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Clustering in sensor networks: A literature survey
Afsar, M. Mehdi ; Tayarani-N, Mohammad-H.
Journal of network and computer applications, 2014-11, Vol.46, p.198-226
[Periódico revisado por pares]
Kidlington: Elsevier Ltd
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Título:
Clustering in sensor networks: A literature survey
Autor:
Afsar, M. Mehdi
;
Tayarani-N, Mohammad-H.
Assuntos:
Applied sciences
;
Cluster-head
;
Clustering
;
Computer science
;
control theory
;
systems
;
Computer systems and distributed systems. User interface
;
Computer systems performance. Reliability
;
Data processing. List processing. Character string processing
;
Energy-efficiency
;
Exact sciences and technology
;
Hierarchical
architecture
;
Memory organisation. Data processing
;
Radiocommunications
;
Software
;
Telecommunications
;
Telecommunications and information theory
;
Wireless sensor networks
É parte de:
Journal of network and computer applications, 2014-11, Vol.46, p.198-226
Descrição:
Wireless sensor networks (WSNs) have recently gained the attention of researchers in many challenging aspects. The most important challenge in these networks is energy conservation. One of the most popular solutions in making WSNs energy-efficient is to cluster the networks. In clustering, the nodes are divided into some clusters and then some nodes, called cluster-heads, are selected to be the head of each cluster. In a typical clustered WSN, the regular nodes sense the field and send their data to the cluster-head, then, after gathering and aggregating the data, the cluster-head transmits them to the base station. Clustering the nodes in WSNs has many benefits, including scalability, energy-efficiency, and reducing routing delay. In this paper we present a state-of-the-art and comprehensive survey on clustering approaches. We first begin with the objectives of clustering, clustering characteristics, and then present a classification on the clustering algorithms in WSNs. Some of the clustering objectives considered in this paper include scalability, fault-tolerance, data aggregation/fusion, increased connectivity, load balancing, and collision avoidance. Then, we survey the proposed approaches in the past few years in a classified manner and compare them based on different metrics such as mobility, cluster count, cluster size, and algorithm complexity.
Editor:
Kidlington: Elsevier Ltd
Idioma:
Inglês
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