Energy Efficiency in W-Grid Data-Centric Sensor Networks via Workload Balancing

Wireless sensor networks are usually composed by small units able to sense and transmit to a sink elementary data which are then processed by an external machine. However, recent improvements in the memory and computational power of sensors, together with the reduction of energy consumption, are rapidly changing the potential of such systems, moving the attention towards data-centric sensor networks. In this kind of networks, nodes are smart enough either to store some data and to perform basic processing allowing the network itself to supply higher level information closer to the network user expectations. In other words, sensors no longer transmit each elementary data sensed, rather they cooperate in order to assemble them in more complex and synthetic information, which will be locally stored and transmitted according to queries and/or events defined by users and external applications. Recently, we proposed W-Grid, a fully decentralized cross-layer infrastructure for self-organizing data-centric sensor networks where wireless communication occur through multi-hop routing among devices. In this paper, we show that network traffic, and thus the energy consumption, can be balanced among sensors by assigning multiple virtual coordinates to nodes trough a fully decentralized workload balancing algorithm, which extends W-Grid.