Opportunistic Direct Interconnection between Co-Located Wireless Sensor Networks

Wireless sensor networks are usually designed to avoid interaction with other networks. To share information, they are usually connected via a backbone network (e.g. the Internet) using gateways. The realization of visions for pervasive computing depends upon effective interconnection between individual networks. As the number of deployed sensor networks increases, the chance of any network having multiple neighbors also increases. In this paper, we argue that a paradigm shift towards ´opportunistic direct interconnection´ is required. This enables one network to share information or resources with neighboring networks that it was unaware of at design-time. We present OI-MAC, which supports automatic neighbor discovery and cross- boundary data exchange without sacrificing the independence of each network. The effects of discovery and cross-boundary data injection are evaluated using both analytical models and network simulation. Initial results indicate that neighbor discovery has little effect on latency, while energy consumption increases insignificantly compared to ordinary operations of each node. If network traffic is doubled by packets ´injected´ from a neighboring network, latency increases by around 7% while average power consumption increases by 20%.