Maximizing continuous barrier coverage in energy harvesting sensor networks

Abstract

The lifetime of wireless sensor networks (WSNs) has been studied extensively. Lifetime is application specific, and long lifetime is desirable in general. In barrier coverage, it is desirable to have a large number of barriers active as well. Energy harvesting is an active research area in WSNs. In this paper we study the barrier coverage problem in energy harvesting WSNs. We develop an algorithm that finds a repeating sleep/wakeup schedule that can provide the continuous operation of the maximum number of barriers in an energy harvesting WSN. I. INTRODUCTIONThe lifetime of wireless sensor networks (WSNs) has been studied extensively [4]. Long lifetime is desirable. For instance, it can make the deployment of a network along a difficult border much less cost-prohibitive as it would reduce the need for frequent maintenance. However, network lifetime is application specific and thus necessitates individual study for different applications.One WSN application is detection of intruders for infrastructure protection and border control. For this application, barriers made of sensors are set up to detect intruders' crossing of the barriers. The k-barrier coverage problem is to set up k disjoint barriers in a wireless sensor network with an objective of achieving the longest operation time [12], [13]. The network lifetime for k-barrier coverage is the longest time of having k operational disjoint barriers. The parameter k has a large impact on the quality of the barrier coverage: the larger the k, the more robust the barrier coverage.Harvesting energy in WSNs has become an active research area [2], [6], [8], [9], [14], [17], [16]. A recent survey on energy harvesting in sensor networks [17] observes that "energy harvesting techniques have the potential to address the trade off between performance parameters and lifetime of sensor nodes." It is obvious by looking at the harvesting and sensing costs [16] that a naive approach to barrier coverage will not work. In a network that gathers energy with vibrational sensors harvesting at most .1mW that also employs light sensors using 1.155mW , it is not hard to see that such a network cannot be powered indefinitely in a barrier coverage application. Energy harvesting rates are much lower than energy consuming rates in sensor nodes. With energy harvesting techniques, there is still research to be done on extending network lifetime and increasing coverage.

Maximizing lifetime for k-barrier coverage in energy harvesting wireless sensor networks

“…This work fills a gap between [10] and [2]. In [10] the problem of achieving maximum lifetime for k-barrier coverage is solved in the homogeneous case when the network does not have energy harvesting nodes.…”

“…In [10] the problem of achieving maximum lifetime for k-barrier coverage is solved in the homogeneous case when the network does not have energy harvesting nodes. In [2] the case of energy harvesting nodes is examined, and an exact solution is given in the case that the network is able to run continuously and never needs to power off.…”

“…We can situate this algorithm in terms of the algorithm given for continuous barrier coverage in [2]. For ease of exposition, we switch to the definitions of α and β used in that paper, i.e.…”

“…β is the rate of charging regardless of whether or not a node is sensing, and α is cost of sensing. If our network is capable of providing continuous barrier coverage, then from [2] we must have β α ≥ k m . Note that if this is the case in the above application then in each ∆-interval we have the net change in charge of each node being…”

Energy Consumption Model of WSN Based on Manifold Learning Algorithm

“…With the rapid development of Wireless Sensor Network (WSN), the question how to extend the lifecycle of a node and reduce the energy consumption has gradually become a key issue to WSN [1][2][3][4][5]. Compared with the conventional network, WSN is featured with constrained energy and dynamic changes in topology characteristics [6][7][8].…”