High-Energy-First (HEF) Heuristic for Energy-Efficient Target Coverage Problem

Abstract

Target coverage problem in wireless sensor networks is concerned with maximizing the lifetime of the network while continuously monitoring a set of targets. A sensor covers targets which are within the sensing range. For a set of sensors and a set of targets, the sensor-target coverage relationship is assumed to be known. A sensor cover is a set of sensors that covers all the targets. The target coverage problem is to determine a set of sensor covers with maximum aggregated lifetime while constraining the life of each sensor by its initial battery life. The problem is proved to be NP-complete and heuristic algorithms to solve this problem are proposed. In the present study, we give a unified interpretation of earlier algorithms and propose a new and efficient algorithm. We show that all known algorithms are based on a common reasoning though they seem to be derived from different algorithmic paradigms. We also show that though some algorithms guarantee bound on the quality of the solution, this bound is not meaningful and not practical too. Our interpretation provides a better insight to the solution techniques. We propose a new greedy heuristic which prioritizes sensors on residual battery life. We show empirically that the proposed algorithm outperforms all other heuristics in terms of quality of solution. Our experimental study over a large set of randomly generated problem instances also reveals that a very naïve greedy approach yields solutions which is reasonably (appx. 10%) close to the actual optimal solutions.

Target Coverage and Network Connectivity Challenges in Wireless Sensor Networks

“…High-Energy-First (HEF) was proposed [14], it prioritizes the sensors based on the leftover energy. Here the target coverage problem is focused based on the scheduling mechanisms and adjustable sensing ranges.…”

“…Target Coverage based on scheduling algorithms and set cover approaches Now we compare various approaches, issues handled, and algorithm complexity based on the related works [1][2][3][4][5][6][7][8]. The comparison table is given in Table-2 and Table-3 summarizes related work done under set cover approaches [11][12][13][14][15][16][17][18][19][20][21][22][23]27]. In this division, we have made the comparative analysis of scheduling algorithms based on the three coverage types namely, probabilistic coverage, area coverage and target coverage based on the assessment done by the authors in their existing works.…”

Distributed lifetime coverage optimization protocol in wireless sensor networks

“…In distributed algorithms [33,29,22], information is disseminated throughout the network and sensors decide cooperatively by communicating with their neighbors which of them will remain in sleep mode for a certain period of time. The centralized algorithms [4,36,17] always provide nearly or close to optimal solution since the algorithm has global view of the whole network. But such a method has the disadvantage of requiring high communication costs, since the node (located at the base station) making the decision needs information from all the sensor nodes in the area and the amount of information can be huge.…”

“…These heuristics involve the construction of a cover set by including in priority the sensor nodes which cover critical targets, that is to say targets that are covered by the smallest number of sensors [3,36]. Other approaches are based on mathematical programming formulations [5,30,17,34] and dedicated techniques (solving with a branch-and-bound algorithms available in optimization solver). The problem is formulated as an optimization problem (maximization of the lifetime or number of cover sets) under target coverage and energy constraints.…”

Analysis of energy efficient connected target coverage algorithm for static and dynamic nodes in IWSNs

“…High energy first heuristic algorithm proposed to solve the target coverage problem [14]. HEF algorithm based on residual battery life of specific sensors.…”