This document summarizes a paper that proposes a neural network based approach for energy efficient clustering and routing in wireless sensor networks. The key points are:
1. It proposes a neural network based clustering algorithm to select cluster heads in a way that balances energy consumption.
2. It defines a routing metric based on transmission and reception energy and uses it to formulate the routing problem as a linear program to optimize energy efficiency.
3. It presents algorithms for cluster head selection using the neural network, and for multi-path routing and data transmission based on the routing metric and linear program formulation.
An Improved Deterministic Energy Efficient Clustering Protocol for Wireless S...IJERA Editor
In recent development, achieving the deployment of nodes, lifetime, fault tolerance, latency, energy efficiency in brief robustness and high reliability have become the prime research goals of wireless sensor network. In recent years many clustering protocols have been suggested on clustering structure based on heterogeneity. We propose improved deterministic energy-efficient clustering protocol for four types of nodes which extend the stability and lifetime of the network in team of first node get dead. Hence, it increases the heterogeneity and energy level of the network. I-DEC performs better than E-SEP, SEP and DEC with more stability and effective messages shows in simulation results.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
ENERGY EFFICIENT AGGREGATION WITH DIVERGENT SINK PLACEMENT FOR WIRELESS SENSO...ijasuc
In WSN the data aggregation is a means for condensing the energy requirement by reducing number of
transmission by combining the data and sending the final required result to the base station. The lifetime
of the WSN can be improved by employing the aggregation techniques. During the process of aggregation
the numbers of transmission are reduced by combining the similar data from the nearby areas. By using
the clustering technique and aggregating the correlated data greatly minimize the energy consumed in
collecting and disseminating the data. In this work, we evaluate the performance of a novel energy
efficient cluster based aggregation protocol (EECAP) for WSN. The main focus in this proposed work is
to study the performance of our proposed aggregation protocol with divergent sink placements such as
when sink is at the centre of the sensing field, corner of the sensing field or at a location selected
randomly in the sensor field. We present experimental results by calculating the lifetime of network in
terms of number of sensing rounds using various parameters such as – average remaining energy of
nodes, number of dead nodes after the specified number of sensing rounds. Finally the performance of
various aggregation algorithms such as LEACH, SEP and our proposed aggregation protocol (EECAP)
are compared with divergent sink placements. The simulation results demonstrates that EECAP exhibits
good performance in terms of lifetime and the energy consumption of the wireless sensor networks and
which can be as equally compared with existing clustering protocols.
The document describes localized, self-organizing approaches for constructing energy-efficient data aggregation trees in sensor networks. It proposes Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs) that use localized structures like LMST and RNG to approximate a minimum spanning tree. L-PEDAP then constructs an actual routing tree over these structures using localized parent selection strategies. Simulation results show L-PEDAP can achieve close to 90% of a theoretical upper bound on network lifetime derived in the paper, outperforming centralized solutions while meeting requirements like distributed operation, scalability, and robustness to failures.
A PROPOSAL TO IMPROVE SEP ROUTING PROTOCOL USING INSENSITIVE FUZZY C-MEANS IN...IJCNCJournal
This document proposes improving the SEP routing protocol in wireless sensor networks by combining it with the Insensitive Fuzzy C-Means clustering algorithm. The SEP protocol is an existing heterogeneous routing protocol that increases network stability but has limitations. The proposed SEP-εFCM protocol selects cluster heads using εFCM clustering, which can create more balanced clusters and reduce energy consumption. Simulation results showed the SEP-εFCM protocol performed better than the original SEP protocol, with more remaining live nodes and energy over time.
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
Ameliorate Threshold Distributed Energy Efficient Clustering Algorithm for He...chokrio
Ameliorating the lifetime in heterogeneous wireless sensor network is an important task because the sensor nodes are limited in the resource energy. The best way to improve a WSN lifetime is the clustering based algorithms in which each cluster is managed by a leader called Cluster Head. Each other node must communicate with this CH to send the data sensing. The nearest base station nodes must also send their data to their leaders, this causes a loss of energy. In this paper, we propose a new approach to ameliorate a threshold distributed energy efficient clustering protocol for heterogeneous wireless sensor networks by excluding closest nodes to the base station in the clustering process. We show by simulation in MATLAB that the proposed approach increases obviously the number of the received packet messages and prolongs the lifetime of the network compared to TDEEC protocol.
Energy efficient clustering in heterogeneousIJCNCJournal
Cluster head election is a key technique used to reduce energy consumption and enhancing the throughput
of wireless sensor networks. In this paper, a new energy efficient clustering (E2C) protocol for
heterogeneous wireless sensor networks is proposed. Cluster head is elected based on the predicted
residual energy of sensors, optimal probability of a sensor to become a cluster head, and its degree of
connectivity as the parameters. The probability threshold to compete for the role of cluster head is derived.
The probability threshold has been extended for multi-levels energy heterogeneity in the network. The
proposed E2C protocol is simulated in MATLAB. Results obtained in the simulationshowthat performance
of the proposed E2Cprotocol is betterthan stable election protocol (SEP), and distributed energy efficient
clustering (DEEC) protocol in terms of energy consumption, throughput, and network lifetime.
An Improved Deterministic Energy Efficient Clustering Protocol for Wireless S...IJERA Editor
In recent development, achieving the deployment of nodes, lifetime, fault tolerance, latency, energy efficiency in brief robustness and high reliability have become the prime research goals of wireless sensor network. In recent years many clustering protocols have been suggested on clustering structure based on heterogeneity. We propose improved deterministic energy-efficient clustering protocol for four types of nodes which extend the stability and lifetime of the network in team of first node get dead. Hence, it increases the heterogeneity and energy level of the network. I-DEC performs better than E-SEP, SEP and DEC with more stability and effective messages shows in simulation results.
Coverage and Connectivity Aware Neural Network Based Energy Efficient Routing...graphhoc
There are many challenges when designing and deploying wireless sensor networks (WSNs). One of the key challenges is how to make full use of the limited energy to prolong the lifetime of the network, because energy is a valuable resource in WSNs. The status of energy consumption should be continuously monitored after network deployment. In this paper, we propose coverage and connectivity aware neural network based energy efficient routing in WSN with the objective of maximizing the network lifetime. In the proposed scheme, the problem is formulated as linear programming (LP) with coverage and connectivity aware constraints. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage and connectivity aware routing with data transmission. The proposed scheme is compared with existing schemes with respect to the parameters such as number of alive nodes, packet delivery fraction, and node residual energy. The simulation results show that the proposed scheme can be used in wide area of applications in WSNs.
ENERGY EFFICIENT AGGREGATION WITH DIVERGENT SINK PLACEMENT FOR WIRELESS SENSO...ijasuc
In WSN the data aggregation is a means for condensing the energy requirement by reducing number of
transmission by combining the data and sending the final required result to the base station. The lifetime
of the WSN can be improved by employing the aggregation techniques. During the process of aggregation
the numbers of transmission are reduced by combining the similar data from the nearby areas. By using
the clustering technique and aggregating the correlated data greatly minimize the energy consumed in
collecting and disseminating the data. In this work, we evaluate the performance of a novel energy
efficient cluster based aggregation protocol (EECAP) for WSN. The main focus in this proposed work is
to study the performance of our proposed aggregation protocol with divergent sink placements such as
when sink is at the centre of the sensing field, corner of the sensing field or at a location selected
randomly in the sensor field. We present experimental results by calculating the lifetime of network in
terms of number of sensing rounds using various parameters such as – average remaining energy of
nodes, number of dead nodes after the specified number of sensing rounds. Finally the performance of
various aggregation algorithms such as LEACH, SEP and our proposed aggregation protocol (EECAP)
are compared with divergent sink placements. The simulation results demonstrates that EECAP exhibits
good performance in terms of lifetime and the energy consumption of the wireless sensor networks and
which can be as equally compared with existing clustering protocols.
The document describes localized, self-organizing approaches for constructing energy-efficient data aggregation trees in sensor networks. It proposes Localized Power-Efficient Data Aggregation Protocols (L-PEDAPs) that use localized structures like LMST and RNG to approximate a minimum spanning tree. L-PEDAP then constructs an actual routing tree over these structures using localized parent selection strategies. Simulation results show L-PEDAP can achieve close to 90% of a theoretical upper bound on network lifetime derived in the paper, outperforming centralized solutions while meeting requirements like distributed operation, scalability, and robustness to failures.
A PROPOSAL TO IMPROVE SEP ROUTING PROTOCOL USING INSENSITIVE FUZZY C-MEANS IN...IJCNCJournal
This document proposes improving the SEP routing protocol in wireless sensor networks by combining it with the Insensitive Fuzzy C-Means clustering algorithm. The SEP protocol is an existing heterogeneous routing protocol that increases network stability but has limitations. The proposed SEP-εFCM protocol selects cluster heads using εFCM clustering, which can create more balanced clusters and reduce energy consumption. Simulation results showed the SEP-εFCM protocol performed better than the original SEP protocol, with more remaining live nodes and energy over time.
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
Ameliorate Threshold Distributed Energy Efficient Clustering Algorithm for He...chokrio
Ameliorating the lifetime in heterogeneous wireless sensor network is an important task because the sensor nodes are limited in the resource energy. The best way to improve a WSN lifetime is the clustering based algorithms in which each cluster is managed by a leader called Cluster Head. Each other node must communicate with this CH to send the data sensing. The nearest base station nodes must also send their data to their leaders, this causes a loss of energy. In this paper, we propose a new approach to ameliorate a threshold distributed energy efficient clustering protocol for heterogeneous wireless sensor networks by excluding closest nodes to the base station in the clustering process. We show by simulation in MATLAB that the proposed approach increases obviously the number of the received packet messages and prolongs the lifetime of the network compared to TDEEC protocol.
Energy efficient clustering in heterogeneousIJCNCJournal
Cluster head election is a key technique used to reduce energy consumption and enhancing the throughput
of wireless sensor networks. In this paper, a new energy efficient clustering (E2C) protocol for
heterogeneous wireless sensor networks is proposed. Cluster head is elected based on the predicted
residual energy of sensors, optimal probability of a sensor to become a cluster head, and its degree of
connectivity as the parameters. The probability threshold to compete for the role of cluster head is derived.
The probability threshold has been extended for multi-levels energy heterogeneity in the network. The
proposed E2C protocol is simulated in MATLAB. Results obtained in the simulationshowthat performance
of the proposed E2Cprotocol is betterthan stable election protocol (SEP), and distributed energy efficient
clustering (DEEC) protocol in terms of energy consumption, throughput, and network lifetime.
The document summarizes a research paper that proposes using a genetic algorithm to optimize energy efficiency in wireless sensor networks. Specifically:
- It clusters sensor nodes using a genetic algorithm to minimize total transmission distance and prolong network lifetime.
- The genetic algorithm determines the optimal number of clusters, cluster heads, cluster members, and transmission schedules.
- It defines a fitness function accounting for total transmission distance, number of cluster heads, and energy used to transmit from clusters to the base station.
- Simulation results show the genetic algorithm approach can find an optimal solution and decreases total distance and number of cluster heads with each generation, improving energy efficiency.
Optimal Transmit Power and Packet Size in Wireless Sensor Networks in Shadowe...IDES Editor
This paper investigates the effects of
shadowing on the optimal transmit power required to
sustain the network connectivity while maintaining a
predefined maximum tolerable Bit Error Rate (BER) in
a Wireless Sensor Networks (WSN). Optimization of
transmit power is of great importance in WSN since
sensor nodes are battery driven and optimization helps
to increase battery life by reducing inter node
interference significantly. An infinite Automatic Repeat
Request (ARQ) model has been considered to assess the
impact of shadowing and other network conditions on
energy requirement for successful packet transmission in
WSN. We also find the optimal packet length based on
energy efficiency. Effects of shadowing on optimal packet
size and energy efficiency in packetized data
transmission are also investigated. Further energy
consumption is minimized considering a variable packet
length based transmission. Use of optimal packet size
shows a significant reduction in energy spending.
NEW APPROACH TO IMPROVING LIFETIME IN HETEROGENEOUS WIRELESS SENSOR NETWORKS ...chokrio
The major challenge for wireless sensor networks is energy consumption minimization. Wireless transmission consumes much more of energy. In the clustered network, a few nodes become cluster heads which causes the energetic heterogeneity. Therefore the behavior of the sensor network becomes very unstable. Hence, the need to apply the balancing of energy consumption across all nodes of the heterogeneous network is very important to prevent the death of those nodes and thereafter increase the
lifetime of the network. DEEC (Distributed Energy Efficient Clustering) is one of routing protocols
designed to extend the stability time of the network by reducing energy consumption. A disadvantage of
DEEC, which doesn’t takes into account the cluster size and the density of nodes in this cluster to elect the
cluster heads. When multiple cluster heads are randomly selected within a small area, a big extra energy
loss occurs. The amount of lost energy is approximately proportional to the number of cluster heads in this
area. In this paper, we propose to improve DEEC by a modified energy efficient algorithm for choosing
cluster heads that exclude a number of low energy levels nodes due to their distribution density and their
dimensions area. We show by simulation in MATLAB that the proposed approach increases the number of
received messages and prolong the lifetime of the network compared to DEEC. We conclude by studying
the parameters of heterogeneity that proposed technique provides a longer stability period which increases
by increasing the number of nodes which are excluded from the cluster head selection.
Based on Heterogeneity and Electing Probability of Nodes Improvement in LEACHijsrd.com
In heterogeneous sensor networks, certain nodes become cluster heads which aggregate the data of their cluster nodes and transfer it to the sink. An Improved Energy leach protocol for cluster head selection in a hierarchically clustered heterogeneous network to reorganize the network topology efficiently is proposed in this research work. The proposed algorithm will use thresholding to improve the cluster head selection. The presented algorithm considers the sensor nodes in wireless network and randomly distributed in the heterogeneous network. The coordinates of the sink and the dimensions of the sensor field are known in prior.
The document compares two hierarchical routing schemes for wireless sensor networks: EEPSC and EEEPSC. EEPSC divides the network into static clusters and uses temporary cluster heads to distribute energy load. EEEPSC extends EEPSC by also considering distance between nodes and cluster heads when selecting cluster heads, in order to reduce inter-cluster communication costs. Simulation results show that EEEPSC increases network lifetime by consuming less energy and keeping more nodes alive over time compared to EEPSC.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
QUAD TREE BASED STATIC MULTI HOP LEACH ENERGY EFFICIENT ROUTING PROTOCOL: A N...IJCNCJournal
This research work propounds a simple graph theory semblance Divide and Conquer Quad tree based Multi-hop Static Leach (DCQMS-Leach) energy efficient routing protocol for wireless sensor networks. The pivotal theme of this research work is to demonstrate how divide and conquer plays a pivotal role in a multi-hop static leach energy efficient routing protocol. This research work motivates, enforces, reckons the DCQMS-Leach energy efficient routing protocol in wireless sensor networks using Mat lab simulator.This research work also computes the performance concepts of DCQMS-Leach routing protocol using various performance metrics such as Packet Drop Rate (PDR), Throughput, and End to End Delay (EED) by comparing and contrasting alive nodes with number of nodes, number of each packets sent to the cluster heads with rounds, number of cluster heads with rounds, number of packets forwarded to the base station with rounds and finally dead nodes with number of rounds. In order to curtail energy consumption this research work proffers a routing methodology such as DCQMS-Leach in energy efficient wireless,sensor routing protocol. The recommended DCQMS-Leach overcomes the in adequacies of all other different leach protocols suggested by the previous researchers.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
The document presents an improved clustering algorithm for load balancing in wireless sensor networks. The algorithm aims to address uneven cluster sizes that can negatively impact load balancing. It does this by selecting master and vice master nodes to partition regions and subregions, aiming to make cluster sizes more balanced. The algorithm has setup and steady state phases. In the setup phase, regions are partitioned recursively if needed to select balanced cluster heads. In the steady state phase, nodes send data to their cluster heads, which then send aggregated data to the base station. Simulation results show the improved algorithm increases network lifetime and energy efficiency compared to LEACH and E-LEACH algorithms.
Wireless sensor networks (WSN) have been widely used in various applications.
In these networks nodes collect data from the attached sensors and send their data to a base
station. However, nodes in WSN have limited power supply in form of battery so the nodes
are expected to minimize energy consumption in order to maximize the lifetime of WSN. A
number of techniques have been proposed in the literature to reduce the energy
consumption significantly. In this paper, we propose a new clustering based technique
which is a modification of the popular LEACH algorithm. In this technique, first cluster
heads are elected using the improved LEACH algorithm as usual, and then a cluster of
nodes is formed based on the distance between node and cluster head. Finally, data from
node is transferred to cluster head. Cluster heads forward data, after applying aggregation,
to the cluster head that is closer to it than sink in forward direction or directly to the sink.
This reduction in distance travelled improves the performance over LEACH algorithm
significantly.
This document discusses multihop/direct forwarding (MDF) for wireless sensor networks deployed in 3D environments. It analyzes the behavior of MDF and compares it to other forwarding schemes. The key points are:
1) MDF is analyzed for its ability to balance energy consumption across sensor nodes in a 3D network model, with the goal of prolonging network lifetime.
2) The network is divided into logical nodes based on distance from the base station. Equations are derived for dividing packet flows between nodes to optimize battery lifespan.
3) Simulation results show MDF balances energy use better than other schemes like closest forwarding, leading to longer network lifetime when applied in 3D wireless sensor networks.
Energy Efficient Multipath Data Fusion Technique for Wireless Sensor NetworksIDES Editor
In wireless sensor networks (WSN), data fusion
should be energy efficient. But, determining the optimal
number of aggregators in an energy efficient manner is a
challenging task. Moreover, the existing data fusion
techniques mostly use the same path for transmitting
aggregated data to the sink which reduces the nodes lifetime.
In this paper, we propose a technique which combines energy
efficiency and multiple path selection for data fusion in WSN.
The network is partitioned into various clusters and the node
with highest residual energy is selected as the cluster head.
The sink computes multiple paths to each cluster head for
data transmission. The distributed source coding and the
lifting scheme wavelet transform are used for compressing
the data at the CH. During each round of transmission, the
path is changed in a round robin manner, to conserve the
energy. This process is repeated for each cluster. From our
simulation results we show that this data fusion technique
has less energy consumption with increased packet delivery
ratio, when compared with the existing schemes.
Extending the longevity, is a significant job to be accomplished by these sensor networks. The traditional routing protocols could not be applied here, due to its nodes powered by batteries. Nodes are often clustered in to non-overlapping clusters, so as to provide energy efficiency. A concise overview on clustering processes, within wireless sensor networks is given in this paper. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.
In Cognitive Radio Networks (CRN), Cooperative Spectrum Sensing (CSS) is
used to improve performance of spectrum sensing techniques used for detection of licensed
(Primary) user’s signal. In CSS, the spectrum sensing information from multiple unlicensed
(Secondary) users are combined to take final decision about presence of primary signal. The
mixing techniques used to generate final decision about presence of PU’s signal are also
called as Fusion techniques / rules. The fusion techniques are further classified as data
fusion and decision fusion techniques. In data fusion technique all the secondary users
(SUs) share their raw information of spectrum detection like detected energy or other
statistical information, while in decision fusion technique all the SUs take their local
decisions and share the decision by sending ‘0’ or ‘1’ corresponding to absence and presence
of PU’s signal respectively. The rules used in decision fusion techniques are OR rule, AND
rule and K-out-of-N rule. The CSS is further classified as distributed CSS and centralized
CSS. In distributed CSS all the SUs share the spectrum detection information with each
other and by mixing the shared information; all the SUs take final decision individually. In
centralized CSS all the SUs send their detected information to a secondary base station /
central unit which combines the shared information and takes final decision. The secondary
base station shares the final decision with all the SUs in the CRN. This paper covers
overview of information fusion methods used for CSS and analysis of decision fusion rules
with simulation results.
Gateway based multi hop distributed energy efficient clustering protocol for ...ijujournal
Wireless sensor network consists of application oriented and cheap micro-devices called sensors nodes having potential of connecting the physical world with virtual world by their sensing abilities. These sensor nodes are having restrained battery sources. Efficient energy management is current area of research in wireless sensor networks. Here we advice one such energy aware multi-hop protocol (G-DEEC) for two
level heterogeneous networks. In G-DEEC, the Base Station is placed out of sensing area and rechargeable
gateway nodes are placed inside field with other randomly deployed sensor nodes. Simulation shows the proposed protocol G-DEEC is better than single-hop DEEC in terms of number of half dead nodes, alive nodes and dead nodes; thereby showing improvement in network lifetime and stability.
Energy aware clustering protocol (eacp)IJCNCJournal
The document summarizes an Energy Aware Clustering Protocol (EACP) proposed for heterogeneous wireless sensor networks. EACP introduces heterogeneity by using two types of nodes: normal and advanced. Normal nodes elect cluster heads using a probability scheme based on residual and average energy. Advanced nodes use a separate probability scheme and act as gateways for normal cluster heads, transmitting their data to the base station. The performance of EACP is compared to SEP through simulations, showing better results for stability period, network life and energy savings.
MULTI-HOP DISTRIBUTED ENERGY EFFICIENT HIERARCHICAL CLUSTERING SCHEME FOR HET...ijfcstjournal
Wireless sensor network (WSNs) are network of Sensor Nodes (SNs) with inherent sensing, processing and
communicating abilities. One of current concerns in wireless sensor networks is developing a stable
clustered heterogeneous protocol prolonging the network lifetime with minimum consumption of battery
power. In the recent times, many routing protocols have been proposed increasing the network lifetime,
stability in short proposing a reliable and robust routing protocol. In this paper we study the impact of
hierarchical clustered network with sensor nodes of two-level heterogeneity. The main approach in this
research is to develop an enhanced multi-hop DEEC routing protocol unlike DEEC. Simulation results
show the proposed protocol is better than DEEC in terms of FDN (First Dead Node), energy consumption
and Packet transmission.
ADAPTIVE SENSOR SENSING RANGE TO MAXIMISE LIFETIME OF WIRELESS SENSOR NETWORK IJCNCJournal
Wireless Sensor Network (WSN) is commonly used to collect information from a remote area and one of the most important challenges associated with WSN is to monitor all targets in a given area while maximizing network lifetime. In wireless communication, energy consumption is proportional to the breadth of sensing range and path loss exponent. Hence, the energy consumption of communication can be minimized by varying the sensing range and decreasing the number of messages being sent. Sensing energy can be optimized by reducing the repeated coverage target. In this paper, an Adaptive Sensor Sensing Range (ASSR) technique is proposed to maximize the WSN Lifetime. This work considers a sensor network with an adaptive sensing range that are randomly deployed in the monitoring area. The sensor is adaptive in nature and can be modified in order to save power while achieving maximum time of monitoring to increase the lifetime of WSN network. The objective of ASSR is to find the best sensing range for each sensor to cover all targets in the network, which yields maximize the time of monitoring of all targets and eliminating double sensing for the same target. Experiments were conducted using an NS3 simulator to verify our proposed technique. Results show that ASSR is capable to improve the network lifetime by 20% as compared to other recent techniques in the case of a small network while achieving an 8% improvement for the case of a large networks.
Cluster-based Target Tracking and Recovery Algorithm in Wireless Sensor NetworkIJASCSE
This document summarizes a research paper that proposes an energy efficient recovery technique for target tracking in wireless sensor networks. It begins with an introduction to target tracking in WSNs and the related challenges of energy efficiency and recovery when targets are lost. It then reviews existing target tracking and recovery techniques. The proposed technique uses dynamic clustering to predict target locations and only wakes clusters near the predicted path to save energy. The recovery mechanism has three steps: 1) the current cluster head announces a lost target, 2) it initiates recovery by waking nearby clusters to search predicted locations, and 3) once the target is found, only tracking clusters remain active while others sleep. The paper argues this approach reduces communication overhead and active clusters compared to existing
The document analyzes and compares the performance of two Medium Access Control (MAC) protocols for wireless sensor networks: Sensor MAC (S-MAC) and Hybrid MAC (H-MAC).
[1] S-MAC is a contention-based protocol that reduces energy waste from idle listening by implementing synchronized sleep and listen schedules. Nodes form virtual clusters to wake up and communicate at the same time. H-MAC improves on this with a slotted frame structure that dynamically allocates slots.
[2] The performance of the two protocols is evaluated based on end-to-end delay, packet delivery ratio, packet drop rate, and energy consumption using the NS2 simulation tool.
[3] Spatial correlation
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
This document describes a new clustering protocol called WDDC (Weighted Dynamic Distributed Clustering) for heterogeneous wireless sensor networks. WDDC selects cluster heads based on the ratio of a node's residual energy to the average network energy, and also considers the distance between nodes and the base station. WDDC divides the network lifetime into two zones and changes its behavior dynamically between the zones. Simulation results show WDDC outperforms other clustering protocols like SEP and DEEC in terms of energy efficiency and extending network lifetime.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
The document summarizes a research paper that proposes using a genetic algorithm to optimize energy efficiency in wireless sensor networks. Specifically:
- It clusters sensor nodes using a genetic algorithm to minimize total transmission distance and prolong network lifetime.
- The genetic algorithm determines the optimal number of clusters, cluster heads, cluster members, and transmission schedules.
- It defines a fitness function accounting for total transmission distance, number of cluster heads, and energy used to transmit from clusters to the base station.
- Simulation results show the genetic algorithm approach can find an optimal solution and decreases total distance and number of cluster heads with each generation, improving energy efficiency.
Optimal Transmit Power and Packet Size in Wireless Sensor Networks in Shadowe...IDES Editor
This paper investigates the effects of
shadowing on the optimal transmit power required to
sustain the network connectivity while maintaining a
predefined maximum tolerable Bit Error Rate (BER) in
a Wireless Sensor Networks (WSN). Optimization of
transmit power is of great importance in WSN since
sensor nodes are battery driven and optimization helps
to increase battery life by reducing inter node
interference significantly. An infinite Automatic Repeat
Request (ARQ) model has been considered to assess the
impact of shadowing and other network conditions on
energy requirement for successful packet transmission in
WSN. We also find the optimal packet length based on
energy efficiency. Effects of shadowing on optimal packet
size and energy efficiency in packetized data
transmission are also investigated. Further energy
consumption is minimized considering a variable packet
length based transmission. Use of optimal packet size
shows a significant reduction in energy spending.
NEW APPROACH TO IMPROVING LIFETIME IN HETEROGENEOUS WIRELESS SENSOR NETWORKS ...chokrio
The major challenge for wireless sensor networks is energy consumption minimization. Wireless transmission consumes much more of energy. In the clustered network, a few nodes become cluster heads which causes the energetic heterogeneity. Therefore the behavior of the sensor network becomes very unstable. Hence, the need to apply the balancing of energy consumption across all nodes of the heterogeneous network is very important to prevent the death of those nodes and thereafter increase the
lifetime of the network. DEEC (Distributed Energy Efficient Clustering) is one of routing protocols
designed to extend the stability time of the network by reducing energy consumption. A disadvantage of
DEEC, which doesn’t takes into account the cluster size and the density of nodes in this cluster to elect the
cluster heads. When multiple cluster heads are randomly selected within a small area, a big extra energy
loss occurs. The amount of lost energy is approximately proportional to the number of cluster heads in this
area. In this paper, we propose to improve DEEC by a modified energy efficient algorithm for choosing
cluster heads that exclude a number of low energy levels nodes due to their distribution density and their
dimensions area. We show by simulation in MATLAB that the proposed approach increases the number of
received messages and prolong the lifetime of the network compared to DEEC. We conclude by studying
the parameters of heterogeneity that proposed technique provides a longer stability period which increases
by increasing the number of nodes which are excluded from the cluster head selection.
Based on Heterogeneity and Electing Probability of Nodes Improvement in LEACHijsrd.com
In heterogeneous sensor networks, certain nodes become cluster heads which aggregate the data of their cluster nodes and transfer it to the sink. An Improved Energy leach protocol for cluster head selection in a hierarchically clustered heterogeneous network to reorganize the network topology efficiently is proposed in this research work. The proposed algorithm will use thresholding to improve the cluster head selection. The presented algorithm considers the sensor nodes in wireless network and randomly distributed in the heterogeneous network. The coordinates of the sink and the dimensions of the sensor field are known in prior.
The document compares two hierarchical routing schemes for wireless sensor networks: EEPSC and EEEPSC. EEPSC divides the network into static clusters and uses temporary cluster heads to distribute energy load. EEEPSC extends EEPSC by also considering distance between nodes and cluster heads when selecting cluster heads, in order to reduce inter-cluster communication costs. Simulation results show that EEEPSC increases network lifetime by consuming less energy and keeping more nodes alive over time compared to EEPSC.
International Journal of Advanced Smart Sensor Network Systems ( IJASSN )ijassn
With the availability of low cost, short range sensor technology along with advances in wireless networking, sensor networks has become a hot topic of discussion. The International Journal of Advanced Smart Sensor Network Systems is an open access peer-reviewed journal which focuses on applied research and applications of sensor networks. While sensor networks provide ample opportunities to provide various services, its effective deployment in large scale is still challenging due to various factors. This journal provides a forum that impacts the development of high performance computing solutions to problems arising due to the complexities of sensor network systems. It also acts as a path to exchange novel ideas about impacts of sensor networks research.
QUAD TREE BASED STATIC MULTI HOP LEACH ENERGY EFFICIENT ROUTING PROTOCOL: A N...IJCNCJournal
This research work propounds a simple graph theory semblance Divide and Conquer Quad tree based Multi-hop Static Leach (DCQMS-Leach) energy efficient routing protocol for wireless sensor networks. The pivotal theme of this research work is to demonstrate how divide and conquer plays a pivotal role in a multi-hop static leach energy efficient routing protocol. This research work motivates, enforces, reckons the DCQMS-Leach energy efficient routing protocol in wireless sensor networks using Mat lab simulator.This research work also computes the performance concepts of DCQMS-Leach routing protocol using various performance metrics such as Packet Drop Rate (PDR), Throughput, and End to End Delay (EED) by comparing and contrasting alive nodes with number of nodes, number of each packets sent to the cluster heads with rounds, number of cluster heads with rounds, number of packets forwarded to the base station with rounds and finally dead nodes with number of rounds. In order to curtail energy consumption this research work proffers a routing methodology such as DCQMS-Leach in energy efficient wireless,sensor routing protocol. The recommended DCQMS-Leach overcomes the in adequacies of all other different leach protocols suggested by the previous researchers.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
The document presents an improved clustering algorithm for load balancing in wireless sensor networks. The algorithm aims to address uneven cluster sizes that can negatively impact load balancing. It does this by selecting master and vice master nodes to partition regions and subregions, aiming to make cluster sizes more balanced. The algorithm has setup and steady state phases. In the setup phase, regions are partitioned recursively if needed to select balanced cluster heads. In the steady state phase, nodes send data to their cluster heads, which then send aggregated data to the base station. Simulation results show the improved algorithm increases network lifetime and energy efficiency compared to LEACH and E-LEACH algorithms.
Wireless sensor networks (WSN) have been widely used in various applications.
In these networks nodes collect data from the attached sensors and send their data to a base
station. However, nodes in WSN have limited power supply in form of battery so the nodes
are expected to minimize energy consumption in order to maximize the lifetime of WSN. A
number of techniques have been proposed in the literature to reduce the energy
consumption significantly. In this paper, we propose a new clustering based technique
which is a modification of the popular LEACH algorithm. In this technique, first cluster
heads are elected using the improved LEACH algorithm as usual, and then a cluster of
nodes is formed based on the distance between node and cluster head. Finally, data from
node is transferred to cluster head. Cluster heads forward data, after applying aggregation,
to the cluster head that is closer to it than sink in forward direction or directly to the sink.
This reduction in distance travelled improves the performance over LEACH algorithm
significantly.
This document discusses multihop/direct forwarding (MDF) for wireless sensor networks deployed in 3D environments. It analyzes the behavior of MDF and compares it to other forwarding schemes. The key points are:
1) MDF is analyzed for its ability to balance energy consumption across sensor nodes in a 3D network model, with the goal of prolonging network lifetime.
2) The network is divided into logical nodes based on distance from the base station. Equations are derived for dividing packet flows between nodes to optimize battery lifespan.
3) Simulation results show MDF balances energy use better than other schemes like closest forwarding, leading to longer network lifetime when applied in 3D wireless sensor networks.
Energy Efficient Multipath Data Fusion Technique for Wireless Sensor NetworksIDES Editor
In wireless sensor networks (WSN), data fusion
should be energy efficient. But, determining the optimal
number of aggregators in an energy efficient manner is a
challenging task. Moreover, the existing data fusion
techniques mostly use the same path for transmitting
aggregated data to the sink which reduces the nodes lifetime.
In this paper, we propose a technique which combines energy
efficiency and multiple path selection for data fusion in WSN.
The network is partitioned into various clusters and the node
with highest residual energy is selected as the cluster head.
The sink computes multiple paths to each cluster head for
data transmission. The distributed source coding and the
lifting scheme wavelet transform are used for compressing
the data at the CH. During each round of transmission, the
path is changed in a round robin manner, to conserve the
energy. This process is repeated for each cluster. From our
simulation results we show that this data fusion technique
has less energy consumption with increased packet delivery
ratio, when compared with the existing schemes.
Extending the longevity, is a significant job to be accomplished by these sensor networks. The traditional routing protocols could not be applied here, due to its nodes powered by batteries. Nodes are often clustered in to non-overlapping clusters, so as to provide energy efficiency. A concise overview on clustering processes, within wireless sensor networks is given in this paper. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.
In Cognitive Radio Networks (CRN), Cooperative Spectrum Sensing (CSS) is
used to improve performance of spectrum sensing techniques used for detection of licensed
(Primary) user’s signal. In CSS, the spectrum sensing information from multiple unlicensed
(Secondary) users are combined to take final decision about presence of primary signal. The
mixing techniques used to generate final decision about presence of PU’s signal are also
called as Fusion techniques / rules. The fusion techniques are further classified as data
fusion and decision fusion techniques. In data fusion technique all the secondary users
(SUs) share their raw information of spectrum detection like detected energy or other
statistical information, while in decision fusion technique all the SUs take their local
decisions and share the decision by sending ‘0’ or ‘1’ corresponding to absence and presence
of PU’s signal respectively. The rules used in decision fusion techniques are OR rule, AND
rule and K-out-of-N rule. The CSS is further classified as distributed CSS and centralized
CSS. In distributed CSS all the SUs share the spectrum detection information with each
other and by mixing the shared information; all the SUs take final decision individually. In
centralized CSS all the SUs send their detected information to a secondary base station /
central unit which combines the shared information and takes final decision. The secondary
base station shares the final decision with all the SUs in the CRN. This paper covers
overview of information fusion methods used for CSS and analysis of decision fusion rules
with simulation results.
Gateway based multi hop distributed energy efficient clustering protocol for ...ijujournal
Wireless sensor network consists of application oriented and cheap micro-devices called sensors nodes having potential of connecting the physical world with virtual world by their sensing abilities. These sensor nodes are having restrained battery sources. Efficient energy management is current area of research in wireless sensor networks. Here we advice one such energy aware multi-hop protocol (G-DEEC) for two
level heterogeneous networks. In G-DEEC, the Base Station is placed out of sensing area and rechargeable
gateway nodes are placed inside field with other randomly deployed sensor nodes. Simulation shows the proposed protocol G-DEEC is better than single-hop DEEC in terms of number of half dead nodes, alive nodes and dead nodes; thereby showing improvement in network lifetime and stability.
Energy aware clustering protocol (eacp)IJCNCJournal
The document summarizes an Energy Aware Clustering Protocol (EACP) proposed for heterogeneous wireless sensor networks. EACP introduces heterogeneity by using two types of nodes: normal and advanced. Normal nodes elect cluster heads using a probability scheme based on residual and average energy. Advanced nodes use a separate probability scheme and act as gateways for normal cluster heads, transmitting their data to the base station. The performance of EACP is compared to SEP through simulations, showing better results for stability period, network life and energy savings.
MULTI-HOP DISTRIBUTED ENERGY EFFICIENT HIERARCHICAL CLUSTERING SCHEME FOR HET...ijfcstjournal
Wireless sensor network (WSNs) are network of Sensor Nodes (SNs) with inherent sensing, processing and
communicating abilities. One of current concerns in wireless sensor networks is developing a stable
clustered heterogeneous protocol prolonging the network lifetime with minimum consumption of battery
power. In the recent times, many routing protocols have been proposed increasing the network lifetime,
stability in short proposing a reliable and robust routing protocol. In this paper we study the impact of
hierarchical clustered network with sensor nodes of two-level heterogeneity. The main approach in this
research is to develop an enhanced multi-hop DEEC routing protocol unlike DEEC. Simulation results
show the proposed protocol is better than DEEC in terms of FDN (First Dead Node), energy consumption
and Packet transmission.
ADAPTIVE SENSOR SENSING RANGE TO MAXIMISE LIFETIME OF WIRELESS SENSOR NETWORK IJCNCJournal
Wireless Sensor Network (WSN) is commonly used to collect information from a remote area and one of the most important challenges associated with WSN is to monitor all targets in a given area while maximizing network lifetime. In wireless communication, energy consumption is proportional to the breadth of sensing range and path loss exponent. Hence, the energy consumption of communication can be minimized by varying the sensing range and decreasing the number of messages being sent. Sensing energy can be optimized by reducing the repeated coverage target. In this paper, an Adaptive Sensor Sensing Range (ASSR) technique is proposed to maximize the WSN Lifetime. This work considers a sensor network with an adaptive sensing range that are randomly deployed in the monitoring area. The sensor is adaptive in nature and can be modified in order to save power while achieving maximum time of monitoring to increase the lifetime of WSN network. The objective of ASSR is to find the best sensing range for each sensor to cover all targets in the network, which yields maximize the time of monitoring of all targets and eliminating double sensing for the same target. Experiments were conducted using an NS3 simulator to verify our proposed technique. Results show that ASSR is capable to improve the network lifetime by 20% as compared to other recent techniques in the case of a small network while achieving an 8% improvement for the case of a large networks.
Cluster-based Target Tracking and Recovery Algorithm in Wireless Sensor NetworkIJASCSE
This document summarizes a research paper that proposes an energy efficient recovery technique for target tracking in wireless sensor networks. It begins with an introduction to target tracking in WSNs and the related challenges of energy efficiency and recovery when targets are lost. It then reviews existing target tracking and recovery techniques. The proposed technique uses dynamic clustering to predict target locations and only wakes clusters near the predicted path to save energy. The recovery mechanism has three steps: 1) the current cluster head announces a lost target, 2) it initiates recovery by waking nearby clusters to search predicted locations, and 3) once the target is found, only tracking clusters remain active while others sleep. The paper argues this approach reduces communication overhead and active clusters compared to existing
The document analyzes and compares the performance of two Medium Access Control (MAC) protocols for wireless sensor networks: Sensor MAC (S-MAC) and Hybrid MAC (H-MAC).
[1] S-MAC is a contention-based protocol that reduces energy waste from idle listening by implementing synchronized sleep and listen schedules. Nodes form virtual clusters to wake up and communicate at the same time. H-MAC improves on this with a slotted frame structure that dynamically allocates slots.
[2] The performance of the two protocols is evaluated based on end-to-end delay, packet delivery ratio, packet drop rate, and energy consumption using the NS2 simulation tool.
[3] Spatial correlation
WEIGHTED DYNAMIC DISTRIBUTED CLUSTERING PROTOCOL FOR HETEROGENEOUS WIRELESS S...ijwmn
This document describes a new clustering protocol called WDDC (Weighted Dynamic Distributed Clustering) for heterogeneous wireless sensor networks. WDDC selects cluster heads based on the ratio of a node's residual energy to the average network energy, and also considers the distance between nodes and the base station. WDDC divides the network lifetime into two zones and changes its behavior dynamically between the zones. Simulation results show WDDC outperforms other clustering protocols like SEP and DEEC in terms of energy efficiency and extending network lifetime.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and
packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which
ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer
from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of
sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads
in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption
and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer
and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers
reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
An Improved Energy Efficient Wireless Sensor Networks Through Clustering In C...Editor IJCATR
One of the major reason for performance degradation in Wireless sensor network is the overhead due to control packet and packet delivery degradation. Clustering in cross layer network operation is an efficient way manage control packet overhead and which ultimately improve the lifetime of a network. All these overheads are crucial in a scalable networks. But the clustering always suffer from the cluster head failure which need to be solved effectively in a large network. As the focus is to improve the average lifetime of sensor network the cluster head is selected based on the battery life of nodes. The cross-layer operation model optimize the overheads in multiple layer and ultimately the use of clustering will reduce the major overheads identified and their by the energy consumption and throughput of wireless sensor network is improved. The proposed model operates on two layers of network ie., Network Layer and Transport Layer and Clustering is applied in the network layer . The simulation result shows that the integration of two layers reduces the energy consumption and increases the throughput of the wireless sensor networks.
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.
Clustering provides an effective method for
extending the lifetime of a wireless sensor network. Current
clustering methods selecting cluster heads with more residual
energy, and rotating cluster heads periodically to distribute the
energy consumption among nodes in each cluster. However,
they rarely consider the hot spot problem in multi hop sensor
networks. When cluster heads forward their data to the base
station, the cluster heads closer to the base station are heavily
burdened with traffic and tend to die much faster. To mitigate
the hot spot problem, we propose a Novel Energy Efficient
Unequal Clustering Routing (NEEUC) protocol. It uses residual
energy and groupsthe nodesinto clusters of unequal layers
IRJET- Chaos based Secured Communication in Energy Efficient Wireless Sensor...IRJET Journal
This document proposes a chaotic encryption method combined with a clustered Low-Energy Adaptive Clustering Hierarchy (LEACH) algorithm to improve energy efficiency and security in wireless sensor networks. It discusses how LEACH clustering helps to reduce energy consumption through data aggregation at cluster heads. The proposed method uses chaotic maps for encryption to provide security. Simulation results show the combined approach increases network lifetime by reducing total energy consumption compared to traditional LEACH.
This document summarizes research on topology control techniques in wireless sensor networks. It first discusses how topology control aims to reduce energy consumption while maintaining network connectivity by regulating nodes' transmission power. It then reviews several existing topology control algorithms proposed in other papers. These algorithms distribute transmission power control to maximize network lifetime. Finally, the document concludes that many topology control algorithms have been developed to achieve energy efficient routing, but implementing them on real-world testbeds poses challenges.
Energy efficient data communication approach in wireless sensor networksijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based
configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor
node creates challenges for routing in WSNs. The research work presents the organized and detailed
description of energy conservation method for WSNs. In the proposed method reclustering and multihop
data transmission processes are utilized for data reporting to base station by sensor node. The accurate use
of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the
proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the
total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for
longer times inside the cluster. The result shows that the proposed clustering approach has higher stable
region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy
Adaptive Clustering Hierarchy (LEACH) for WSNs.
ENERGY EFFICIENT DATA COMMUNICATION APPROACH IN WIRELESS SENSOR NETWORKSijassn
Wireless sensor network has a vast variety of applications. The adoption of energy efficient cluster-based configuration has many untapped desirable benefits for the WSNs. The limitation of energy in a sensor node creates challenges for routing in WSNs. The research work presents the organized and detailed description of energy conservation method for WSNs. In the proposed method reclustering and multihop data transmission processes are utilized for data reporting to base station by sensor node. The accurate use of energy in WSNs is the main challenge for exploiting the network to the full extent. The main aim of the proposed method is that by evenly distributing the energy all over the sensor nodes and by reducing the total energy dissipation, the lifetime of the network is enhanced, so that the node will remain alive for longer times inside the cluster. The result shows that the proposed clustering approach has higher stable region and network life time than Topology-Controlled Adaptive Clustering (TCAC) and Low-Energy Adaptive Clustering Hierarchy (LEACH) for WSNs.
CBHRP: A Cluster Based Routing Protocol for Wireless Sensor NetworkCSEIJJournal
A new two layer hierarchical routing protocol called Cluster Based Hierarchical Routing Protocol
(CBHRP) is proposed in this paper. It is an extension of LEACH routing protocol. We introduce cluster
head-set idea for cluster-based routing where several clusters are formed with the deployed sensors to
collect information from target field. On rotation basis, a head-set member receives data from the neighbor
nodes and transmits the aggregated results to the distance base station. This protocol reduces energy
consumption quite significantly and prolongs the life time of sensor network. It is found that CBHRP
performs better than other well accepted hierarchical routing protocols like LEACH in term of energy
consumption and time requirement.
The document summarizes a research paper on an Energy Efficient Parallel LEACH Protocol for Underwater Wireless Sensor Networks. It proposes EEPLEACH, which improves on the popular LEACH protocol by implementing it in parallel across multiple CPU cores and GPUs. The paper presents the EEPLEACH algorithm and simulation results showing it improves network performance metrics like lifetime and reduces dead nodes compared to serial LEACH. Evaluation on dual-core through octa-core machines demonstrated faster execution times with more cores. The research contributes an energy-efficient routing protocol for underwater sensor networks that harnesses parallel processing.
The document summarizes a student's M. Tech thesis project on improving routing protocols in wireless sensor networks. It begins with an objective to develop a hybrid routing protocol combining features of PEGASIS and LEACH to increase network lifetime. It then reviews related work on routing protocols and energy efficiency. The proposed methodology describes a hybrid protocol that selects cluster heads probabilistically like LEACH while forming chains to route data like PEGASIS. Simulation results show the hybrid protocol increases network lifetime to over 2000 rounds compared to 2000 rounds for previous work. The conclusion is that lower cluster head election probabilities in the hybrid protocol extend network lifetime. Future work could analyze different network parameters.
EEIT2-F: energy-efficient aware IT2-fuzzy based clustering protocol in wirel...IJECEIAES
This document presents a new energy-efficient clustering protocol called EEIT2-F LEACH for wireless sensor networks. It uses an interval type-2 fuzzy inference system to select cluster heads, taking into account the residual energy, distance to the base station, and centrality of each node. The proposed protocol runs in set-up and steady-state phases similar to the LEACH protocol. In the set-up phase, cluster heads are selected based on the interval type-2 fuzzy logic system. Simulation results show that the new protocol outperforms existing approaches in terms of energy consumption and extending the network lifetime.
An energy-efficient cluster head selection in wireless sensor network using g...TELKOMNIKA JOURNAL
Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms.
Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Eff...CSCJournals
The objective of this paper is to develop a mechanism to increase the lifetime of homogeneous wireless sensor networks (WSNs) through minimizing long range communication, efficient data delivery and energy balancing. Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. To achieve energy balancing and maximizing network lifetime we divided the whole network into different clusters. In cluster based architecture, the role of aggregator node is very crucial because of extra processing and long range communication. Once the aggregator node becomes non functional, it affects the whole cluster. We introduced a candidate cluster head node on the basis of node density. We proposed a modified cluster based WSN architecture by introducing a server node (SN) that is rich in terms of resources. This server node (SN) takes the responsibility of transmitting data to the base station over longer distances from the cluster head. We proposed cluster head selection algorithm based on residual energy, distance, reliability and degree of mobility. The proposed method can save overall energy consumption and extend the lifetime of the sensor network and also addresses robustness against even/uneven node deployment.
1) The document proposes an NSGA-III based energy efficient clustering and tree-based routing protocol for wireless sensor networks.
2) It forms clusters based on remaining energy of nodes initially, then uses NSGA-III to improve inter-cluster data aggregation and select the shortest path between cluster heads and the sink.
3) Simulation results show the proposed protocol significantly improves network lifetime, throughput, and residual energy over other techniques.
A clustering protocol using multiple chainambitlick
This document proposes two schemes for clustering protocols based on chain routing in wireless sensor networks. It then describes in detail the Chain Routing Based on Coordinates-oriented Clustering Strategy (CRBCC) protocol. CRBCC forms balanced clusters based on node coordinates, constructs intra-cluster chains using simulated annealing, elects chain leaders, and then constructs an inter-cluster chain among leaders also using simulated annealing. Simulation results show CRBCC performs better than PEGASIS in terms of energy efficiency and network delay.
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
Similar to Neural network based energy efficient clustering and routing (20)
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Handling selfishness in replica allocationambitlick
The document discusses techniques for handling selfish nodes in replica allocation over mobile ad hoc networks. It aims to reduce traffic overhead while maintaining high data accessibility. The techniques include a selfish node detection algorithm that considers partial selfishness and novel replica allocation methods to address issues caused by selfish nodes hoarding replicas for their own benefit instead of sharing memory space. Simulations are used to evaluate the performance of these techniques in improving data delivery rates.
Mutual Distance Bounding Protocols enable entities to determine an upper bound on their physical distance and authenticate each other. They have been actively researched due to distance-based attacks on wireless systems like RFID. While most protocols provide unilateral authentication of a tag to a reader, one was proposed to provide mutual authentication with a lower false acceptance rate. However, this analysis is shown to overestimate security, as a new attack achieves a higher false acceptance rate. A method is also introduced to modify existing unilateral authentication protocols into mutual authentication protocols.
Moderated group authoring system for campus wide workgroupsambitlick
This paper describes a distributed authoring system for campus workgroups that allows group members to modify any document type using their own devices. Each member maintains an updatable copy of shared content, and read-only copies are distributed asynchronously based on wireless availability. Group members manually reconcile updates through moderation, merging changes from others into their copy. Over time, successive moderation converges all copies into a single version. An evaluation found the asynchronous update model effective and the moderation process intuitive for students.
Efficient spread spectrum communication without pre shared secretsambitlick
This document proposes a new mechanism called Time Reversed Message Extraction and Key Scheduling (TREKS) that allows for efficient spread spectrum communication without pre-shared secrets. TREKS is four orders of magnitude faster than previous solutions to this problem. It enables long-term spread spectrum communication with optimal energy costs, minimal storage overhead, and a computation cost at most twice traditional spread spectrum. The approach was evaluated through simulations and experiments sustaining 1Mbps communication spread over 100 Megachips per second using modest hardware.
The document lists 23 networking and mobile computing projects implemented in NS2. It includes projects on topics like mobility in wireless networks, intrusion detection, neighbor discovery, energy renewal with wireless power transfer, load balancing, and spectrum access control. Contact information is provided for those interested in the project reports, presentations, source code, or implementing new projects.
Adaptive weight factor estimation from user review 1ambitlick
This document proposes a novel technique called Adjacent Pair Priorities (APP) to estimate weight factors for quality of service parameters in vertical handoff decision algorithms. The APP technique allows users to set relative priority levels for adjacent pairs of QoS parameters in descending order using an exponential mapping. This adaptive approach controls the width of the weight distribution to provide flexibility for users. The document outlines the system requirements, block diagram, modules and references several research papers on vertical handoff decision schemes and network selection algorithms.
The document proposes an Integrated Institutional Portal that allows all colleges and institutions within a university or district to share information. [1] The portal would allow students and staff from different colleges to discuss and request information from one another through blogs, forums and by publishing notices. [2] Currently, each college maintains separate portals without a common forum for communication. [3] The proposed centralized portal managed by a super administrator would make all college information like results, events and departments accessible to benefit students and staff across institutions.
This document describes an Embassy Administration portal that aims to centralize and automate manual processes at a college. [1] The portal allows separate login access for staff, parents, students and other members of the college. [2] It displays student results, attendance, and performance for parents to view as well as enables communication between parents and faculty. [3] The system conducts model and unit examinations.
The document proposes a customer relationship management system (CRMS) to help space marketing executives, managers, and management interact and share information online. The existing CRMS is manual and DOS-based, which has disadvantages like a distributed database, obsolete technology, and low efficiency. The proposed system is a web-based online CRMS designed for the space marketing department. It allows monitoring executive calls, tracking performance, and sharing information among departments to improve customer relationships and business operations. The system has modules for corporate administration, regional management, center management, and executives to organize work and monitor progress at different levels.
Mutual Distance Bounding Protocols enable entities to determine an upper bound on their physical distance and authenticate each other. They have been actively researched due to distance-based attacks on wireless systems like RFID. While most protocols provide unilateral authentication of a tag to a reader, one was proposed to provide mutual authentication with a lower false acceptance rate. However, this analysis is shown to overestimate security, as a new attack achieves a higher false acceptance rate. A method is also introduced to modify existing unilateral authentication protocols into mutual authentication protocols.
Moderated group authoring system for campus wide workgroupsambitlick
This paper describes a distributed authoring system for campus workgroups that allows group members to modify any document type using their own devices. Each member maintains an updatable copy of shared content, and read-only copies are distributed based on wireless availability. Group members manually reconcile updates through moderation, merging changes from others into their copy. Over time, successive moderations converge the multiple versions into a single version. An evaluation found the asynchronous update propagation and moderation process intuitive for students.
Efficient spread spectrum communication without pre shared secretsambitlick
This document proposes a new mechanism called Time Reversed Message Extraction and Key Scheduling (TREKS) that allows for efficient spread spectrum communication without pre-shared secrets. TREKS is four orders of magnitude faster than previous solutions to this problem and enables long-term spread spectrum communication without establishing keys. It was evaluated through simulation and on a testbed and can sustain 1Mbps communication spread over a 100 Megachips bandwidth in real-time, with provably optimal energy cost and minimal storage overhead.
Comments on “mabs multicast authentication based on batch signature”ambitlick
This document summarizes and critiques the MABS-DSA protocol proposed by Zhou et al. for multicast authentication using batch verification. While MABS-DSA was intended to increase efficiency and security over other implementations, the author finds through reexamination of the arithmetic that the algorithm is actually incorrect and batch signature verification would fail almost always, even when individual packets were properly signed by an honest sender. The key issue is a flaw in protocol correctness rather than the intended security improvements.
Energy-Efficient Protocol for Deterministic and Probabilistic Coverage In Sen...ambitlick
The document proposes a new probabilistic coverage protocol (PCP) for sensor networks that can employ different sensing models. PCP aims to address the costly task of designing and testing different coverage protocols for each sensing model. It works with common disk sensing models as well as probabilistic sensing models with minimal changes. Simulation results show that PCP outperforms other deterministic and probabilistic protocols in terms of number of activated sensors, total energy consumed, and network lifetime while being robust against failures and inaccuracies.
Energy efficient protocol for deterministicambitlick
The document describes a new probabilistic coverage protocol (PCP) for sensor networks that can employ both deterministic and probabilistic sensing models. PCP works by activating sensors to construct an approximate triangular lattice over the monitored area. It is more energy efficient than previous protocols by reducing the number of activated sensors needed for coverage. Simulation results show PCP outperforms other protocols in terms of energy consumption and network lifetime while maintaining coverage under various conditions.
Estimating Parameters of Multiple Heterogeneous Target Objects Using Composit...ambitlick
This article proposes a method for estimating parameters of multiple heterogeneous target objects (objects with different sizes and shapes) using networked binary sensors. The sensors are simple and only report detections, but no individual sensor location is known. The method introduces "composite sensor nodes" containing multiple sensors in a fixed arrangement. This provides relative location information to help distinguish individual target objects. As an example, the article considers a composite node with two sensors on a line segment. Measures from these nodes can identify target shapes and estimate object parameters like radius and side lengths. Numerical tests demonstrate networked composite sensors can estimate parameters of multiple target objects.
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How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
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LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
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significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
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providing crucial environmental data for scientific, resource management, policy purposes, and
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and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
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these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
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In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
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বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
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তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
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A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
2. clusters in a wireless sensor network. Computation of the 3.2 Energy Model
optimal probability of becoming a cluster head was To ascertain the amount of energy consumed by a radio
presented. Moscibroda and Wattenhofer [13] defined the transceiver, we apply the following energy model. For
maximum cluster-lifetime problem, and they proposed each packet transmitted by a sending node to one or
distributed, randomized algorithms that approximate the more receivers in its neighborhood, the energy is
optimal solution to maximize the lifetime of dominating calculated as according to [7]:
sets on wireless sensor networks. Pemmaraju and e = et + ne r + ( N − n)e h r ………………………(1)
Pirwani []14 considered the k-domatic partition problem,
Where et and e r denote the amount of energy required
and they proposed three deterministic, distributed
algorithms for finding large k-domatic partitions. Tan to send and receive, n the number of nodes which should
and Korpeoglu [15] proposed two new algorithms under receive the packet, and N the total number of neighbors
the name PEDAP, which are near optimal minimum in the transmission range. e h r quantifies the amount of
spanning tree based wireless routing scheme. The energy required to decode only the packet header
performance of the PEDAP was compared with LEACH According to model described in [7], et and e r are
and PEGASIS, and showed a slightly better network defined as
lifetime than PEGASIS. Yi et. al[16] presents a Power
efficient and adaptive clustering protocol PEACH et (d , k ) = (e elect + e amp * d ρ )8k
………………..(2)
e r (k ) = e elect * 8k
3 Models, Routing Metric and Problem Formulation
for a distance d and a k byte message. We have
3.1 Network Model
We consider a network of homogeneous and energy- set e elect = 70nJ / bit , e amp = 120 pJ / bit / m 2 , d = 50m ,
constrained sensor nodes that are randomly deployed in a ρ=4
sensor field. Sensor nodes are initially powered by
batteries with full capacities. Each sensor collects data For a given header size n bytes, e h r would be
which are typically correlated with other sensors in its accordingly calculated.
vicinity, and then the correlated data is sent to the BS via
Cluster Head (CH) for evaluation or decision making 3.2 Routing Metric and Problem Formulation
purposes. We assume periodic sensing with the same A proper routing metric has to be chosen that can be used
period for all sensors. To facilitate the operation of the to decide the next hop for data transmission. This metric
network, we apply a novel clustering scheme that results always ensure the best shortest route and incurs the least
in selection of cluster. Inside each fixed cluster, a node is energy to transmit the packet from source to destination.
periodically elected to act as CH through which The cost of a link between two nodes S i and S j is equal
communication to/from cluster takes place. to the energy spent by these nodes to transmit and to
BS receive one data packet, successfully.
Source The metric chosen is Routing cost is calculated as
follows:
⎛ Ei D ⎞
R_C =⎜ ⎟ , ………..(3)
⎜ Et ( S i , S j ) + E r (S i , S j ) ⎟
⎝ ⎠
Where E i D is energy associated with the delivery ratio
of the packet originating from source node S i and
correctly received at destination node, while
E t ( S i , S j ) .is the energy used in transmitting from S i to
S j and E r ( S i , S j ) is the energy used in receiving the
packet. Data routing from every cluster head to the sink
is done over multi-hop paths, which is given by
Sensors
CH BS
minimizing equation (3)
Fig.1: Data Transmission in typical Sensor Networks 4 Proposed Solution
The solution for the energy aware routing problem is
proposed using an LP formulation. The objective of the
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3. LP is to select a number of nodes with higher levels of
residual energy to form an optimal route, while Output Layer
Elected
minimizing the total routing cost. Let us label the base- CH
station as node 0 and label the CH nodes as nodes 1 to n,
where n is the total number of CH sensor nodes. So the
Competition
problem reduces to Layer
Minimize ∑ R_C
1≤i ≤ n
Subject to following constraints
δ ( s, w 2 ) δ ( s, wm )
∑Dij −
1≤ j ≤ n
∑
D ji = bi ………….(4)
1≤ j ≤ n
δ ( s, w1 )
Dij ≥ 0 , 1 ≤ j ≤ n ………….….(5)
E ≤ Pmax imum ……………………(6)
Input Layer
Constraint (4) specifies the amount of data transmitted bi
between two nodes S i and S j , Constraint (5) specifies
amount of data to be transmitted from two nodes
S i and S j , Constraints (6) guarantees a minimum node Input Sensor node for election to be CH
lifetime and limits the maximum power consumption of
any node in the network. Fig.2: Selection of CH
The proposed protocol is divided into two phases namely Neural networks have solved a wide range of
as: setting up phase and energy aware routing and data problems and have good learning capabilities. Their
transmission phase. strengths include adaptation, ease of implementation,
parallelization, speed, and flexibility. A two - layer feed
4.1 Setup Phase forward neural network that implements the idea of
In this part, the initial cluster head selection and cluster competitive learning is depicted in Figure 2 above. The
formation algorithm are introduced , followed by the nodes in the input layer admit input patterns of sensor
energy aware routing. nodes competing for CH and are fully connected to the
output nodes in the competitive layer. Each output node
Cluster Head Election corresponds to a cluster and is associated with
To ensure balanced energy consumption among the weight W j , j = 1,2,...., m , where m is the number of
cluster head nodes throughout the network lifetime, clusters.
many clustering protocols favor uniformly distributed The neurons in the competitive layer then compete
clusters with stable average cluster sizes [7-11]. But we with each other, and only the one with the smallest
propose a new neural network based coverage aware
E i D value becomes activated or fired. Each neuron in the
clustering algorithm. The set of cluster head nodes can
be selected based on the cost metric defined in equation proposed algorithm for CH selection has an adaptive
3. The densely populated parts of the network will be learning. The learning rate μ determines the adaptation
overcrowded with cluster head nodes, while the scarcely of the vector towards the input pattern and is directly
covered areas will be left without any cluster head nodes. related to the convergence. If μ equals zero, there is no
In such a situation, it is likely that the high cost sensors learning. If μ is set to one, it will result in fast learning,
from poorly covered areas will have to perform
and the prototype vector is directly pointed to the input
expensive data transmissions to distant cluster head
pattern. For the other choices of μ , the new position of
nodes, further reducing their lifetime. There are three
layers in the proposed neural network: Input layer, the vector will be on the line between the old vector
Competition layer and Output Layer. value and the input pattern. Generally, the learning rate
could take a constant value or vary over time.
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4. routes, the sink node first generates a Route Discovery
1. Initialize the Vector S = {S1 , S 2 ,...., S m } of message that is broadcasted throughout the network.
sensor nodes competing for Cluster head. Upon receiving the broadcast message, each sensor node
//Processing at Input Layer introduces a delay proportional to its cost before it
2. Choose a winner k from sensor nodes as CH forwards the Route Discovery message to nodes in
range R . In this way a message arrives at each node
whose E i D is minimum as follows
along the desired minimum cost path. The cumulative
k = arg min{E i D } // Competition Layer cost of the routing path from the sink to the node
obtained in this phase is called the energy aware routing
3. Also E i D smallest Euclidean distance to BS i.e. cost of the node described in (3).
Ei D = k ∑| S
i =1, 2 ,...m
i − BS | , where k is proponality 1. Sort the paths p1 , p 2 ,....... p m according to
constant E i D as E i D1 < E i +1 D+11 < .......E m Dm
4.Update the value of weight vector as follows: 2. j = 1 // initialize the counter for available
paths.
w j (new) = w j (old ) + μ ( S i − w j (old )) , where 3. repeat and calculate E ≤ Pmax imum (Constraint 6)
μ is learning rate of the neurons. 0 ≤ μ ≤1 4. repeat
5. Repeat Steps (2-4) iteratively. 5.
6. Neuron with smallest value of E i D is E C ,m = ∑ m i E max L // E C ,m is use to
i =1, 2...m
winner.// Output Layer store the minimal energy consumption per bit with
m paths and is assigned maximum value initially.
Fig.3: Algorithm for Cluster head selection 6. R _ C = 0 // initialize the value of routing cost
4.2 Routing and Data Transmission 7. repeat
An algorithm for routing and data transmission is 8. Solve equation (3) and get the corresponding
proposed in Figure 5. optimal energy distribution with respect to
Let us denote by R the maximum number of routes that constraints defined in equations (4),(5),(6).
exist between each source-destination pair, and l indicate
by a route in R. Also, denote by pow( S i , l ) the power
9. Calculate E C ,m = Ei L∑
i =1, 2...m
consumed by node S i in transmitting to the next node on 10. Calculate the value of R _ C from equation (3)
route l . For the sake of simplicity, we assume that this and R _ C updated = R _ C // Update value of routing
parameter depends only on the distance between the cost
transmitting and the receiving node. Then, we associate
11. Until | R − C updated − R − C |< δ 1 (predefined
with each route l an energy cost routing metric defined
in equation (3) above. The proposed algorithm scan all threshold)
routes in R and determine the least expensive route to 12. Update the values of energy for each data
reach the BS. A source will select the route that has the transmission as E C ,m Updated = E C , m
least energy consumption or the one that maximizes the
network lifetime. Until | E C ,m Updated − E C ,m |< δ 2
13. j = j + 1 // Update the counter of the paths
14. Until m > Destination _ node
Source Destination
15. Compare all paths using R _ C metric and select
the smallest one.
16. Send the data across the multiple paths defined.
Fig. 4: Multipath Routing Fig. 5: Algorithm for Routing and Data Transmission
Route Update
The cluster head nodes send their data over multi-hop Given m available paths, the overall energy consumption
paths to the sink as shown in Figure 4. To obtain these per packet, E, can be written as
37
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5. E= ∑ E L , where E
i =1, 2...m
i i is the energy consumption for
one bit along path i and L is the packet length in bits. 100
Proposed
80 PEACH
5. Simulation and Results
Number of Alive Nodes
We have considered a stationary WSN of size 400×400 60
with a maximum transmission range of 50 m. The
message length is assumed to be 48 bytes, including an 40
12 byte packet header. The energy used to receive and
transmit data is modeled according to the energy model 20
presented in Section 3. Other sources of energy
consumption like sensing, processing, and idle listening 0
are neglected. MAC-layer behaviors such as contention, 1000 2000 3000 4000 5000
duty cycles, or packet buffering are not addressed. We Number of Rounds
have simulated the proposed scheme on ns-2[17]. Fig. 7: Number of alive nodes in PEACH and Proposed
Figure 6 presents the energy consumption of the Scheme
proposed scheme with well known PEACH clustering
protocol [16] when the maximum transmission range is 100
Proposed
60 m. The results demonstrate that the energy PEACH
consumption of proposed neural network based 90
clustering is smaller than PEACH. Percentage of alive Nodes
80
0.10
70
Proposed
PEACH
0.08 60
Mean Residual Energy
50
0.06
40
0.04 50 100 150 200 250 300
Number of Nodes
0.02 Fig. 8: Percentage of alive nodes in PEACH and
Proposed Scheme after 1500 rounds
0.00
1000 2000 The percentage of nodes alive and the mean of residual
3000 4000 5000
energy versus the number of nodes after 1500 rounds are
Number of Rounds
Fig.6: Mean residual Energy in PEACH and Proposed presented in Figures 8 and 9. Proposed scheme has
Scheme highest percentage of residual energy compared with
PEACH protocol. Also, the variation in the mean of
Figure 7 presents the number of nodes alive when residual energy of proposed scheme is smaller than
using clustering in proposed scheme and PEACH. This PEACH
result directly reflects the network lifetime of the
wireless sensor networks. In the case of networks using
PEACH with the maximum transmission range r = 60 m,
where a node runs out of energy occurs nearly after 4000
rounds, while in propped scheme there is a slight
improvement and node runs out of energy in nearly
4200 rounds.
.
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Authorized licensed use limited to: Bharat University. Downloaded on July 10,2010 at 18:41:30 UTC from IEEE Xplore. Restrictions apply.
6. [6]. J. Zhao, R. Govindan, Understanding packet
0.10
delivery performance in dense wireless sensor
Proposed networks, in: Proceedings of the 1st ACM
PEACH
International Conference on Embedded Networked
0.08
Sensor Systems, SENSYS, ACM Press, Los
Angeles, CA, USA, 2003.
Mean Residual Energy
0.06
[7]. W.R. Heinzelman, A. Chandrakasan, H.
Balakrishnan, Energyefficient communication
0.04 protocol for wireless microsensor networks, in:
Hawaii International Conferenceon System
0.02
Sciences (HICSS), 2000.
[8]. S. Lindsey, C. Raghavendra, K.M. Sivalingam,
Data gathering algorithms in sensor networks
0.00
50 100 150 200 250 300 using energy metrics, IEEE Transactions on
Number of Nodes Parallel and Distributed Systems, 13: 9, 924–935,
Fig. 9: Mean residual Energy in PEACH and Proposed Scheme 2002.
after 1500 rounds [9]. O. Younis, S. Fahmy, Heed: A hybrid, energy-
efficient, distributed clustering approach for ad
6. Conclusions hoc sensor networks, IEEE Transactions on
This paper has proposed a neural network based energy Mobile Computing, 3: 4, 366–379, 2004.
efficient routing and clustering protocol for WSNs. The [10]. C. Li, M. Ye, G. Chen, J. Wu, An energy-efficient
selection of CH is done using adaptive learning unequal clustering mechanism for wireless sensor
mechanism. Simulations results show that it performs networks, in: Proceedings of the 2nd IEEE
better than existing routing protocol PEACH in terms of International Conference on Mobile Ad-hoc and
residual energy and .number of alive nodes. So the Sensor Systems (MASS’05), 2005.
proposed scheme can be used in wide areas of sensor [11]. M. Demirbas, A. Arora, V. Mittal, Floc: A fast
networks where energy efficiency is a critical issue. local clustering service for wireless sensor
networks, in: Orkshop on Dependability Issues in
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