Distributed online data aggregation for large scale sensor networks

To benefit from data aggregation in large scale sensor networks, an aggregation point, i.e. the place where data are aggregated, must be close to sources. In event triggered sensor networks, this can be achieved by dynamically constructing a tree connecting the sources rooted at a nearby node. However, this incurs high control and maintenance overhead. With static trees, the distance (Delta) between sources and the aggregation point can be as high as O(n) where n is the number of nodes in the network. This diminishes the benefit of data aggregation, thereby limiting the scalability of static trees. In this paper we propose AFT (alternative forwarding tree), a structure with multi-level overlapping clusters. Packet forwarding decisions on AFT are made on the fly when packets are being forwarded and it bounds the distance between the aggregation point and sources by O(delta) irrespective of network size, where delta is the diameter of the event. This guarantees that packets can be aggregated near sources without the overhead of constructing a dynamic structure and therefore is scalable. We prove that in the worst case, AFT guarantees aggregation at a node that is at most 2(1 + radic13)delta away from the sources.