Clustering energy-efficient transmission protocol for Wireless Sensor Networks based on ant colony path optimization

Chen, Huahongzi; Lv, Ze; Tang, Ruichun; Tao, Ye

doi:10.1109/cits.2017.8035280

Cited by 10 publications

(8 citation statements)

References 7 publications

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“…Clustering Energy-Efficient Transmission Protocol (CEETP) for WSNs was proposed by Chen et al [17] on the basis of Ant Colony Path Optimization (CEETP-ACPO). Initially, the Distributed Cluster Computing Energy-Efficient Routing Scheme (DCCERS) is employed toward CHs based on centre of gravity and node energy in the available range of nodes, and then there is a clustering of SNs.…”

Section: Related Workmentioning

confidence: 99%

Optimized cluster head selection using krill herd algorithm for wireless sensor network

Karthick

Palanisamy²

2019

Automatika

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Wireless Sensor Network (WSNs) can perform transmission within themselves and examination is performed based on their range of frequency. It is quite difficult to recharge devises under adverse conditions. The main limitations are area of coverage, network's lifetime and aggregating and scheduling. If the lifetime of a network should be prolonged, then it can become a success along with reliability of the data transferred, conservation of sensor and scalability. Through many research works, this challenge can be overcome which are being proposed and the network's lifespan improved which can preserve the sensor's energy. By schemes of clustering, a low overhead is provided and the resources are efficiently allocated thus increasing the ultimate consumption of energy and reducing interfaces within the sensor nodes. Challenges such as node deployment and energy-aware clustering can be considered as issues of optimization with regards to WSNs, along with data collection. An optimal solution can be gotten through evolutionary and SI algorithm, pertaining to Non-deterministic Polynomial (NP)-complete along with a number of techniques. In this work, Krill Herd Algorithm based clustering is proposed.

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Section: Related Workmentioning

confidence: 99%

Optimized cluster head selection using krill herd algorithm for wireless sensor network

Karthick

Palanisamy²

2019

Automatika

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“…Various cluster-based only solutions have been proposed to explicitly address these problems in WSNs [27][28][29][30][31]. To increase energy efficiency, an additional technique, essentially physical topology oriented such as power control or scheduling, is used [20,[32][33][34][35]. However, such hybrid solutions are usually confined to the construction of 1-hop clusters.…”

Section: Related Workmentioning

confidence: 99%

Self‐stabilising hybrid connectivity control protocol for WSNs

Diédié

Aka

Michel

2019

IET wirel. sens. syst.

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In this study, the authors address the problem of combining hierarchical and flat techniques to construct and maintain nodes' connectivity as well as links' symmetry (bidirectionality) in a wireless sensor network (WSN) comprising static nodes. They propose a localised and asynchronous self-stabilising hybrid message passing a solution that seamlessly merges three well known connectivity control techniques for such ad hoc networks, namely k-hop clustering (k ≥ 1), power control (transmission range adjustment) and sleep/wake scheduling. Their stigmergy-based strategy (i.e. inspired from ants' pheromone-based communication, division of labour and swarming behaviours) allows a WSN to simultaneously cope with issues such as scalability, fault tolerance, transmission range minimisation, energy hole problem (i.e. premature node deaths in the vicinity of the sink), channel overhearing and signalisation reduction. To the best of their knowledge, such a solution does not exist in the literature. The few self-stabilising hybrid connectivity control protocols currently proposed use only two of the above-mentioned techniques. The authors formally prove the correctness of their scheme and its self-stabilisation property under an unfair distributed daemon. Simulation results show that the proposed scheme has a low average convergence time, is energy efficient and can prolong network lifetime.

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“…An ant colony path optimization-based clustering energy-efficient transmission protocol (CEETP-ACPO) is proposed [23]. In this protocol, the cluster heads are selected using a distributed algorithm and the optimized path is based on ant colony optimization algorithm.…”

Section: Distributed Approachesmentioning

confidence: 99%

RARZ: Ring-Zone Based Routing Protocol for Wireless Sensor Networks

et al. 2018

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Sensor networks are handicapped by limited resources in the form of energy, processing, and memory. This paper proposes a new multi-hop energy efficient protocol, namely a routing algorithm using the ring-zone (RARZ) model. The protocol is lightweight, takes routing decisions based on the remaining energy of nodes, and performs location-based routing without the need for the nodes to know their respective positions. The protocol partitions the network into concentric rings around the base station. Each node assigns itself to a particular ring, known by a ringID. Multi-hop routing is performed and nodes within inner rings carry data for the outer rings towards the base station. Simulation results show that RARZ outperforms the address-light integrated MAC routing protocol (AIMRP), ad hoc on-demand distance vector (AODV) and Flooding in terms of end-to-end delay, average hop count, and energy consumption.

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Clustering energy-efficient transmission protocol for Wireless Sensor Networks based on ant colony path optimization

Cited by 10 publications

References 7 publications

Optimized cluster head selection using krill herd algorithm for wireless sensor network

Optimized cluster head selection using krill herd algorithm for wireless sensor network

Self‐stabilising hybrid connectivity control protocol for WSNs

RARZ: Ring-Zone Based Routing Protocol for Wireless Sensor Networks

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