Dominating Set Algorithms for Wireless Sensor Networks Survivability | Zendy

Tayler Pino | Zendy; Salimur Choudhury | Zendy; Fadi Al-Turjman | Zendy

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Dominating Set Algorithms for Wireless Sensor Networks Survivability

Author(s) -

Tayler Pino,

Salimur Choudhury,

Fadi Al-Turjman

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2819083

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Limited energy of the sensors is one of the key issues towards realizing a reliable wireless sensor network (WSN), which can survive under the emerging WSN applications. A promising method for conserving the energy of these sensors can be implemented by applying a sleep-wake scheduling while distributing the data gathering and sensing tasks to a dominating set of awake sensors while the other nodes are in a sleep mode. Producing the maximum possible number of such disjoint dominating sets, called the domatic partition problem in unit disk graphs, can further prolong the network lifetime. This problem becomes challenging when the initial energy of the nodes varies from one to another. In this paper, we introduce multiple local search algorithms that can improve the total lifetime of WSNs consisting of nodes with varying initial energy. We discuss the performance of the existing dominating set algorithm and introduce three more algorithms which can be applied on multiple disjoint dominating sets with nodes having varying initial energy. We discuss the efficiency of each of the algorithms through extensive simulations.

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