Evaluating the Performance of Social Networks of Sensors Under Different Mobility Models

We live in a world where demand for monitoring natural phenomena is growing. Sensor Networks are becoming ubiquitous in our society due to their broad applicability to data intensive tasks such as keeping air population to safe levels, efficient communication in military applications, implementation of alarms for forest fires, to mention but a few. Furthermore, we have seen the emergence of sensor technology being integrated in everyday objects such as cars, traffic lights, bicycles, phones, and even being attached to living beings such dolphins, trees, birds and humans. The consequence of this widespread use of sensors is that new sensor network infrastructures may be built out of static and mobile nodes. When mobility is a variable one should define which mobility model is best for the infrastructure given their differences; for instance human mobility is not akin to bird mobility. This paper then tries to evaluate which mobility pattern (or model) is best suited to be used in a Social Network of Sensors (SNoS). We evaluate several mobility models and measure the efficiency of information flow in a SNoS if mobile sensors follow these mobility patterns. The paper provide us with a greater understanding of the benefits of mobility in realistic scenarios.