Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring

The study presents a novel computational intelligence algorithm designed to optimise energy consumption in an environmental monitoring process: specifically, water level measurements in flooded areas. This algorithm aims to obtain a tradeoff between accuracy and power consumption. The implementation constitutes a data aggregation and fusion in itself. A harsh environment can make the direct measurement of flood levels a difficult task. This study proposes a flood level estimation, inferred through the measurement of other common environmental variables. The benefit of this algorithm is tested both with simulations and real experiments conducted in Donñana, a national park in southern Spain where flood level measurements have traditionally been done manually.Junta de Andalucía P07-TIC-0247

Trading Structure for Randomness in Wireless Opportunistic Routing

Opportunistic routing is a recent technique that achieves high throughput in the face of lossy wireless links. The current opportunistic routing protocol, ExOR, ties the MAC with routing, imposing a strict schedule on routers' access to the medium. Although the scheduler delivers opportunistic gains, it misses some of the inherent features of the 802.11 MAC. For example, it prevents spatial reuse and thus may underutilize the wireless medium. It also eliminates the layering abstraction, making the protocol less amenable to extensions of alternate traffic type such as multicast.This paper presents MORE, a MAC-independent opportunistic routing protocol. MORE randomly mixes packets before forwarding them. This randomness ensures that routers that hear the same transmission do not forward the same packets. Thus, MORE needs no special scheduler to coordinate routers and can run directly on top of 802.11. Experimental results from a 20-node wireless testbed show that MORE's average unicast throughput is 20% higher than ExOR, and the gains rise to 50% over ExOR when there is a chance of spatial reuse. For multicast, MORE's gains increase with the number of destinations, and are 35-200% greater than ExOR

Towards an Optimized Traffic-Aware Routing in Wireless Mesh Networks

International audienceIn this paper we study through simulations the impact of PHY/MAC protocols on higher layers. In a comparative way, we investigate the effectiveness of some protocols when they coexist on a wireless mesh network environment. Results show that PHY/MAC parameters have an important impact on routing performances. Based on these results, we propose two tra c-aware routing metrics based on link availability. The information about the link availability/occupancy is picked up from lower layers using a cross-layer approach. The rst metric is load-sensitive and aims to balance the tra c load according to the availability of a link to support additional ows. The second metric reproduces better the capacity of a link since it is based on its residual bandwidth. Using several real experiments, we have shown that our proposals can accurately determine better paths in terms of throughput and delay. Our experiments are carried out into an heterogeneous IEEE 802.11n based network running with OLSR routing protocol