encrypt sensitive numeric fields like credit cards while preserving functionality.
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
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed
Hybrid approaches in Network Optical Routing with QoS based on Genetic Algori...IDES Editor
Hybrid heuristics have been proposed by many
researches as a method to overcome problems in pure heuristic
implementation for multi-constrained QoS routing problems.
In this paper we present some hybrid approaches based on
Genetic Algorithms and Particle Swarm Optimization as well
as their performance to solve NP-complete routing problem. .
Solving QoS multicast routing problem using ACO algorithmAbdullaziz Tagawy
The document discusses using an ant colony optimization (ACO) algorithm to solve the quality of service (QoS) constrained multicast routing problem. The ACO algorithm is inspired by how real ants find the shortest path to food sources. In the algorithm, artificial ants probabilistically construct multicast trees and update pheromone values on the paths/edges to gradually converge on high quality solutions. The document provides details of the ACO algorithm and gives an example of applying it to find the shortest path between a source and destination node to demonstrate how it works.
This document summarizes a research paper that proposes using a cuckoo search algorithm to optimize routing in mobile ad hoc networks (MANETs). Specifically:
1) It enhances an existing Loyalty Pair Neighbors selection (LPNS) routing protocol using cuckoo search optimization to select stable neighbor nodes.
2) Cuckoo search is applied to select neighbor nodes based on hop count, energy level, and queue length to find optimal routes.
3) The proposed Enhanced LPNS with Cuckoo Search (ELPNS_Cuckoo) protocol is evaluated in simulations and shown to improve performance metrics like packet delivery ratio, throughput, and delay compared to the original LPNS protocol.
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.
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
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
Abstract In optical circuit switching the high values of blocking probability is resolved by dynamic wavelength routing algorithms with wavelength conversion. The aim of this paper is to study these algorithms. Then the algorithm is selected which gives good results with and without wavelength conversion. The selected algorithm is then checked for other parameters of networking namely throughput, packet delivery ratio, and delay. A comparative study is then carried out for increasing traffic. We try to prove that these algorithms satisfy the criteria of QoS parameters by this comparative study. The results of simulation show that the parameters follow the trend of blocking probability of the selected algorithm. Keywords: optical burst switching, throughput, packet delivery ratio, delay.
Review and Comparisons between Multiple Ant Based Routing Algorithms in Mobi...IJMER
Along with an increase in the use and development of various types of mobile ad hoc and
wireless sensor networks the necessity for presenting optimum routing in these networks is a topic yet to
be discussed and new algorithms are presented. Using ant colony optimization algorithm or ACO as a
routing method because of its structural similarities to these networks’ model, has had acceptable results
regarding different parameters especially quality of service (QoS). Considering the fact that many
articles have suggested and presented various models for ant based routing, the need for studying and comparing them can be felt. There are about 17 applied ant based routings, this article studies and compares the most important ant based algorithms so as to indicate the quality and importance of each of them under different conditions
Cluster head election using imperialist competitive algorithm (chei) for wire...ijmnct
One of the most important challenges of wireless sensor network is how to prolong its life time. The main
obstacle in these networks is the limited energy of nodes. We can overcome this problem by optimizing the
nodes' power consumption. The clustering mechanismis the one of the representative approachesto reduce
energy consumption, but optimum clustering of wireless sensor network is an NP-Hard problem. This
paper proposes a hybrid algorithm based on Imperialist competitive algorithm to overcome this clustering
problem. The proposed method, acts on one of the clusters in the network to choose the best sensor in
the cluster as a cluster head. To perform this action, the cluster is divided into several sub-clusters,
each of which has a cluster head. These cluster heads using Assimilation
policies, try to attract the regular nodes to themselves, and Using Imperialistic competition,
they compete with each other until one of these cluster heads is selected as the final cluster head. After this
stage, the algorithm work ends. This algorithm will balance the energy consumption in the network and
improve the network lifetime. To prove efficiency of proposed algorithm(CHEI), we simulated the proposed
algorithm compared with two clustering algorithms using the matlab
This document discusses using a learning automata approach to predict target locations in wireless sensor networks to reduce energy consumption and improve tracking accuracy. It proposes a learning automata based method that uses a target's movement history to predict its next location. Related works on target tracking techniques like tree-based, cluster-based, and prediction-based methods are summarized. Learning automata concepts are introduced. Simulation results are said to show the proposed method improves energy efficiency, reduces missed targets, and decreases transmitted packets compared to other methods.
Iaetsd modified artificial potential fields algorithm for mobile robot path ...Iaetsd Iaetsd
This document presents a modified artificial potential fields algorithm for mobile robot path planning in unknown and dynamic environments. The algorithm uses artificial potential fields to iteratively find optimal points to form a collision-free path from the start to destination. For static obstacles, potential values are used to identify clusters of points around the start and goal, and find a connecting midpoint. This process is repeated iteratively. For dynamic obstacles, Markov models are used to analyze obstacle behavior from sensor data and predict collision points. The robot's path is replanned as needed to avoid collisions based on feedback from sensors and odometry. Simulation results show the algorithm can efficiently plan paths in unknown environments and avoid both static and dynamic obstacles.
Mobile elements scheduling for periodic sensor applicationsijwmn
In this paper, we investigate the problem of designing the mobile elements tours such that the length of each tour is below a per-determined length and the depth of the multi-hop routing trees bounded by k. The path of the mobile element is designed to visit subset of the nodes (cache points). These cache points store other nodes data. To address this problem, we propose two heuristic-based solutions. Our solutions take into consideration the distribution of the nodes during the establishment of the tour. The results of our experiments indicate that our schemes significantly outperforms the best comparable scheme in the literature.
Path constrained data gathering scheme for wireless sensor networks with mobi...ijwmn
This document summarizes a research paper on using mobile elements to gather data in wireless sensor networks. The paper proposes a heuristic algorithm called Graph Partitioning (GP) to address the K-Hop tour planning (KH-tour) problem of designing the shortest possible tour for a mobile element to visit a subset of sensor nodes called caching points, such that any node is at most k hops from the tour.
The GP algorithm works by first partitioning the sensor network graph into partitions where the depth of each partition is bounded by k hops. It then identifies the minimum number of caching points needed in each partition. Finally, it constructs the mobile element's tour to visit all the identified caching points.
Routing in Wireless Mesh Networks: Two Soft Computing Based Approachesijmnct
Due to dynamic network conditions, routing is the most critical part in WMNs and needs to be optimised.
The routing strategies developed for WMNs must be efficient to make it an operationally self configurable
network. Thus we need to resort to near shortest path evaluation. This lays down the requirement of some
soft computing approaches such that a near shortest path is available in an affordable computing time. This
paper proposes a Fuzzy Logic based integrated cost measure in terms of delay, throughput and jitter.
Based upon this distance (cost) between two adjacent nodes we evaluate minimal shortest path that updates
routing tables. We apply two recent soft computing approaches namely Big Bang Big Crunch (BB-BC) and
Biogeography Based Optimization (BBO) approaches to enumerate shortest or near short paths. BB-BC
theory is related with the evolution of the universe whereas BBO is inspired by dynamical equilibrium in
the number of species on an island. Both the algorithms have low computational time and high convergence
speed. Simulation results show that the proposed routing algorithms find the optimal shortest path taking
into account three most important parameters of network dynamics. It has been further observed that for
the shortest path problem BB-BC outperforms BBO in terms of speed and percent error between the
evaluated minimal path and the actual shortest path.
The document summarizes three algorithms for multi-robot path planning: Bacteria Foraging Optimization (BFO), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). BFO is inspired by how bacteria like E. coli search for food by swimming and tumbling. ACO is based on how ants deposit and follow pheromone trails to find food sources. PSO mimics the movement of bird flocking and fish schooling. The document provides details on the mechanisms and equations used in each algorithm's approach to finding optimal paths for multiple robots.
AN INITIAL PEER CONFIGURATION ALGORITHM FOR MULTI-STREAMING PEER-TO-PEER NETW...ijp2p
The growth of the Internet technology enables us to use network applications for streaming audio and
video.Especially, real-time streaming services using peer-to-peer (P2P) technology are currently
emerging.An important issue on P2P streaming is how to construct a logical network (overlay network) on
a physical network (IP network). In this paper, we propose an initial peer configuration algorithm for a
multi-streaming peer-to-peer network. The proposed algorithm is based on a mesh-pull approach where
any node has multiple parent and child nodes as neighboring nodes, and content transmitted between these
neighboring nodes depends on their parent-child relationships. Our simulation experiments show that the
proposed algorithm improves the number of joining node and traffic load.
Techniques for Optimal Maintenance SchedulingIOSR Journals
This document presents techniques for optimizing maintenance scheduling to minimize total maintenance costs. It describes developing a mathematical model to determine optimal preventive maintenance periods and number of maintenance workers. The model minimizes total costs, which include downtime, wages, and maintenance setup costs, subject to equipment availability constraints. An example application to mine power equipment is provided to illustrate the optimization technique. The results show optimal preventive maintenance intervals for different equipment groups and that a workforce of 7 workers achieves the minimum total annual maintenance cost rate of $625.70.
Efficient Fpe Algorithm For Encrypting Credit Card NumbersIOSR Journals
This document proposes an efficient format-preserving encryption (FPE) algorithm for encrypting credit card numbers. The algorithm uses AES-128 encryption and adds two additional steps to retain the plaintext format of 16 decimal digits. Specifically, it divides the 128-bit ciphertext into blocks, performs an XOR operation between blocks, and then converts the resulting hexadecimal values to decimal digits. This allows encryption without changing the database structure or queries. The proposed algorithm is faster and requires no additional storage compared to existing FPE techniques like prefix encryption, cycle walking, or Feistel networks. It provides an efficient way to encrypt sensitive numeric fields like credit cards while preserving functionality.
A Solution to Optimal Power Flow Problem using Artificial Bee Colony Algorith...IOSR Journals
This document presents an artificial bee colony (ABC) algorithm approach to solve the optimal power flow (OPF) problem incorporating a flexible AC transmission system (FACTS) device, specifically a static synchronous series compensator (SSSC). The ABC algorithm is tested on the IEEE 14-bus test system both with and without the SSSC. Results show that the ABC algorithm gives a better solution when incorporating the SSSC, improving the system performance in terms of lower total cost, lower power losses, and better voltage profile compared to the case without SSSC.
1) The study investigated the emulsifying power of violet plant root (VPR) at different concentrations (1-6 g/100 ml) compared to two synthetic detergents (Samples A and B).
2) VPR showed better emulsion stability over time and across all concentrations tested compared to the synthetic detergents. The emulsion capacity of VPR ranged from 98.4-70% at 1 g/100 ml concentration, decreasing more gradually over time.
3) VPR is concluded to be a good natural emulsifier, promoting emulsion formation at both low and high concentrations and exhibiting better stability than the synthetic detergents tested. Its saponin content contributes to its emulsifying properties.
This document summarizes research on the dimerization of pumpkin seed oil using sulfur as a catalyst. Key findings include:
- Pumpkin seed oil's properties make it a potential source for oleochemicals. Dimerization yields increased with temperature up to 340°C, with a maximum dimer yield of 42.53% obtained at that temperature and 35 minutes.
- Molecular weight and acid values of dimerized samples increased with reaction time and temperature, indicating more polymerization. Optimum conditions were 340°C for 35 minutes.
- Preparative thin layer chromatography also found the highest dimer yield (42.53%) at 340°C and 35 minutes, suggesting this is the optimum temperature for pumpkin seed oil
A New Single-Stage Multilevel Type Full-Bridge Converter Applied to closed lo...IOSR Journals
This document describes a new single-stage multilevel full-bridge converter applied to a closed loop condition with a brushless DC motor load. The converter uses auxiliary windings on the transformer to cancel the DC bus voltage during certain operating modes, allowing the input currents to rise and minimizing harmonics. It operates by switching between four modes to transfer energy from the DC link to the output load and inductors. Simulation results showed the converter can achieve high power factor and continuous output current from maximum to half load.
IOSR Journal of Applied Chemistry (IOSR-JAC) is an open access international journal that provides rapid publication (within a month) of articles in all areas of applied chemistry and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Chemical Science. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
The Delivery of Web Mining in Healthcare System on Cloud ComputingIOSR Journals
This document discusses delivering web mining services in healthcare systems using cloud computing. It proposes a model where a cloud-based web server would provide various healthcare-related data and services that could be accessed anywhere, anytime through internet-connected devices. Key benefits identified include unlimited storage, lower costs, automatic software integration, backup/recovery, and increased scalability and speed compared to traditional systems. The proposed approach involves extracting data from websites, cleaning and integrating it into a database, then allowing users to access the information remotely through the cloud server. This could help with tasks like comparing product prices from different suppliers to purchase items more cost effectively.
An Optimal Approach to derive Disjunctive Positive and Negative Rules from As...IOSR Journals
This document discusses an optimal approach to derive disjunctive positive and negative association rules from association rule mining using a genetic algorithm. It aims to address some shortfalls of conventional algorithms like Apriori by supporting disjunctive rules, using multiple minimum support thresholds, and effectively identifying negative rules. The proposed approach uses a modified FP-Growth algorithm and genetic algorithm to generate conjunctive and disjunctive positive and negative rules in an optimized manner by reducing candidate generation time and capturing useful rare item relationships.
This document describes a column decoder design for memory that aims to minimize power and area. It summarizes the key components of a memory architecture including a 6-transistor memory cell, precharge circuit, sense amplifier, row decoder, column decoder, and control logic. The column decoder is implemented using pass transistor logic to reduce the number of transistors and area. Simulation results show the output waveforms of the column decoder, bidirectional multiplexer, sense amplifier, and control signals, verifying the read and write cycles. The design aims to reduce memory area by using a more efficient multiplexer and reducing the required number of sense amplifiers.
This document discusses effective cryptography standards for conducting business and personal communications over the Internet. It begins by noting that while organizations are working to secure themselves from growing cyber threats, data breaches continue to occur frequently. The document then reviews the problem and proposes several possible solutions. It discusses different cryptography techniques from the past like private key algorithms, public key algorithms, and hash functions. It also covers more modern techniques like quantum cryptography and elliptic curve cryptography. The document concludes that with continued development of proven cryptography technologies, we may be able to better protect secrecy in digital communications.
Improved Fuzzy Control Strategy for Power Quality in Distributed Generation’s...IOSR Journals
This document describes an improved fuzzy control strategy for a single-phase inverter used in distributed power generation systems to improve power quality. The control strategy allows the inverter to generate active power from a renewable energy source while also compensating for reactive power and current harmonics from local nonlinear loads. The control scheme uses a reference current generator based on sinusoidal signal integrators and instantaneous reactive power theory. It also employs a dedicated repetitive current controller with a fuzzy controller. Simulation results demonstrate the feasibility of the proposed solution for active power generation, reactive power compensation, and harmonic compensation when connected to the grid.
A Greybox Hospital Information System in the Medical Center Tobruk Libya base...IOSR Journals
This document presents a study on developing a greybox hospital information system for the Medical Center in Tobruk, Libya based on the Three-layer Graph-based Model (3LGM). The study aims to model the current information system and propose improvements using 3LGM. It describes modeling the main functions, logical and physical layers, use cases, and databases for patient, doctor, and clinical documentation data. Tables compare 3LGM to other models. Figures illustrate the domain layers, tools layers, use cases, and database tables. The conclusion is that all tasks were successfully completed to develop and implement an information system model to support management of patient, doctor, and clinical data using 3LGM.
This document discusses wireless energy transfer through high frequency signals. It begins by providing background on wireless energy transfer and the traditional use of electromagnetic induction, which is less efficient and can negatively impact human health. It then proposes using high frequency signals to wirelessly charge electronic devices, where the signals would be transmitted using a transmitter circuit including an oscillator and loudspeaker transducer, and received using a receiver circuit including a microphone transducer, rectifier, and amplifier. The document discusses the components that would be used, including crystal oscillators to produce the high frequencies, and transducers to convert the signals to and from electrical and sound waves. The goal is to enable efficient and safe wireless charging of devices over short ranges.
Correlation Preserving Indexing Based Text ClusteringIOSR Journals
This document discusses a correlation preserving indexing (CPI) based text clustering method. CPI aims to find a low dimensional semantic subspace that maximizes correlation between similar documents while minimizing correlation between dissimilar documents. It is different from other methods like LSI and LPI that use Euclidean distance. The document outlines the CPI method and evaluates it on document clustering tasks, showing it doubles the accuracy of previous correlation-based methods. Hierarchical clustering algorithms are also discussed and compared to CPI in terms of evaluation metrics.
Bt cotton was introduced in India in 2002 and widely adopted by farmers, reaching 92% of cotton area by 2013. This led to significant impacts. Yields increased 24-28% due to bollworm resistance. Pesticide use decreased 43-50% for bollworms but increased for other pests. Production increased, lowering cotton prices 3%. However, input costs increased, reducing farmer profits. The document reviews research on Bt cotton impacts in various regions and cropping systems in India and calls for further research and development efforts to improve yields, reduce costs, and meet consumer demands.
The document summarizes a study on the effects of sowing date and crop spacing on growth, yield attributes, and quality of sesame. The study found that sowing early in the second fortnight of February and using a rectangular spacing of 45 x 15 cm resulted in superior performance of the sesame variety KS 95010. This combination led to taller plants, higher leaf area index, more branches, capsules, and seeds per plant. It also resulted in higher test weight, seed yield of 908 kg/ha, net income of 19,801 rupees, and a benefit-cost ratio of 3.09. The optimal plant density and spacing of 45 x 15 cm allowed for better resource utilization and maxim
Achieving Privacy in Publishing Search logsIOSR Journals
The document discusses algorithms for publishing search logs while preserving user privacy. It analyzes a search log using an algorithm that produces three types of outputs: query counts, a query-action graph showing query-result click counts, and a query-reformulation graph showing query suggestions clicked. The algorithm adds noise to query counts before publishing to achieve differential privacy. It aims to provide useful aggregated information for applications like search improvement while preventing re-identification of individual user data in the search log.
Using Multi-layered Feed-forward Neural Network (MLFNN) Architecture as Bidir...IOSR Journals
This document presents a method for using a multi-layered feed-forward neural network (MLFNN) architecture as a bidirectional associative memory (BAM) for function approximation. It proposes applying the backpropagation algorithm in two phases - first in the forward direction, then in the backward direction - which allows the MLFNN to work like a BAM. Simulation results show that this two-phase backpropagation algorithm achieves convergence faster than standard backpropagation when approximating the sine function, demonstrating that the MLFNN architecture is better suited for function approximation when trained this way.
Multicast Dual Arti-Q System in Vehicular Adhoc NetworksIOSR Journals
This document discusses a dual Arti-Q system for efficient call taxi management in vehicular ad hoc networks (VANETs). The existing Artigence system uses an Arti-Q algorithm with two components: Arti-Q main and Arti-Q proxy. The dual Arti-Q system proposes distributing the functionalities of scheduling and message transmission between separate servers to process requests in parallel and reduce response times. By separating these functions, the dual Arti-Q system aims to improve efficiency over the existing Artigence approach for managing taxi reservations and communications in VANETs.
Optimal Data Collection from a Network using Probability Collectives (Swarm B...IJRES Journal
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 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.
i. The document describes an ant colony optimization (ACO) based routing algorithm for mobile ad hoc networks (MANETs). ACO algorithms are inspired by how real ants find the shortest path between their colony and food sources.
ii. In the algorithm, artificial "ants" are generated at nodes and collect information about path lengths and quality as they travel between nodes. They deposit and follow "pheromone trails" to probabilistically route along better paths. This allows the protocol to discover paths and adapt to dynamic topologies.
iii. The algorithm is analyzed in simulation. Results show it constructs probabilistic routing tables where better paths have higher pheromone values and are preferred. It can find next
This document proposes a modified ant colony optimization (ACO) routing protocol for mobile ad hoc networks (MANETs). The key points are:
1) The protocol is based on swarm intelligence principles and uses mobile software agents like ants to intelligently route packets from node to node.
2) It modifies the standard ACO algorithm to make it power-balanced and achieve faster packet delivery rates by making the pheromone decay dependent on nodes' battery levels.
3) The routing process involves forward and backward ants establishing and maintaining routes between source and destination via probabilistic path selection based on accumulated pheromone levels.
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.
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
AntNet is an ant colony optimization (ACO) based routing algorithm that uses two types of mobile agents called forward ants and backward ants. Forward ants explore the network concurrently and examine traffic patterns along paths to exchange information with backward ants. Backward ants then use this information to update routing tables, directing data packets towards their destinations in a traffic-adaptive and multipath manner. The algorithm maintains pheromone values, routing tables, link queue observations, and statistical models at each node to probabilistically route packets based on collected network information.
This document summarizes three algorithms for multi-robot path planning: Bacteria Foraging Optimization (BFO), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). BFO mimics the movement of bacteria in search of food to find optimal paths. ACO is inspired by how ants find food paths using pheromone trails; the algorithm uses heuristic information and state transition rules. PSO is based on the social behaviors of bird flocking and fish schooling; it represents solutions as particles that fly through the problem space following certain rules.
This document summarizes three algorithms for multi-robot path planning: Bacteria Foraging Optimization (BFO), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). BFO mimics the movement of bacteria in searching for nutrients to find optimal paths. ACO is inspired by how ants find food by leaving and following pheromone trails. PSO is based on the social behavior of bird flocking and fish schooling, with robots updating their movements based on their own experiences and those of nearby robots. The document reviews the mechanisms and applications of each algorithm for solving multi-robot path planning problems.
Comparative Study of Ant Colony Optimization And Gang SchedulingIJTET Journal
Abstract— Ant Colony Optimization (ACO) is a well known and rapidly evolving meta-heuristic technique. All optimization problems have already taken advantage of the ACO technique while countless others are on their way. Ant Colony Optimization (ACO) has been used as an effective algorithm in solving the scheduling problem in grid computing. Whereas gang scheduling is a scheduling algorithm that is used to schedule the parallel systems and schedules related threads or processes to run simultaneously on different processors. The threads that are scheduled are belonging to the same process, but they from different processes in some cases, for example when the processes have a producer-consumer relationship, when all processes come from the same MPI program.
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 presents a path planning algorithm called Ant Colony Robot Path Planning (ARPP) that is based on Ant Colony Optimization (ACO) techniques. The ARPP algorithm uses artificial ants to find optimal paths for a warehouse material handling robot to navigate between locations, avoiding obstacles. The algorithm models the environment as a visibility graph and applies ACO concepts like pheromone deposition and evaporation to guide the ants toward shorter paths. Simulation results on a sample visibility graph show that after 100 iterations, the ARPP approach consistently finds the shortest path of 33 units in length. The algorithm provides an effective method for mobile robot path planning in complex warehouse environments.
Routing of traffic sensors in intelligent transportation systemeSAT Journals
Abstract As country develops, the application of technology in each and every field increases to fulfill the demand of people. The application of technology in transportation system is called Intelligent Transportation System (ITS) which has more demand in today’s world for traffic management. Vehicular Ad hoc Network (VANET) is one of the technology used in Intelligent Transportation System. In Vehicular Ad hoc Network temporary network is formed within the vehicles or vehicle to traffic infrastructure which has sensors within it for communication. The temporary network establishes and ends after exchanging the required information. This process should happen within fraction of seconds which is more complicated issue in highly mobile vehicles, so routing is a major problem in Vehicular Ad hoc Network. In this work, hybrid two stage heuristic routing protocol which is based on ant colony optimization and particle swarm optimization algorithm is used to make routing more efficient in Vehicular Ad hoc Network. The MATLAB software is used to implement the algorithm. The result shows that two stage heuristic protocol perform better than Ad hoc on Demand Vector (AODV) protocol. Keywords: Intelligent Transportation System, Vehicular Ad Hoc Network (VANET), Ad Hoc on Demand Vector (AODV), Ant Colony optimization (ACO), Particle Swarm Optimization (PSO)
This document summarizes an innovative routing algorithm called AntHocNet for mobile ad hoc networks. AntHocNet combines aspects of ant colony optimization and information bootstrapping to address the challenges of routing in dynamic mobile networks. Key elements of AntHocNet include the use of both reactive and proactive routing components, combining ant-based path sampling with a lightweight bootstrapping process to update routing information, and using a composite pheromone metric to guide path selection. The document evaluates the performance impacts of these different design components through simulation studies.
A Randomized Load Balancing Algorithm In Grid using Max Min PSO Algorithm IJORCS
Grid computing is a new paradigm for next generation computing, it enables the sharing and selection of geographically distributed heterogeneous resources for solving large scale problems in science and engineering. Grid computing does require special software that is unique to the computing project for which the grid is being used. In this paper the proposed algorithm namely dynamic load balancing algorithm is created for job scheduling in Grid computing. Particle Swarm Intelligence (PSO) is the latest evolutionary optimization techniques in Swarm Intelligence. It has the better performance of global searching and has been successfully applied to many areas. The performance measure used for scheduling is done by Quality of service (QoS) such as makespan, cost and deadline. Max PSO and Min PSO algorithm has been partially integrated with PSO and finally load on the resources has been balanced.
A Survey of Solving Travelling Salesman Problem using Ant Colony OptimizationIRJET Journal
This document summarizes research on solving the travelling salesman problem (TSP) using ant colony optimization (ACO). It first provides background on TSP and describes how ACO mimics real ants finding food to solve optimization problems. The document then reviews several papers that have applied ACO to TSP and compared it to other algorithms. It finds that ACO generally performs better than genetic algorithms at finding optimal solutions to TSP as the number of cities increases. Finally, it proposes studying the effects of different ACO parameters on finding optimal TSP solutions.
The document summarizes research on using ant colony optimization (ACO) supervised by particle swarm intelligence (PSI) to solve multi-objective vehicle routing problems. It proposes applying this approach to determine optimal routes on a linearly expanded network model. The ACO algorithm finds shortest paths between nodes while avoiding local optima, guided by PSI. Experimental results show the ACOLS-PSI algorithm improves average route distance by 8% compared to existing greedy algorithms. Future work could combine this approach with other shortest path methods into a memetic algorithm to better solve wide and sparse vehicle routing networks.
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
Performance Analysis of Minimum Hop Source Routing Algorithm for Two Dimensio...IOSR Journals
Abstract: Network on Chip has emerged as new paradigm for the system designers to design an on chip interconnection network. However, NOC presents a large amount of array of design parameters and decision that are sometimes difficult to tackle. Apart from these issues NOC presents a framework of communication for complex SOC and has been widely accepted by the industries and academia’s. Today all the complex VLSI circuitry which requires an on chip communication between them are the part of NOC. The mature concepts of communication network such as routing algorithm, switching technique, flow and congestion control etc in the NOC are the important features on which the performance of NOC depends. This paper introduces the efficient source routing algorithm which generates the minimum hop from source to destination. Performance of NOC network in terms of latency and throughput for minimum hop source routing algorithm is also evaluated. Keywords: Network on chip, routing algorithm, topology, traffic.
Similar to Comparison of different Ant based techniques for identification of shortest path in Distributed Network (19)
This document provides a technical review of secure banking using RSA and AES encryption methodologies. It discusses how RSA and AES are commonly used encryption standards for secure data transmission between ATMs and bank servers. The document first provides background on ATM security measures and risks of attacks. It then reviews related work analyzing encryption techniques. The document proposes using a one-time password in addition to a PIN for ATM authentication. It concludes that implementing encryption standards like RSA and AES can make transactions more secure and build trust in online banking.
This document analyzes the performance of various modulation schemes for achieving energy efficient communication over fading channels in wireless sensor networks. It finds that for long transmission distances, low-order modulations like BPSK are optimal due to their lower SNR requirements. However, as transmission distance decreases, higher-order modulations like 16-QAM and 64-QAM become more optimal since they can transmit more bits per symbol, outweighing their higher SNR needs. Simulations show lifetime extensions up to 550% are possible in short-range networks by using higher-order modulations instead of just BPSK. The optimal modulation depends on transmission distance and balancing the energy used by electronic components versus power amplifiers.
This document provides a review of mobility management techniques in vehicular ad hoc networks (VANETs). It discusses three modes of communication in VANETs: vehicle-to-infrastructure (V2I), vehicle-to-vehicle (V2V), and hybrid vehicle (HV) communication. For each communication mode, different mobility management schemes are required due to their unique characteristics. The document also discusses mobility management challenges in VANETs and outlines some open research issues in improving mobility management for seamless communication in these dynamic networks.
This document provides a review of different techniques for segmenting brain MRI images to detect tumors. It compares the K-means and Fuzzy C-means clustering algorithms. K-means is an exclusive clustering algorithm that groups data points into distinct clusters, while Fuzzy C-means is an overlapping clustering algorithm that allows data points to belong to multiple clusters. The document finds that Fuzzy C-means requires more time for brain tumor detection compared to other methods like hierarchical clustering or K-means. It also reviews related work applying these clustering algorithms to segment brain MRI images.
1) The document simulates and compares the performance of AODV and DSDV routing protocols in a mobile ad hoc network under three conditions: when users are fixed, when users move towards the base station, and when users move away from the base station.
2) The results show that both protocols have higher packet delivery and lower packet loss when users are either fixed or moving towards the base station, since signal strength is better in those scenarios. Performance degrades when users move away from the base station due to weaker signals.
3) AODV generally has better performance than DSDV, with higher throughput and packet delivery rates observed across the different user mobility conditions.
This document describes the design and implementation of 4-bit QPSK and 256-bit QAM modulation techniques using MATLAB. It compares the two techniques based on SNR, BER, and efficiency. The key steps of implementing each technique in MATLAB are outlined, including generating random bits, modulation, adding noise, and measuring BER. Simulation results show scatter plots and eye diagrams of the modulated signals. A table compares the results, showing that 256-bit QAM provides better performance than 4-bit QPSK. The document concludes that QAM modulation is more effective for digital transmission systems.
The document proposes a hybrid technique using Anisotropic Scale Invariant Feature Transform (A-SIFT) and Robust Ensemble Support Vector Machine (RESVM) to accurately identify faces in images. A-SIFT improves upon traditional SIFT by applying anisotropic scaling to extract richer directional keypoints. Keypoints are processed with RESVM and hypothesis testing to increase accuracy above 95% by repeatedly reprocessing images until the threshold is met. The technique was tested on similar and different facial images and achieved better results than SIFT in retrieval time and reduced keypoints.
This document studies the effects of dielectric superstrate thickness on microstrip patch antenna parameters. Three types of probes-fed patch antennas (rectangular, circular, and square) were designed to operate at 2.4 GHz using Arlondiclad 880 substrate. The antennas were tested with and without an Arlondiclad 880 superstrate of varying thicknesses. It was found that adding a superstrate slightly degraded performance by lowering the resonant frequency and increasing return loss and VSWR, while decreasing bandwidth and gain. Specifically, increasing the superstrate thickness or dielectric constant resulted in greater changes to the antenna parameters.
This document describes a wireless environment monitoring system that utilizes soil energy as a sustainable power source for wireless sensors. The system uses a microbial fuel cell to generate electricity from the microbial activity in soil. Two microbial fuel cells were created using different soil types and various additives to produce different current and voltage outputs. An electronic circuit was designed on a printed circuit board with components like a microcontroller and ZigBee transceiver. Sensors for temperature and humidity were connected to the circuit to monitor the environment wirelessly. The system provides a low-cost way to power remote sensors without needing battery replacement and avoids the high costs of wiring a power source.
1) The document proposes a model for a frequency tunable inverted-F antenna that uses ferrite material.
2) The resonant frequency of the antenna can be significantly shifted from 2.41GHz to 3.15GHz, a 31% shift, by increasing the static magnetic field placed on the ferrite material.
3) Altering the permeability of the ferrite allows tuning of the antenna's resonant frequency without changing the physical dimensions, providing flexibility to operate over a wide frequency range.
This document summarizes a research paper that presents a speech enhancement method using stationary wavelet transform. The method first classifies speech into voiced, unvoiced, and silence regions based on short-time energy. It then applies different thresholding techniques to the wavelet coefficients of each region - modified hard thresholding for voiced speech, semi-soft thresholding for unvoiced speech, and setting coefficients to zero for silence. Experimental results using speech from the TIMIT database corrupted with white Gaussian noise at various SNR levels show improved performance over other popular denoising methods.
This document reviews the design of an energy-optimized wireless sensor node that encrypts data for transmission. It discusses how sensing schemes that group nodes into clusters and transmit aggregated data can reduce energy consumption compared to individual node transmissions. The proposed node design calculates the minimum transmission power needed based on received signal strength and uses a periodic sleep/wake cycle to optimize energy when not sensing or transmitting. It aims to encrypt data at both the node and network level to further optimize energy usage for wireless communication.
This document discusses group consumption modes. It analyzes factors that impact group consumption, including external environmental factors like technological developments enabling new forms of online and offline interactions, as well as internal motivational factors at both the group and individual level. The document then proposes that group consumption modes can be divided into four types based on two dimensions: vertical (group relationship intensity) and horizontal (consumption action period). These four types are instrument-oriented, information-oriented, enjoyment-oriented, and relationship-oriented consumption modes. Finally, the document notes that consumption modes are dynamic and can evolve over time.
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Comparison of different Ant based techniques for identification of shortest path in Distributed Network
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 14, Issue 2 (Sep. - Oct. 2013), PP 47-52
www.iosrjournals.org
www.iosrjournals.org 47 | Page
Comparison of different Ant based techniques for identification
of shortest path in Distributed Network
Nidhi Nayak1
, Dr. Bhupesh Gour2
, Dr. Asif Ullah Khan3
1,2,3
(C.S.E, T.I.T/ R.G.P.V., Bhopal, India)
Abstract : A Distributed network is one in which the data is distributed and the data from source to destination
can be transferred through several nodes. When huge amount of packets are transferred through particular
node congestion may occur which may result loss of packets and bandwidth also can’t utilize. Hence the
shortest path is chosen and routing is done dynamically so that the node can’t suffer from congestion. Ant based
routing techniques is an efficient one in which routing is done on the behavior of the ants and a shortest path is
selected such that the packets can be send quickly and bandwidth also utilizes. Here in this paper we compare
different ant based techniques for the shortest path selection from source to destination in a distributed network.
Here on the basis of different Ant based techniques such as Max-Min, Rank based and Fuzzy rule based ant
technique an efficient algorithm of ant technique is implemented which performs better as compared to other
existing ant based techniques.
Keywords : ACO, multi congestion, QoS, hierarchical routing, pheromone.
I. INTRODUCTION
With the rapid growth of information applications as well as the increasing bandwidth requirements, it
is obvious that optical networks scale to multi-layer and multi-domain. In the MRN/MLN optical transport
network, traffic Engineering (TE) turns to be an essential requirement for Internet Service Provider (ISPs) to
improve the utilization of the total network resources and to maintain a desired overall Quality of Service (QoS)
with limited network resources. Ant Colony Optimization (ACO) is a paradigm for designing met heuristic
algorithms for combinatorial optimization problems [1]. The first algorithm which can be classified within this
framework was presented 1991[2, 3] and, since then, many diverse variants of the basic principle have been
reported in the literature. The necessary attribute of ACO algorithms is the combination of a priori information
about the structure of a promising solution with posterior information about the structure of previously obtained
good solution. An enhanced Ant colony optimization algorithm is used to resolve this difficulty in this work.
Ant Colony Optimization (ACO) is based on the behavior of ants seeking a path between their colony and a
source of food, and proposed by Italy scholar M. Dorigo [4]. The original idea is to solve a wider class of
numerical problems, until now, various aspects are studied about the behavior of ants. ACO can be briefly
introduced as follows. In the natural world, the behavior of ant is very simple; ants wander randomly to find
food and then back to their colony while laying down pheromone trails. Once other ant’s find the path, they are
likely to follow the trail, but not to keep wandering at random as before. Also the followed ants can reinforce the
trail if they get the food successfully. Thus, when a good path is discovered by one ant from the colony to a food
source, other ants have a larger probability to pursue that path, and constructive feedback eventually lead all the
ants following a single path at last.
Since the underlying topology and path-traversing mechanism in ACO exhibits many similarities to
urban water distribution systems (UWDS), the concepts and methodology employed by the ACO meta heuristic
can find a direct application in pipe routing optimization. If one substitutes the search for shortest path (ACO) to
the search for shortest or longest path (UWDS) and treats ACO ants, states, connections and cost function to
UWDS’s water flow, operational state, pipes/valves and customers serviced respectively then the ACO meta
heuristic can be employed in solving for the shortest (or longest) path in connected, acyclic graphs (such as pipe
networks).
Load balancing technique may improve the performance and scalability of Internet to a great extent.
Many researchers focal point on intra-domain load balancing which distributes traffic over multiple paths or
server farms in a single domain. However, resources in inter-domain are more limited than intra-domain, thus
load balancing is an effective strategy to avoid the resources congestion in inter-domain. Many multi-level and
multi-domain route algorithms have been proposed aiming at load balancing to reduce the service request
blocking, they only can generate the optimal solutions for some specific network, but original route algorithms
(such as hierarchical routing algorithm) in multi level and multi-domain can't compute the global optimization
path.
2. Comparison of different Ant based techniques for identification of shortest path in Distributed Network
www.iosrjournals.org 48 | Page
1.1 Ant Colony Optimization
ACO [5, 6] is a class of algorithms, whose primary part, called Ant System, was originally planned by
Colorni, Dorigo and Maniezzo [6, 7, and 8]. The main underlying idea, loosely inspired by the behavior of
actual ants, is that of a parallel search over several productive computational threads based on local problem
data and on a dynamic memory structure containing information on the quality of previously obtained result.
The collective performance emerging from the interaction of the different search threads has proved effective in
solving combinatorial optimization (CO) problems. Furthermore, an ACO algorithm includes two more
mechanisms: trail disappearance and, optionally, daemon events. Trail vanishing decreases all trail value over
time, in order to keep away from infinite accumulation of trails over some component. Daemon actions can be
used to implement centralized actions which cannot be performed by solo ants, such as the invocation of a local
optimization process, or the revise of global information to be used to decide whether to bias the search process
from a non-local perspective [9]. More specifically, an ant is a simple computational agent, which iteratively
constructs a explanation for the instance to resolve. Partial problem solutions are seen as states. At the center of
the ACO algorithm lies a loop, where at every iteration, each ant move (performs a step) from a state i to
another one y, consequent to a more complete fractional solution. That is, at each step s, each ant k computes a
set AK s (i) of possible expansions to its present state, and move to one of these in probability. The probability
allocation is specified as follows. For ant k, the probability piy k of stirring from state i to state y depends on the
grouping of two values: · the attractiveness h(iy) of the progress, as compute by some heuristic signifying the a
priori desirability of that move; the trail level t(iy) of the progress, signifying how capable it has been in the past
to make that particular move: it represents therefore an a posteriori indication of the desirability of that travel.
Trails are updated frequently when all ants have finished their solution, growing or declining the level of trails
corresponding to moves that were part of “good" or "bad" solution, correspondingly. The universal framework
just presented has been specified in different ways by the authors working on the ACO approach. The remainder
of Section 2 will summarize some of these contributions.
Figure1: Ant Colony Optimization
There are different properties known as ant’s generation and activity:
• An ant searches for a minimum (or maximum) cost solution to the optimization problem being addressed.
• Each ant has a memory use to store up all connections used to date, and so that the path can be evaluated at the
completion of solution construction.
• An ant can be assigning an initial position, for example an initial city in a TSP.
• An ant can go to any possible vertex until such time that no feasible moves exist or a termination criterion is
met (usually correlating to the completion of a candidate solution).
• Ants move according to a mixture of a pheromone value and a heuristic value which is connected with every
edge in the problem, the choice of where to move is usually a probabilistic one.
• When going from one vertex to a different vertex the pheromone value associated with the edge connecting
these vertices can be altered (known as online step-by-step pheromone update).
• An ant can repeat a constructed path at the completion of a solution updating the pheromone values of all
edges used in the solution (known as online delayed pheromone update).
• Once a answer is created, and after finishing online delayed pheromone update (if required) an ant dies, freeing
all allocated resources.
II. RELATED WORK
In 2011 by Le Lu, Shanguo Huang, Wanyi Gu [1] gives the concept about ant colony optimization
algorithm based on load balancing is anticipated. Ants pursue path not just depend on pheromone alone, Here
also taken available resources on the link as a aspect too. Simulations show the proposed method might decrease
the traffic blocking probability, and understand load balancing inside the network.
In 2006 by Neumann and Witt [2], Doerr, Neumann, Sudholt, and in 2007 by Witt [10], and Doerr and
Johannsen [11] studied a simple algorithm 1-ANT that constructs a pseudo Boolean solution according to a
3. Comparison of different Ant based techniques for identification of shortest path in Distributed Network
www.iosrjournals.org 49 | Page
straightforward construction graph where an ant makes independent choices for each bit. The 1-ANT records the
best solution found so far. In case a new solution is found which is not worse, the new solution replaces the old
one and pheromones are updated with respect to the new solution. This mechanism implies that each new best
so-far solution leads to only one pheromone update. The mentioned studies have shown that in case ρ is too
small this leads to a stagnation behavior as the knowledge gained through improvements cannot be adequately
stored in the pheromones. There is a phase transition from polynomial to exponential optimization times for
decreasing ρ.
In 2009 by Zhou [3] considered ACO for very simple instances of the TSP. This study was
significantly extended by Kotzing, ¨ Neumann, Roglin, and Witt in 2010 [12] who considered two different
construction procedures and presented an average-case result for the performance of ACO. Kotzing, Lehre,
Oliveto, ¨ and Neumann [13] investigated the performance of ACO for the minimum cut problem, but they only
presented negative results for pheromone-based construction procedures.
In 2010 by En-Jui Chang, Kai-Yuan Jheng, Hsien-Kai Hsin, Chih-Hao Chao and An-Yeu Wu [14]
gives the concept about Ant Colony Optimization (ACO) is a bio-inspired algorithm extensively applied in
optimization problems propose an ACO-based Cascaded Adaptive Routing (ACO CAR) by combining two
features: 1) table reforming by eliminating redundant information of far destinations from full routing table, and
2) adaptive searching of cascade point for more exact network information. The experimental results show that
ACO-CAR has lower latency and higher saturation throughput, and can be implemented with 19.05% memory
of full routing table.
In 1997 by Ruud Schoonderwoerd Owen Holland and Janet Bruten [15] gives the concept about a
simulated network models a typical distribution of calls between arbitrary nodes; nodes carrying an excess of
traffic can become congested, causing calls to fail. In calculation to calls, the network also supports inhabitants
of simple mobile agents with behaviors modeled on the trail laying abilities of ants. The agents move across the
network between arbitrary pairs of nodes, select their path at each transitional node according to the distribution
of simulated pheromones at every node. As they go they leave simulated pheromones as a function of their
distance from their source node, and the congestion encounter on their journey. Calls among nodes are routed as
a function of the pheromone distributions at each intermediate node. The performance of the network is
measured by the proportion of calls which fail. The ant-based system is shown to drop fewer calls than the
additional methods, while exhibit many striking features of distributed control.
In 1995 by Gambardella & Dorigo[16] and In 1996 by Dorigo, Maniezzo & Colorni [17] proposed the
metaphor of trail laying by ants has previously been successfully applied to certain combinatorial optimization
problems such as the Traveling Salesman Problem and Job Shop Scheduling These investigations were
concerned with finding one good solution to a static problem. However, the problem of load balancing in
telecommunication networks is essentially dynamic. The stochastic nature of calls, and the variation in call
distributions, means that the problem to be solved constantly changes with time, as different call combinations
give rise to congestion in different areas of the network. It is essential to maintain network performance
throughout the response of the load balancing system to a change in call distributions; therefore interested in the
performance of the algorithm over a certain period of time, and not merely in the eventual performance of some
fixed solution.
Markov chain Monte Carlo techniques have recently also been used to establish conditions for the
success of the Metropolis algorithm in the context of optimization in 2010 by Sanyal, S, and Biswas [18]. The
Metropolis algorithm is a very convenient algorithm for MCMC techniques as for this algorithm it is very easy
to compute the stationary distribution.
In a different line of research, Gutjahr and Sebastiani [19] and Neumann, Sudholt, and Witt [20]
studied an algorithm called MMAS, where the current best-so-far solution is reinforced in every generation.
This holds regardless of whether the best-so-far solution has been changed or not. This means that the algorithm
might reinforce the same solution over and more again, until the best-so-far solution is replace. In stark contrast
to the 1-ANT, the increased greediness of MMAS leads to polynomial upper bounds on simple pseudo Boolean
functions. Besides these results also analyses for hybridization with local search [21] and for ACO in
combinatorial optimization have appeared.
In 2008 by Neumann and Witt [22] investigated ACO algorithms for finding minimum spanning trees.
They considered two different construction procedures and proved that for one procedure the use of heuristic
information leads to a performance that is better than the performance of a 140simple evolutionary algorithm
[23], in terms of the number.
III. PROPOSED METHODOLOGY
The model is fully distributed, i.e. every node behaves separately as well as each ant or agent, and this
denotes that every node or ant is autonomous. Figure represents the table attached to each node or ant. In the
model, each node contains a table that includes information about other nodes in the system. At the initial state,
4. Comparison of different Ant based techniques for identification of shortest path in Distributed Network
www.iosrjournals.org 50 | Page
the table entries are Null. In each ant tour, the ant will carry the updated information about all nodes that the ant
has been passed throughout. Upon arrival of the ant at every node, the following events will be done:
1. If the node does not have the information contained in the ant table, these information will be passed to the
node table as it is.
2. If the node contains information that does not be present in the ant's table, the ant table will be updated.
3. If both of them share the similar information, the recently updated one will replace the other.
3.1 Max-min algorithm
1. Generate construction graph
2. Set the range of pheromone value to αmin, αmax where αmin>0
3. Set m ants at randomly chosen vertices on the construction graph
4. Initialize trails to αmax
5. Ant arbitrary moves on the graph to constructs its solutions
6. If iteration completed then the pheromone trails consisting of the best solution will be updated
7. The pheromone trail constructs αmin,<= α(i,j)<=αmax where α(i,j) shows the pheromone trails for the connection
8. It will be imposed such the
If α(i,j)<αmin then αmin,= α(i,j)
If α(i,j)>αmax then αmax= α(i,j)
9. Continues till the termination criteria is not met
3.2 Ant colony optimization with fuzzy logic
1. Obtain a problem & represent it as a graph so that it is covered by ants
2. Assign a heuristic preference to each choice that the ant has to take in each step to generate the solution
3. Initialize the pheromone value
4. Define fitness function
Do for each ant
Calculate the fitness value of the ant fa
/*updating ants best fitness value so far*/
If fa is better than abest then set current value as the new abest
/*updating population best fitness value so far*/
Set gbest to the best fitness value of all ants
5. Repeat until the termination criteria is not met
3.3 Rank based Algorithm
1. Generate construction graph
2. Initialize pheromone value
3. While not stop condition
4. Generate m ants for a tour
5. Perform sorting on ants by their length such that
l1<=l2<=lm
6. An ant to the trail update is weighted according to the rank R of the ant
7. The n best ant is chosen based on the rank R
8. If W is the weight of the trail level involvement of the best tour length than it should not be exceeded by any
other ant weight
IV. RESULT ANALYSIS
Here the result analysis of different Ant Based System algorithm is presented. The comparison between
Max-Min Ant Algorithm, Rank Based Ant Algorithm and Fuzzy Logic Based Ant Algorithm on the basis of
different parameters such as number of packets transferred and on the basis of number of ants is given.
The table shown below is the comparative analysis of different ant colony algorithms on the basis of no. Of ants
used to traverse the network and to find the average length of the best tour.
Algorithm No. of Ants Average Length of
Best Tour
Max Min 15 42
Rank Based 15 48
Fuzzy logic based 15 51
Proposed Method 15 29
Table 1. No. Of Ants Vs Average Length of Best Tour
5. Comparison of different Ant based techniques for identification of shortest path in Distributed Network
www.iosrjournals.org 51 | Page
The table shown below is the analysis of the time complexity of different ant based algorithms as the set up the
pheromone and the evaporation rate of the ants in the network. The results analysis shows the time required to
forward the packets if the evaporation rate and pheromone value is set.
Algorithm Time Evaporation
Rate
Pheromone Packets
Max Min 38478 ms 3 10 15
Rank Based 38678 ms 3 10 15
Fuzzy logic based 38792 ms 3 10 15
Proposed Method 38367 ms 3 10 15
Table 2. Time Complexity of Ant Based Algorithms
As shown in the graph below is the total pheromone deposited when a number of ants are moved from source
to destination. The ant when moved from source to destination will drop pheromone. Here we have chosen
some value of pheromone and value of evaporation for a limited amount of time, as the packet reach to the
destination the amount of pheromone is calculated for 5, 10, 15 and 20 packets.
Graph 1. Total Pheromone used in shortest path
V. CONCLUSION
The paper shows the comparative analysis of different ant based optimization algorithms. Here in this paper
three ant based algorithms for the optimization of the network is given and on the basis of the different
parameters of the ants in the network a study is shown. The result analysis shows the Average length and the
time complexity of the algorithms, so in the future these ant based optimization technique can be used for
various applications such that the efficiency of the network is increased.
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