Avoid 'void' in geographic routing for data aggregation in sensor networks

Abstract

Wireless sensor networks have attracted great attention in research and industrial development due to its fast-growing application potentials. New techniques must be developed for sensor networks due to their lack of infrastructure support and the constraints on computation capability, memory space, communication bandwidth, and above all, energy supply. To prolong the life time of a battery-powered sensor network, an energy efficient routing algorithm for data collection is essential. We propose a new geographic routing algorithm that forwards packets from sensors to base stations along efficient routes. The algorithm eliminates the voids that cause non-optimal routing paths in geographic routing. It replaces the right-hand rule by distance upgrading. It is fully distributed and responds to topology changes instantly with localized operations. We formally prove the correctness of the algorithm and evaluate its performance by simulations.

A Survey on Void Handling Techniques for Geographic Routing in VANET Network

“…One technique into this category is Distance Upgrading Algorithm (DUA) [22]. Main operation of these techniques is forwarding packets from a node has a higher cost towards a node has a lower cost.…”

“…In this algorithm, a method is provided for reducing the distance cost to an appropriate level. Figure 8.b and 8.c from [22] show respectively the mentioned problem and the presented solution in this algorithm. Second problem is incompatibility of these techniques with changes of the network topology.…”

SWR: Smartness Provided by Simple, Efficient, and Self-Adaptive Algorithm

“…Routing algorithms should be able to cope with the void problem. Approaches and algorithms for void problem in geographical routing in sensor networks are well defined in [19][20][21].…”

“…These algorithms may also experience void problem. Only few of those [19][20][21] propose solutions for local-minima problem and to recover voids. Although the SWR does not suffer from local-minima problem, it utilizes a void recovery algorithm to pass around large void areas [27] if and only if such a problem is not overcame implicitly by the use of multiple paths.…”

Path quality detection algorithms for near optimal geographic routing in sensor networks with obstacles

“…Cost based approach [13] consists in assigning a cost to each node, proportional to the distance to the destination. When greedy forwarding fails, a node will forward a packet to a neighbor with a lower cost than itself.…”