Utility Optimal Coding for Packet Transmission over Wireless Networks - Part II: Networks of Packet Erasure Channels

We define a class of multi--hop erasure networks that approximates a wireless multi--hop network. The network carries unicast flows for multiple users, and each information packet within a flow is required to be decoded at the flow destination within a specified delay deadline. The allocation of coding rates amongst flows/users is constrained by network capacity. We propose a proportional fair transmission scheme that maximises the sum utility of flow throughputs. This is achieved by {\em jointly optimising the packet coding rates and the allocation of bits of coded packets across transmission slots.}Comment: Submitted to the Forty-Ninth Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, US

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes take samples periodically and then contend over a {\em random access network} to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center to process the measurements. The Bayesian setting is assumed; i.e., the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is \emph{network-oblivious} and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is \emph{network-aware} and processes measurements as they arrive, but in a time causal order. In this case, the decision statistic depends on the network delays as well, whereas in the network-oblivious case, the decision statistic does not depend on the network delays. This yields a Bayesian change detection problem with a tradeoff between the random network delay and the decision delay; a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network--oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network--aware case, the optimal stopping problem is analysed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient statistic for decision is found to be the network-state and the posterior probability of change having occurred given the measurements received and the state of the network. The optimal regimes are studied using simulation.Comment: To appear in ACM Transactions on Sensor Networks. A part of this work was presented in IEEE SECON 2006, and Allerton 201

Utility Optimal Coding for Packet Transmission over Wireless Networks - Part I: Networks of Binary Symmetric Channels

We consider multi--hop networks comprising Binary Symmetric Channels ($\mathsf{BSC}$s). The network carries unicast flows for multiple users. The utility of the network is the sum of the utilities of the flows, where the utility of each flow is a concave function of its throughput. Given that the network capacity is shared by the flows, there is a contention for network resources like coding rate (at the physical layer), scheduling time (at the MAC layer), etc., among the flows. We propose a proportional fair transmission scheme that maximises the sum utility of flow throughputs subject to the rate and the scheduling constraints. This is achieved by {\em jointly optimising the packet coding rates of all the flows through the network}.Comment: Submitted to Forty-Ninth Annual Allerton Conference on Communication, Control, and Computing, Monticello, IL, US

Proportional Fair Coding for Wireless Mesh Networks

We consider multihop wireless networks carrying unicast flows for multiple users. Each flow has a specified delay deadline, and the lossy wireless links are modeled as binary symmetric channels (BSCs). Since transmission time, also called airtime, on the links is shared among flows, increasing the airtime for one flow comes at the cost of reducing the airtime available to other flows sharing the same link. We derive the joint allocation of flow airtimes and coding rates that achieves the proportionally fair throughput allocation. This utility optimization problem is nonconvex, and one of the technical contributions of this paper is to show that the proportional fair utility optimization can nevertheless be decomposed into a sequence of convex optimization problems. The solution to this sequence of convex problems is the unique solution to the original nonconvex optimization. Surprisingly, this solution can be written in an explicit form that yields considerable insight into the nature of the proportional fair joint airtime/coding rate allocation. To our knowledge, this is the first time that the utility fair joint allocation of airtime/coding rate has been analyzed, and also one of the first times that utility fairness with delay deadlines has been considered