Abstract
Wireless sensor networks (WSNs) deployed in harsh and unfavorable environments become inoperable because of the failure of multiple sensor nodes. This results into the division of WSNs into small disjoint networks and causes stoppage of the transmission to the sink node. Furthermore, the internodal collaboration among sensor nodes also gets disturbed. Internodal connectivity is essential for the usefulness of WSNs. The arrangement of this connectivity could be setup at the time of network startup. If multiple sensor nodes fail, the tasks assigned to those nodes cannot be performed; hence, the objective of such WSNs will be compromised. Recently, different techniques for repositioning of sensor nodes to recover the connectivity have been proposed. Although capable to restore connectivity, these techniques do not focus on the coverage loss. The objective of this research is to provide a solution for both coverage and connectivity via an integrated approach. A novel technique to reposition neighbouring nodes for multinode failure is introduced. In this technique, neighbouring nodes of the failed nodes relocate themselves one by one and come back to their original location after some allocated time. Hence, it restores both prefailure connectivity and coverage. The simulations show our proposed technique outperforms other baseline techniques.
Highlights
Wireless sensor networks (WSNs) gained global attention in the present times. e building block of WSNs is a sensor node. ese sensors nodes can measure, gather, and sense the information from the external environment. is information can be used for decision making by the end users. ere are various areas of interests for WSNs applications; for example, military surveillance and target tracking, providing relief in a natural disaster, monitoring biomedical health, and exploration of the hazardous environment and seismic sensing [1, 2].e sensing nodes in WSNs have low power, memory, and computational and radio capabilities
In [23], HRSRT for restoration of connectivity is recommended for impaired WSNs. e realistic terrain influence of area of interest (AOI) is considered in this algorithm. e terrain is planned by plotting the AOI and dividing it into a grid of cells of equal size
A comparison is made between the proposed algorithm with and increased robustness against recurrent failure (RIR) of damaged WSN topologies in the event of multiple node failures [25] and autonomous repair (AuR) [26] protocols. is section presents niceties of the simulation setup and the discussion of the results
Summary
WSNs gained global attention in the present times. e building block of WSNs is a sensor node. ese sensors nodes can measure, gather, and sense the information from the external environment. is information can be used for decision making by the end users. ere are various areas of interests for WSNs applications; for example, military surveillance and target tracking, providing relief in a natural disaster, monitoring biomedical health, and exploration of the hazardous environment and seismic sensing [1, 2]. E first approach suggests that to restore connectivity, the topology of the network may be rearranged by repositioning sensor nodes from the original positions of the WSN. A node’s individual travelling distance and coverage loss caused by multinode failure were minimized by the optimization-based ILP that formed the connected topology In this technique, the position of the node is assumed prior to the failure in WSNs. In [8], a technique grounded on the network flow transportation model is used where normally every single node should have the capability to go to each destination of WSNs. Here, the problem was solved by the polygon approximation model and the formulation of mixed-integer approach. Is extended technique was known as RAM (recovery algorithm to handle multiple failures) and selected critical sensors and designated backup for these nodes.
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