We consider a data aggregating wireless network where all nodes have data to send to a single destination node, the sink. We consider a linear placement of nodes with the sink at one end. The nodes communicate directly to the sink (single hop transmi
ssion) and we assume that the nodes are scheduled one at a time by a central scheduler (possibly the sink). The wireless nodes are power limited and our network objective (notion of fairness) is to maximize the minimum throughput of the nodes subject to the node power constraints. In this work, we consider network designs that permit adapting node transmission time, node transmission power and node placements, and study cross- layer strategies that seek to maximize the network throughput. Using simulations, we characterize the performance of the dif- ferent strategies and comment on their applicability for various network scenarios.
We consider allcast and multicast flow problems where either all of the nodes or only a subset of the nodes may be in session. Traffic from each node in the session has to be sent to every other node in the session. If the session does not consist of
all the nodes, the remaining nodes act as relays. The nodes are connected by undirected links whose capacities are independent and identically distributed random variables. We study the asymptotics of the capacity region (with network coding) in the limit of a large number of nodes, and show that the normalized sum rate converges to a constant almost surely. We then provide a decentralized push-pull algorithm that asymptotically achieves this normalized sum rate without network coding.
