Self-organized aggregation in irregular wireless networks

Gossip-based epidemic protocols are used to aggregate data in distributed systems. This fault-tolerant approach does neither require maintenance of any global network state nor knowledge of network structure. However, although gossip-based aggregation algorithms scale well for graphs with good expansion, their efficiency for sparse graphs is unexamined. In this paper we analyze the feasibility and efficiency of a gossip aggregation protocol in wireless networks with low expansion. We propose a modification of the existing aggregation algorithm for use in locality-aware, sparse, static wireless networks. Our protocol terminates autonomously, uses less bandwidth than the original version, and removes the need for the leader election process while counting network nodes. Aggregates are calculated only over nodes placed in the vicinity, and nodes communicate only with their immediate neighbors by using a wireless broadcast. We evaluate our approach by simulation on sparse, irregular graphs with low expansion for the simplified system model. Furthermore, we analytically assess the worst-case convergence time of this protocol for sparse wireless networks and also for the simplified system model.