Particle Swarm Optimization-Based Routing Protocol for Clustered Heterogeneous Sensor Networks With Mobile Sink

Sudarmani, R.; Kumar, K.R. Shankar

doi:10.3844/ajassp.2013.259.269

Cited by 24 publications

(11 citation statements)

References 42 publications

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“…Also, we compare our proposed protocol to that of Sudarmani and Kumar [24]. The simulation results show that our model surpasses Sudarmani and Kumar's protocol.…”

Section: Related Workmentioning

confidence: 96%

“…We assume that the nodes are randomly deployed, immobile, and with non-rechargeable batteries. We consider our protocol as a variation of the LEACH protocol; therefore, we use it as a benchmark to our mode besides the performance of LEACH with Fuzzy Descriptors (Fuzzy-LEACH) by Nayak and Devulapalli [23] and clustered HSNs with mobile sink by using PSO proposed by Sudarmani and Kumar [24]. The simulation results show that our model outperforms both LEACH and Fuzzy-LEACH protocol and CHSN with mobile sink by using PSO.…”

Section: Ma-leach Modelmentioning

confidence: 99%

“…Sudarmani and Kumar [24] propose an approach to extend the network lifetime of CHSNs by mobilizing the sink. They optimize the path of mobile sink by using particle swarm optimization.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

MA-LEACH: Energy Efficient Routing Protocol for WSNs using Particle Swarm Optimization and Mobile Aggregator

Elsayed¹,

Sharaf²

2018

ijcna

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-Routing protocols for wireless sensor networks pay a great attention to the limited resources of the nodes. As battery lifetime is a major concern, we consider our proposed model as an effort to prolong the network lifetime in harmony with WSNs' constraints. In this paper, we study LEACH routing protocol and its performance and propose an extension to it, MA-LEACH. We introduce a mobile aggregator (MA) which is a gadget adopted to mitigate the overhead on the cluster heads (CHs). In addition, we optimize the trajectory using particle swarm optimization (PSO). Hence, we adapt the TSP problem to our protocol to determine the optimal trajectory that a mobile aggregator could travel to visit every cluster head in the network. We simulate the proposed protocol in MATLAB and the results reveal that it outperforms LEACH in network lifetime and energy consumption. Also, we compare our findings with a recent extension to the LEACH called LEACH with fuzzy descriptors and with clustered heterogeneous sensor networks (CHSNs) with a mobile sink. The simulation results show that MA-LEACH surpasses LEACH with fuzzy descriptor and CHSNs.

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“…Also, we compare our proposed protocol to that of Sudarmani and Kumar [24]. The simulation results show that our model surpasses Sudarmani and Kumar's protocol.…”

Section: Related Workmentioning

confidence: 96%

Section: Ma-leach Modelmentioning

confidence: 99%

See 1 more Smart Citation

MA-LEACH: Energy Efficient Routing Protocol for WSNs using Particle Swarm Optimization and Mobile Aggregator

Elsayed¹,

Sharaf²

2018

ijcna

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show abstract

“…We can get the target function y based on the truth table. The fitvalue is given by: fitvalue ¼ X 2 n 1 fitnumber i (8) where fitnumber i is the i th input combination of truth table suffice for the evolution circuit and n is the number of inputs. Figure 7 shows the flow of minimum energy (MINEN) [9] algorithm.…”

Section: Objective Function Design Of Gsomentioning

confidence: 99%

Intelligent Routing Mechanisms in IoT

Subhrahmanyam¹,

Ginimav²

2020

Intelligent System and Computing

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Wireless sensor networks (WSN) works on battery in order to communicate with each other. Energy consumption is the challenging issue in WSNs. In the recent few years, green communications have become a major concern in communication research and industries. Its major goal is to minimize the energy consumed by the nodes of the WSN. In order to save energy we need to switch off the extra components that are not in use during low traffic period. The technique where the unused extra components are switched off is called as sleep-scheduling, and the routing algorithm used to implement this is called as sleep-scheduling routing algorithm. In WSN the network is divided into multiple clusters. In each cluster one of the sensor nodes is elected as cluster head (CH) and other sensor nodes act as cluster members (CM). The cluster head collects the data form all the other nodes, removes the redundant data and transmits it to the destination. As the amount of workload is much more on the cluster head, the energy consumed by the cluster head is also more. Therefore to equalize the energy consumption among all the nodes, cluster head rotation is done. This chapter deals with different energy consumption techniques.1 workload is much more on the cluster head, the energy consumed by the cluster head is also more. Therefore to equalize the energy consumption among all the nodes, cluster head rotation is done. Energy consumption is the challenging issue in WSN. This chapter deals with different energy consumption techniques.

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“…Some of the techniques and methods that are used to design the proposed algorithm are discussed here to know how power is dynamically reconciled to meet the constraint of power depletion in nodes of the network. Sudarmani and Kumar (2013) have used a novel technique particle swarm optimization-based routing Protocol for clustered heterogeneous sensor networks with mobile sink. PSO is used to find the optimal path for mobile sink to collect data from cluster heads and the technique has lower energy consumption and improved lifetime over static sink.…”

Section: Related Workmentioning

confidence: 99%

Signed Graph Approach in Adaptive Transmission Power to Enhance the Lifetime of Wireless Sensor Networks

Karuppiah¹,

Rajaram²

2014

American Journal of Applied Sciences

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A Wireless Sensor Network (WSN) comprises a collection of sensor nodes networked for applications like surveillance, battlefield, monitoring of habitat. Nodes in a WSN are usually highly energy-constrained and expected to operate for long periods from limited on-board energy reserves. When a node transmits data to a destination node the data is overheard by the nodes that are in the coverage range of the transmitting node or the forwarding node. Due to this, the individual nodes might waste their energy in sensing data that are not destined to it and as a result the drain in the energy of the node is more resulting in much reduced network life time. As power is a limiting factor in a WSN, the major challenge in deploying a WSN is to enhance the network life time. So, it becomes inevitable to devise an efficient method of conserving the power. In this study, a novel algorithm, Signed Graph based Adaptive Transmission Power (SGATP) is developed to avoid redundancy in sensing the data thereby enhancing the life time of the network. The concept of adapting the transmission power based on the distance of the next neighbor is proposed while a node communicates with the Cluster Head during Intrusion Detection. The simulation results show that the average network life time is greatly improvised by 96.8% when the proposed method is adopted.

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Particle Swarm Optimization-Based Routing Protocol for Clustered Heterogeneous Sensor Networks With Mobile Sink

Cited by 24 publications

References 42 publications

MA-LEACH: Energy Efficient Routing Protocol for WSNs using Particle Swarm Optimization and Mobile Aggregator

MA-LEACH: Energy Efficient Routing Protocol for WSNs using Particle Swarm Optimization and Mobile Aggregator

Intelligent Routing Mechanisms in IoT

Signed Graph Approach in Adaptive Transmission Power to Enhance the Lifetime of Wireless Sensor Networks

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