Approximation algorithms
A utility-based power-control scheme in wireless cellular systems
IEEE/ACM Transactions on Networking (TON)
Maximum lifetime routing in wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Network optimization and control
Foundations and Trends® in Networking
Towards utility-optimal random access without message passing
Wireless Communications & Mobile Computing - Recent Advances in Wireless Communications and Networks
Network Coding: An Introduction
Network Coding: An Introduction
Markov approximation for combinatorial network optimization
INFOCOM'10 Proceedings of the 29th conference on Information communications
Distributed algorithms for maximum lifetime routing in wireless sensor networks
IEEE Transactions on Wireless Communications
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Min-Cost Selfish Multicast With Network Coding
IEEE Transactions on Information Theory
Cross-Layer Optimization for Wireless Networks With Deterministic Channel Models
IEEE Transactions on Information Theory
Hi-index | 0.00 |
In this paper, we study the problem of maximising network lifetime in wireless multihop networks with network coding. For this aim, we introduce a cross-layer formulation with general Network Utility Maximisation NUM that accommodates routing, scheduling and stream control from different layers of network. Specifically, to maximise such a lifetime while satisfying a given traffic demand, we elaborate its objective along with a lifetime fairness constraint and the other relevant constraints across different layers. Consequently, by taking network coding into account, we resolve the optimisation problem with a stochastic primal-dual algorithm that can iteratively update its subgradients to find the saddle points involved with a smoother trajectory, and can globally converge to the optimal solutions asymptotically. In particular, the corresponding distributed algorithms can be resulted to dynamically approach the optimal in a distributed manner. Finally, our numerical results are presented to validate and exhibit the possible benefits that can be gained from the cross-layer optimisation and the corresponding algorithms.