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Journal ArticleDOI

Cluster head selection for energy efficient and delay-less routing in wireless sensor network

Amit Sarkar, +1 more
- 01 Jan 2019 - 
- Vol. 25, Iss: 1, pp 303-320
TLDR
Firefly with cyclic randomization is proposed for selecting the best cluster head for wireless sensor network and the network performance is increased in this method when compared to the other conventional algorithms.
Abstract
Wireless sensor network (WSN) is comprised of tiny, cheap and power-efficient sensor nodes which effectively transmit data to the base station. The main challenge of WSN is the distance, energy and time delay. The power resource of the sensor node is a non-rechargeable battery. Here the greater the distance between the nodes, higher the energy consumption. For having the effective transmission of data with less energy, the cluster-head approach is used. It is well known that the time delay is directly proportional to the distance between the nodes and the base station. The cluster head is selected in such a way that it is spatially closer enough to the base station as well as the sensor nodes. So, the time delay can be substantially reduced. This, in turn, the transmission speed of the data packets can be increased. Firefly algorithm is developed for maximizing the energy efficiency of network and lifetime of nodes by selecting the cluster head optimally. In this paper firefly with cyclic randomization is proposed for selecting the best cluster head. The network performance is increased in this method when compared to the other conventional algorithms.

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Citations
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Journal ArticleDOI

A novel dynamic clustering approach for energy hole mitigation in Internet of Things-based wireless sensor network

TL;DR: The dynamic and energy‐efficient clustering for energy hole mitigation (DECEM) is proposed and the simulation experiments reveal that DECEM has enhanced stability period by 5% and 31% as compared to the MEEC and IDHR protocols, respectively.
Journal ArticleDOI

Energy efficient protocol in wireless sensor network: optimized cluster head selection model

TL;DR: A new hybrid algorithm is proposed that hybridizes the concept of dragon fly and firefly algorithm algorithms, termed fire fly replaced position update in dragonfly, to develop a new clustering model with optimal cluster head selection by considering four major criteria like energy, delay, distance, and security.
Journal ArticleDOI

A Survey of Routing Protocols in WBAN for Healthcare Applications.

TL;DR: This paper briefly introduces WBAN, focuses on the analysis of the routing protocol, classify, and compare the advantages and disadvantages of various routing protocols, and puts forward some problems and suggestions which provides ideas for the follow-up routing design.
Journal ArticleDOI

An Energy Efficient Routing Protocol Based on Improved Artificial Bee Colony Algorithm for Wireless Sensor Networks

TL;DR: A clustering algorithm that selects cluster heads using an improved artificial bee colony (ABC) algorithm and an energy-efficient routing algorithm based on an improved ant colony optimization for routing between the cluster heads and the base station are proposed.
Journal ArticleDOI

Routing in Wireless Sensor Networks Using Optimization Techniques: A Survey

TL;DR: This article looks into the details of routing in WSN using different optimization techniques and provides the future insight for researchers to fill in existing gaps in the WSN research field and to find new research trends in this area.
References
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Journal ArticleDOI

An application-specific protocol architecture for wireless microsensor networks

TL;DR: This work develops and analyzes low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality.
Proceedings ArticleDOI

Sensor deployment and target localization based on virtual forces

TL;DR: A virtual force algorithm (VFA) is proposed as a sensor deployment strategy to enhance the coverage after an initial random placement of sensors to improve the coverage of cluster-based distributed sensor networks.
Journal ArticleDOI

A comprehensive review of firefly algorithms

TL;DR: The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice as mentioned in this paper, and many problems from various areas have been successfully solved using the Firefly algorithm and its variants.
Proceedings ArticleDOI

Constrained coverage for mobile sensor networks

TL;DR: In this article, the authors consider the problem of self-deployment of a mobile sensor network and propose an algorithm based on artificial potential fields which is distributed, scalable and does not require a prior map of the environment.
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