We consider the problem of coordinating a group of mobile nodes communicating through a wireless medium. The objective of the network is the alignment of all the nodes towards a common direction through local interactions, without the need for global knowledge such as the network topology or the maximum degree of the network, or even local parameters, such as the number of neighbors. The key feature of our algorithm is that each node state update is done through voting, where the probability of each vote is biased by the state of the node neighbors. We propose two possible physical implementations for our algorithm. The first is based on the explicit exchange of packetized messages, while the second is a cross-layer approach. Our analysis unveils key convergence properties of this simple class of alignment algorithms, via analytical and simulated results.

Kalman filtering is a classical technique with a number of potential distributed applications in sensor networks. In this paper we consider a specific algorithm for distributed Kalman filtering proposed recently by Olfati-Saber [Olfati-Saber, 2005 ]. We design a communication access protocol for wireless sensor networks that is tailored to converge rapidly to the desired estimate and provides scalable error performance as number of sensors increases. By exploiting the structure of the distributed filtering computations, we derive an optimal communication resource allocation policy for minimizing the component-wise state estimation error. We provide simulation results demonstrating the performance of our architecture.

We study error propagation in wireless cooperative broadcast protocols. In our model, nodes in the network are randomly deployed in a fixed region. The message from a certain source node is relayed by multiple groups of cooperating relays that are located in predetermined consecutive swaths of the network area. We refer to these groups of relays as "levels". Our analysis is based on the derivation of recursive equations that express the error rate at each relay in a given level as a function of the error probabilities of the nodes in the previous levels. To provide analytical results we take the limit as the number of nodes goes to infinity while the relay power goes to zero, so that the relay power density per unit area is constant. In the limit, we show that the relay power density and area of the regions that correspond to the levels lead to fixed points in the error rate that prevent catastrophic error propagation, regardless of the distance the message is transmitted over.