An Adaptive Blind Algorithm for Energy Balanced Data Propagation in Wireless Sensors Networks

Algorithmic Aspects of Wireless Sensor Networks

Moraru

Powell

et al. 2006

Self Cite

Abstract. Widely used positioning systems like GPS are not a valid solution in large networks with small size, low cost sensors, due both to their size and their cost. Thus, new solutions for localization awareness are emerging, commonly based on the existence of a few references spread into the network. We propose a localization algorithm to reduce the number of transmitting nodes. The algorithm relies on self selecting nodes for location information disclosure. Each node makes a decision based on its proximity to the nodes in the area covered only by two of the references used for its own localization. We analyze different aspects of the location awareness propagation problem: communication overhead, redundant transmissions, network coverage.

Section: Introductionmentioning

confidence: 99%

Localization Algorithm for Wireless Ad-Hoc Sensor Networks with Traffic Overhead Minimization by Emission Inhibition

Algorithmic Aspects of Wireless Sensor Networks

Moraru

Powell

et al. 2006

Self Cite

“…If anymore messages are slided, S k will be in a "non-physical" state. So what we do is that we recompute all ǫ k 's for 1 ≤ k ≤ j, 8 but whenever an ǫ k < 0 and j k = 0, we force ǫ k to 0. What does this do?…”

Section: 1) So What Is the Problem?mentioning

confidence: 99%

Energy optimal data propagation in wireless sensor networks

Powell

Journal of Parallel and Distributed Computing

Rolim

2007

Self Cite

We propose an algorithm which produces a randomized strategy reaching optimal data propagation in wireless sensor networks (WSN). In [6] and [8], an energy balanced solution is sought using an approximation algorithm. Our algorithm improves by (a) when an energy-balanced solution does not exist, it still finds an optimal solution (whereas previous algorithms did not consider this case and provide no useful solution) (b) instead of being an approximation algorithm, it finds the exact solution in one pass. We also provide a rigorous proof of the optimality of our solution.

“…As far as we know, no previous similar works are present in the literature. However, stochastic estimation methods seems to appear sporadically for dynamic control of communications in wireless networks, see for instance [17,20,25].…”

Section: Related Workmentioning

confidence: 99%

Numerical Estimation of the Impact of Interferences on the Localization Problem in Sensor Networks

Bouget

Experimental Algorithms

Rolim

2006

Self Cite

Abstract.In this paper we numerically analyze the impact of interferences in wireless networks. More particularly, the impact on the probability of success of a localization algorithm. This problem is particularly relevant in the context of sensor networks. Actually, our numerical experiments provide information about this algorithm, even when we do not consider interferences. Indeed, in this case, sharp threshold is observed on the probability of success of the algorithm. Moreover, our numerical computations show that the main harmful interferences are the ones occurring between sensors which get localized at the same time and send in turn their own location. This is demonstrated by varying the time span of the random waiting time before the emissions. We then observe that the longer the waiting time the closer the curves are to the ones obtained without considering interferences. Hence, this proves to be an efficient way of reducing the impact of interferences on the localization algorithm. Moreover, our numerical experiments demonstrate that among the sectors of disk with same area, the one with the smaller radius of emission and larger angle of emission is the more appropriate to the localization algorithm.