Mobility improves coverage of sensor networks

Abstract

Previous work on the coverage of mobile sensor networks focuses on algorithms to reposition sensors in order to achieve a static configuration with an enlarged covered area. In this paper, we study the dynamic aspects of the coverage of a mobile sensor network that depend on the process of sensor movement. As time goes by, a position is more likely to be covered; targets that might never be detected in a stationary sensor network can now be detected by moving sensors. We characterize the area coverage at specific time instants and during time intervals, as well as the time it takes to detect a randomly located stationary target. Our results show that sensor mobility can be exploited to compensate for the lack of sensors and improve network coverage. For mobile targets, we take a game theoretic approach and derive optimal mobility strategies for sensors and targets from their own perspectives.

Ensuring strong data guarantees in highly mobile ad hoc networks via quorum systems

“…Figure 11 shows the variation of max(f p ), avg(f p ), max(f r ), avg(f r ), ∆(f p ) over different speed. We observe no significant variation of avg(f p ), which is encouraging for our approach and confirms that mobility can improve network connectivity as shown by recent papers (8). Note that we observe a significant variation of max(f p ) and max(f r ) from one execution to another, especially for high average speed.…”

“…In our experiments we have also noticed that the variability of the time pause affects function f p (t) and the increment/decrement of f p (t) during a small time interval (e.g., 10 seconds). For instance, function f p (t) is smoother if the time pause is contained in [8,12] seconds. This is not surprising since the variability of the nodes increases in case of larger pause intervals.…”

A Survey on Localization for Mobile Wireless Sensor Networks

“…However, when nodes are mobile, redeployment is possible. In fact, it has been shown [17], [18] that the integration of mobile entities into WSNs improves coverage, and hence, utility of the sensor network deployment. This enables more versatile sensing applications as well [1].…”

Dynamic Point Coverage in Wireless Sensor Networks: A Learning Automata Approach

“…This can lead to fast energy exhaustion of nodes, and hence shortening the lifetime of the network. Many researchers try to overcome the point coverage problem by designing a suitable scheduling strategy for making nodes on and off in such a way that in each time slice, only nodes which can sense the target points in that period are on [13,14,15,16,17,18,19,20]. In this method, many nodes are scattered randomly throughout the filed, and the criterion of minimum number of required nodes addressed by the scheduling mechanism which tries to minimize the number of nodes being in on state according to their ability to sense the target points.…”