Abstract
Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations.
Highlights
Wireless Sensor Networks (WSNs) equipped with extremely small, low cost sensors that possess sensing, signal processing and wireless communication capacities are highly capable of performing monitoring applications
The energy consumption model in [5] established that the energy consumed by transmitting a unit of data is the same for each node, whereas energy performance is still hard to evaluate based on elusory communication distance measurements
We focused on the energy performance of the Static Sink (SS) and Mobile Sinks (MSs) which are more critical than other ordinary sensors for the whole monitoring network
Summary
Wireless Sensor Networks (WSNs) equipped with extremely small, low cost sensors that possess sensing, signal processing and wireless communication capacities are highly capable of performing monitoring applications. We show that it is possible to achieve considerable savings in energy consumption expended on communication to mobile sinks at the expense of a moderate increase in message delivery delay. Exploration of this trade-off is the main principle that underlies the design of our algorithm. The objective of point coverage is similar, but it is to cover a set of points The latter, barrier coverage, aims to minimize the probability of undetected penetration through a sensor network. To measure barrier coverage, [2] defined the worst- and best-case coverage They proposed two centralized algorithms to solve these problems. Regarding modeling the energy performance, in the energy model for gathered data transmission, MS mobility and load balancing critical factors
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