A survey of clustering schemes for mobile ad hoc networks

Yu, Jiale; Chong, J. Michael

doi:10.1109/comst.2005.1423333

Cited by 721 publications

(439 citation statements)

References 27 publications

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“…Thus, clustering operation may consume a large portion of network bandwidth, drain mobile nodes' energy quickly, and override its improvement on network scalability and performance [13]. By limiting re-clustering situations or minimizing explicit control messages for clustering, the cluster structure can be maintained well without excessive consumption of network resources [17].…”

Section: Cluster Maintenance Algorithmmentioning

confidence: 99%

“…In addition, neither LID nor HD algorithm take into account mobility metrics, i.e. highly mobile nodes are equally likely to be elected as CHs, although their movement away from their attached cluster members may soon lead to a ripple re-clustering effect [17]. Most importantly, LID, HD and VC do not cater for separating cluster maintenance phase, i.e.…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…Also, article [2] does not clarify how MHs re-affiliation takes place, i.e. the process for the detachment of a MH from its current CH and the attachment to another [17].…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…enhance clusters stability). We have chosen not to include a node degree metric, as this has been shown to negatively affect cluster stability [6][8] [17]. LIDAR's execution involves the following steps:…”

Section: Cluster Formation Algorithmmentioning

confidence: 99%

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Stable and Energy Efficient Clustering of Wireless Ad-Hoc Networks with LIDAR Algorithm

Gavalas

Pantziou

Konstantopoulos

et al. 2006

Personal Wireless Communications

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Abstract. The main objective of clustering in mobile ad-hoc network environments is to identify suitable node representatives, i.e. cluster heads (CHs) to store routing and topology information; CHs should be elected so as to maximize clusters stability, that is to prevent frequent cluster re-structuring. A popular clustering algorithm (LID) suggests CH election based on node IDs (nodes with locally lowest ID value become CHs). Although fast and simple, this method is biased against nodes with low IDs, which are likely to serve as CHs for long periods and are therefore prone to rapid battery exhaustion. Herein, we propose LIDAR, a novel clustering method which represents a major improvement over traditional LID algorithm: node IDs are periodically re-assigned so that nodes with low mobility rate and high energy capacity are assigned low ID values and, therefore, are likely to serve as CHs. Our protocol also greatly reduces control traffic volume of existing algorithms during clustering maintenance phase, while not risking the energy availability of CHs. Simulation results demonstrate the efficiency, scalability and stability of our protocol against alternative approaches.

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Section: Cluster Maintenance Algorithmmentioning

confidence: 99%

Section: Related Work and Motivationmentioning

confidence: 99%

“…Also, article [2] does not clarify how MHs re-affiliation takes place, i.e. the process for the detachment of a MH from its current CH and the attachment to another [17].…”

Section: Related Work and Motivationmentioning

confidence: 99%

Section: Cluster Formation Algorithmmentioning

confidence: 99%

See 2 more Smart Citations

Stable and Energy Efficient Clustering of Wireless Ad-Hoc Networks with LIDAR Algorithm

Gavalas

Pantziou

Konstantopoulos

et al. 2006

Personal Wireless Communications

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show abstract

“…They sense data and forwarded it to the CH in their cluster who in turn sends it to a base station for processing. The main advantage behind clustering [9] is to make only the cluster head communicate with the base station, which allows to the remaining nodes to preserve their energy by switching to sleep mode. This minimizes the number of transmissions as well as the non-needed replicated data.…”

Section: Introductionmentioning

confidence: 99%

MUCH: Multi-Criteria Cluster Head Delegation Based on Fuzzy Logic

Ghosn¹,

Ghaddar²

2017

International Journal of Advanced Research in Computer and Comm

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WSNs are composed of limited-power sensors. Replacing or recharging sensors, especially when deployed in places where human intervention is risky, is an important challenge. Therefore, and since communication is the major energy consuming operation [1], ensuring an energy efficient usage is a major concern. Clustering is one of the techniques used for this purpose [2]. It decreases the number of sensors which take part in transmission thereby assist in power consumption [3]. The sensors are organized into clusters. Each Cluster has a Cluster Head (CH) to which only other cluster members send data. CHs gather information and send it to a base station for processing. We propose an method for CH selection based on multiple criteria (distance to base station, distance to cluster members, energy cost and number of rounds) using fuzzy logic. Simulation results show that MUCH decreases the energy consumption comparing to LEACH thus increases the network lifetime.

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Ad Hoc Wireless Networks

Tonguz¹

2006

217

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A survey of clustering schemes for mobile ad hoc networks

Cited by 721 publications

References 27 publications

Stable and Energy Efficient Clustering of Wireless Ad-Hoc Networks with LIDAR Algorithm

Stable and Energy Efficient Clustering of Wireless Ad-Hoc Networks with LIDAR Algorithm

MUCH: Multi-Criteria Cluster Head Delegation Based on Fuzzy Logic

Ad Hoc Wireless Networks

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