A New Opportunistic Routing Scheme in Low Duty-Cycle WSNs for Monitoring Infrequent Events

We address opportunistic routing in low-duty cycle wireless sensor networks. A low duty-cycle consists in alternating active and sleep cycles asynchronously in order to save energy. In multihop networks, such a design must take an opportunistic approach in order to cope with the unpredictable appearance of wireless links. In fact, topology-based routing approaches are ineffective in this context. Our main objective is to maximize the network lifespan while guaranteeing i) the routing of packets to the sink and ii) acceptable end-to-end delays. We propose a new geographical opportunistic cross-layer scheme based on an asynchronous sender-oriented MAC protocol. The proposal sets the priority of selecting the next hop, among all potential candidates, according to its closeness to the sink. The next hop is elected through a selection process based on signalling bursts. The performance evaluation of our proposal is carried out both by an analytical model and simulations. The approach is evaluated in terms of i) probability of packet delivery to the sink, ii) number of hops per path and iii) end-to-end packet delay from the source to the sink

Communication protocols for energy constrained networks

Ph.DDOCTOR OF PHILOSOPH

Resource Efficient Urban Delay/disruptive Tolerant Networks

Ph.DDOCTOR OF PHILOSOPH

Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network