Poly: A reliable and energy efficient topology control protocol for wireless sensor networks

Qureshi, Hassaan Khaliq; Rizvi, Sajjad; Saleem, Muhammad; Khayam, Syed Ali; Rakocevic, Veselin; Rajarajan, Muttukrishnan

doi:10.1016/j.comcom.2010.12.016

Cited by 28 publications

(14 citation statements)

References 12 publications

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“…However, the topology maintenance phase may require repeated topology reconstruction, which increases energy overhead. Energy overhead is defined as the fraction of the network energy expended on topology construction [23]. In the case of topology maintenance, this metric calculates the overhead during topology reconstruction under appropriate conditions.…”

Section: Performance Evaluationmentioning

confidence: 99%

Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks

Lee

Yang

2012

International Journal of Distributed Sensor Networks

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Because machine-to-machine (M2M) technology enables machines to communicate with each other without human intervention, it could play a big role in sensor network systems. Through wireless sensor network (WSN) gateways, various information can be collected by sensors for M2M systems. For home M2M networks, this study proposes a distributed energy-efficient topology control algorithm for both topology construction and topology maintenance. Topology control is an effective method of enhancing energy efficiency and prolonging network lifetime. During the topology construction phase, each node builds a new topology based on the best parent node. Nodes can extend the network lifetime by adjusting transmission power to control the topology. In the topology maintenance phase, each node monitors the energy status of neighbors and triggers topology construction as needed. By balancing energy consumption, topology maintenance also avoids the hot spot problem. Simulation results confirm the superior performance of the proposed algorithm for distributed energy-efficient topology control (DETC) in terms of energy efficiency and network lifetime in home M2M networks.

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Section: Performance Evaluationmentioning

confidence: 99%

Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks

Lee

Yang

2012

International Journal of Distributed Sensor Networks

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“…The algorithm is based on growing-tree technique and selects active nodes which are at the farthest distance from the parent based on the signal strength and remaining energy. This allows fewer nodes to be selected in the CDS tree which in turn leads to an overhead of long distance communication [20].…”

Section: Related Workmentioning

confidence: 99%

“…Any node can initiate the discovery process and does not require any pre-defined node (e.g. the sink node) to initiate the process as in [1], [20]. The neighbour lists are stored by each node after the discovery process and will be used for cluster head election.…”

Section: B Dynamic Dominating Set Constructionmentioning

confidence: 99%

Energy-Efficient Dynamic Dominating Set Construction in Wireless Sensor Networks

Dahnil¹,

Singh²,

Ho³

2012

IJCEE

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Abstract-Clustering and topology control are two well-known techniques to improve network lifetime in Wireless Sensor Networks. This paper proposes a hybrid approach combining both techniques to construct a dominating set that aims to minimize energy consumption by abandoning long-distance communication. A transmission power control strategy is proposed to establish connection for all nodes so as to communicate in one hop to their cluster heads and consequently reducing the energy consumption. Topology control along with a clustering technique elects cluster heads to form a dominating set. The proposed hybrid approach constructs a dynamic dominating set based on energy and coverage metrics with low computational complexity and significant reduction in the amount of message overhead required for dominating set construction. Simulation results show that the set of elected cluster heads is a dominating set constructed dynamically on every round having optimal one-hop cluster.

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“…f Final topology, tree cycles of size three, denoting redundant paths three clique set. The topology construction phase of Poly3 is similar to Poly [8] except for the last step in which instead of a single polygon, multiple cliques of size three are retained.…”

Section: Topology Constructionmentioning

confidence: 99%

Adding the Reliability on Tree Based Topology Construction Algorithms for Wireless Sensor Networks

Fiaz

Yousaf

Hanfi

et al. 2013

Wireless Pers Commun

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract Topology control is a technique used in wireless sensor networks to maximize energy efficiency and network lifetime. In previous literature, many tree based techniques have been proposed to save energy and increase the network lifetime. In tree based algorithms, the most promising solution is the formation of a network backbone, which serves on behalf of rest of the nodes in the network and therefore leading towards Connected Dominating Set (CDS) formulation. However, one imminent problem with all tree based solution is a compromise on network reliability. Therefore, to address reliability issues in tree based solutions, in this paper, we propose Poly3 which maintains cliques of size three in order to achieve network reliability on top of the CDS algorithm. This makes the network more robust to link removal. Our empirical and mathematical analysis reveals that Poly3 provides better reliability than algorithms of the same kind. Permanent repository link

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Poly: A reliable and energy efficient topology control protocol for wireless sensor networks

Cited by 28 publications

References 12 publications

Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks

Distributed Energy-Efficient Topology Control Algorithm in Home M2M Networks

Energy-Efficient Dynamic Dominating Set Construction in Wireless Sensor Networks

Adding the Reliability on Tree Based Topology Construction Algorithms for Wireless Sensor Networks

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