Hybrid HSA and PSO algorithm for energy efficient cluster head selection in wireless sensor networks

Shankar, T.; Shanmugavel, S.; Rajesh, A.

doi:10.1016/j.swevo.2016.03.003

Cited by 161 publications

(84 citation statements)

References 28 publications

(35 reference statements)

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“…On the contrary, HSA and PSO-based CH selection [2] attains faster convergence with improvement in residual energy and throughput. However, it suffers from the requirement of more number of iterations to get the optimum value, the problem of poor convergence in refined search stage, and sometimes it gets trapped in the local search area.…”

Section: B Reviewmentioning

confidence: 99%

“…The investigational outcome has attained higher network lifetime along with the greatest throughput when compared to other existing algorithms. In 2016, Shankar et al [2] have proposed a hybrid model of 'Harmony Search Algorithm (HSA)' as well as 'Particle Swarm Optimization (PSO)' procedure for the efficient selection of cluster head. The model has attained global search with rapid convergence.…”

Section: A Related Workmentioning

confidence: 99%

“…Thus, there require additional protocols to solve all the above mentioned drawbacks. [2] HSA and PSO ❖ Faster convergence ❖ Improvement in residual energy and throughput ❖ Needs to maximize the iteration to get the optimal value ❖ Slow convergence in refined search stage ❖ Get trapped in local search area Mahajan et al [3] Cluster Chain Weight Metrics approach (CCWM)…”

Section: B Reviewmentioning

confidence: 99%

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Architectural analysis for lifetime maximization and energy efficiency in hybridized WSN model

Dattatraya¹,

Rao²,

Kumar³

2018

IJET

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It is well known that WSN is one of the leading techniques in granting pervasive computing for various applications regarding health sector and communication sector. However, the raising of issues in WSN is still a burden cause because of certain renowned terms like energy consumption and network lifetime extension. Clustering is a major contribution in any network and moreover Cluster Head selection is also a vital role since it is additively responsible in sending data to the base station, which means that Cluster Head directly makes its communication with base station. Day by day, the researches in cluster head selection get increased, but the requirements are not yet fulfilled. This paper proposes a energy efficient cluster head selection algorithm for maximizing the WSN lifetime. This paper develops a hybrid optimization process termed Group Search Ant Lion with Levy Flight (GAL-LF) for selecting the Cluster head in WSN. The proposed model is compared to the conventional models such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Group Search Optimization (GSO), Ant Lion Optimization (ALO) and Cuckoo Search (CS). The outcome of the simulation result shows the superiority of the proposed model by prolonging the lifetime of the network.

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Section: B Reviewmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

Section: B Reviewmentioning

confidence: 99%

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Architectural analysis for lifetime maximization and energy efficiency in hybridized WSN model

Dattatraya¹,

Rao²,

Kumar³

2018

IJET

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“…where qon, qoff represents probability of busy channel and idle channel respectively. Spectrum sensing performance is measured with the help detection probability qd, false alarm probability qf [24]. Probability of false alarm is the measure of spectrum holes which are misclassified as busy channel.…”

Section: Energy Efficiency Optimization Functionmentioning

confidence: 99%

Energy efficient spectrum sensing for cognitive radio network using artificial bee colony algorithm

Eappen

Shankar²

2018

IJET

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In this paper Artificial Bee Colony (ABC) algorithm based optimization of energy efficiency for spectrum sensing in a Cognitive Radio Network (CRN) is implemented. ABC algorithm which is an efficient optimization technique is used for optimizing energy efficiency function derived for cognitive users, where energy efficiency function is derived as the dependency on spectrum sensing time and the transmission power. Energy efficiency optimized by ABC is compared with Particle Swarm Optimization (PSO) based technique. Simulation results shows that with ABC it is able to achieve more energy efficient spectrum sensing as compared to PSO optimized with a margin of 33% efficiency over PSO.

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“…e protocol presented in [32] utilizes PSO for cluster head selection taking residual energy, intracluster distance, and node degree as fitness function. A hybrid centralized protocol combining harmony search algorithm (HSA) and PSO is also used for clustering in sensor networks [33]. Bee colony metaheuristic achieved success in resolving the clustering problem in WSNs [34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

A Proficient Bee Colony-Clustering Protocol to Prolong Lifetime of Wireless Sensor Networks

Pathak¹

2020

Journal of Computer Networks and Communications

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In wireless sensor network, replacement of node’s battery is very tough task in hostile environments. Therefore, to maximize network lifetime is the ultimate solution. Dividing the sensing region of wireless sensor network into clusters is an excellent approach to gain high energy efficiency and to enhance lifetime of the network. On the other hand, heads of the cluster need additional energy because of additional work such as obtaining data from its member nodes, aggregation of their data, and finally sending it to the base station. To enhance the lifetime of these networks, proper selection of heads plays a vital role. In this paper, we propose proficient bee colony-clustering protocol (PBC-CP) which is based on artificial bee colony algorithm. In PBC-CP approach, we have taken important factors for selection of heads such as node’s energy, degree of node, and distance from base station to node. For transmitting the data from cluster head to base station, it chooses the energy-efficient path which further minimizes the energy consumption of sensor network. Simulation experiments show the effectiveness of our proposed approach.

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Hybrid HSA and PSO algorithm for energy efficient cluster head selection in wireless sensor networks

Cited by 161 publications

References 28 publications

Architectural analysis for lifetime maximization and energy efficiency in hybridized WSN model

Architectural analysis for lifetime maximization and energy efficiency in hybridized WSN model

Energy efficient spectrum sensing for cognitive radio network using artificial bee colony algorithm

A Proficient Bee Colony-Clustering Protocol to Prolong Lifetime of Wireless Sensor Networks

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