Prediction-Based Localization for Mobile Wireless Sensor Networks

Abstract

In this paper, we propose two extensions of SDPL (Speed and Direction Prediction-based Localization) method. The first is called MA-SDPL (Multiple Anchors SDPL) which uses multiple mobile anchors instead of only one. Each anchor has its own trajectory and its own departure point. The goal is to ensure a total coverage of the sensor field and to multiply the chance of receiving anchor beacons. Anchor Beacons help localizing mobile sensors. As a consequence, the location estimation will be enhanced. The second method deals with one mobile anchor but with the ability of multi-hoping, that is, when a sensor estimates that it is well enough localized, it sends beacons to its hneighborhood about its current location, hence, it plays the role of an additional anchor. This solution reduces the cost comparing to when using multiple anchors and allows rapid location propagation. Simulation results show that the two extensions improve better the ratio of localized sensors and reduce the location error compared to the basic SDPL. We have also tested them in a noisy environment to be closer to a real deployment.

Intertwined localization and error-resilient geographic routing for mobile wireless sensor networks

“…In this section, we describe our proposed localization algorithm Speed and Direction Prediction-based Localization (SDPL), which the preliminary version was previously published in [17]. The method allows localizing mobile sensor nodes with the assistance of a mobile anchor visiting the sensor area and following a path that ensures visiting the maximum number of nodes.…”

“…The scheme exploits previous nodal locations to predict the speed and the direction a mobile node moves with. Due to space restrictions, we refer the interested reader to [17] and to its improvement published in [18] for further details.…”

“…If the packet holder finds no neighbor that goes towards the sink or no neighbor that has higher weight than its weight, i.e. no neighbor fulfills condition (18), then it applies the carry-and-forward strategy, that is, it keeps holding the packet while continuing its basic trajectory hoping to across a neighbor that goes toward the destination or being in a more adequate neighborhood. In the previous example, if s moves with 12m/s which higher than the speeds of its neighbors, then Ws=0.16 > W 1 =0.14 > W 2 =0.08.…”

“…The maximum speed of nodes ranges in {3, 5, 10, 15} m/s while the minimum speed is 0.05 m/s to ensure that all nodes are totally mobile. The mobile anchor that assists the localization phase follows WAVES trajectory [39] with a resolution of 20m and has a fixed speed of 20m/s emulating UAV average speed. Each 6 seconds, nodes independently estimate their positions.…”

“…The protocol is composed of two intertwined algorithms. Speed and Direction Prediction-based Localization (SDPL) for localizing mobile nodes which is an improvement of our works published in [17,18] that gives an estimate of the location error bound to be considered in the routing phase. The other algorithm is a new geographic routing that uses on-demand neighborhood discovery and exploits the results of the improved localization algorithm to route packets considering the location-error, the mobility of nodes and the intermittence of the connections.…”