Localized Techniques for Broadcasting in Wireless Sensor Networks

Abstract

In this paper we tackle the problem of designing simple, localized, low energy consuming, reliable protocols for one-to-all communication in large scale wireless sensor networks. Our first proposed technique, called the Irrigator protocol, relies on the idea to first build a sparse overlay network, and then flood over it. The overlay network is set up by means of a simple, distributed, localized probabilistic protocol and spans all the sensor nodes with high probability. Based on the algorithmic ideas of the Irrigator protocol we then develop a second protocol, dubbed Fireworks, with similar performance that does not require any overlay network to be set up in advance. Asymptotic analytical results are provided which assess the reliability of the Irrigator and Fireworks techniques. The theoretical analysis of the proposed protocols is complemented and validated by a (simulation based) comparative performance evaluation that assesses several advantages of our new protocols with respect to gossiping and simple flooding. Differently from previous studies, we analyze and demonstrate the performance of our protocols for two different node distributions: The typical uniform distribution and a newly defined "hill" distribution, here introduced to capture some of the important and more realistic aspects of 413 node deployment in heterogeneous terrain. Simulation results show that the proposed schemes achieve very good trade-offs between low overhead, low energy consumption and high reliability. In particular, the Irrigator and Fireworks protocols are more reliable than gossiping, and significantly reduce the number of links along which a message is sent over both flooding and gossiping.

Broadcast in wireless mobile sensor networks with population protocols and extension with the rendezvous model

“…But, since several communications can take place simultaneously during its execution, there is a risk of collision and duplication of the information since a node can receive it from several neighbors. Many works adopted this model, like [5] [6] [7] [8] [9] [10] [11], in a static context, trying to find the adequate probability while choosing a neighbour at each iteration, to avoid the problems that we cited. And even if we use this model in a mobile context, the problems will persist.…”

Detecting and Defending against Replication Attacks in Wireless Sensor Networks

“…Stationary nodes can get their geographic location by using positioning device (e.g., GPS device) or positioning algorithms [15][16][17][18]. Also, we assume that all the sensor nodes are loosely time synchronized using time synchronization techniques, such as [19,20].…”

Randomized broadcasting in wireless mobile sensor networks

“…However, because several communications can take place simultaneously during its execution, there is a risk of collision and duplication of the information because a node can receive it from several neighbours. Many works adopted this model, such as , in a static context, trying to find the adequate probability while choosing a neighbour at each iteration, to avoid the problems that we cited. Nevertheless, even if we use this model in a mobile context, the problems will persist.…”