On the effect of human mobility to the design of metropolitan mobile opportunistic networks of sensors

This is the author accepted manuscriptWe live in a world where demand for monitoring natural and artificial phenomena is growing. The practical importance of Sensor Networks is continuously increasing in our society due to their broad applicability to tasks such as traffic and air-pollution monitoring, forest-fire detection, agriculture, and battlefield communication. 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 as dolphins, trees, and humans. The consequence of this widespread use of sensors is that new sensor network infrastructures may be built out of static (e.g., traffic lights) and mobile nodes (e.g., mobile phones, cars). The use of smart devices carried by people in sensor network infrastructures creates a new paradigm we refer to as Social Networks of Sensors (SNoS). This kind of opportunistic network may be fruitful and economically advantageous where the connectivity, the performance, of the scalability provided by cellular networks fail to provide an adequate quality of service. This paper delves into the issue of understanding the impact of human mobility patterns to the performance of sensor network infrastructures with respect to four different metrics, namely: detection time, report time, data delivery rate, and network coverage area ratio. Moreover, we evaluate the impact of several other mobility patterns (in addition to human mobility) to the performance of these sensor networks on the four metrics above. Finally, we propose possible improvements to the design of sensor network infrastructures

Using Patterns of Social Dynamics in the Design of Social Networks of Sensors

The practical importance of sensor networks is continuously increasing; from air-pollution monitoring to forest-fire detection, from agriculture to battlefield communication, sensor networks are now part of many dimensions of society. Furthermore, we live in a world where sensors integrated in smart objects and smart phones are increasingly pervasive. The use of such sensors as if they were sensor network infrastructures (towards what we call Social Networks of Sensors'', or SNoS) may be very fruitful and economically advantageous. However, it also introduces some new research challenges, one of which relates to understanding the potential impact of social mobility patterns---for sensors integrated into the performances of sensor infrastructures. This paper delves into such issue and analyses how the presence of mobile sensors moving according to social mobility patterns can impact the performances of fixed sensor network infrastructures and their design choices. Simulation results show that such integration can lead to increased efficiency of the integrated SNoS infrastructure for both sensing coverage and data delivery