Resource allocation and cross-layer control in wireless networks
Foundations and Trends® in Networking
Greedy primal-dual algorithm for dynamic resource allocation in complex networks
Queueing Systems: Theory and Applications
IEEE/ACM Transactions on Networking (TON)
Energy optimal control for time-varying wireless networks
IEEE Transactions on Information Theory
Optimal Energy and Delay Tradeoffs for Multiuser Wireless Downlinks
IEEE Transactions on Information Theory
Dynamic power allocation and routing for time-varying wireless networks
IEEE Journal on Selected Areas in Communications
Super-fast delay tradeoffs for utility optimal fair scheduling in wireless networks
IEEE Journal on Selected Areas in Communications
Routing without routes: the backpressure collection protocol
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Delay efficient scheduling via redundant constraints in multihop networks
Performance Evaluation
Dishonest reporting in queue-based cross-layer network optimization
Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service
Timescale decoupled routing and rate control in intermittently connected networks
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Hi-index | 0.00 |
In this paper, we consider the problem of reducing network delay in stochastic network utility optimization problems. We start by studying the recently proposed quadratic Lyapunov function based algorithms (QLA). We show that for every stochastic problem, there is a corresponding deterministic problem, whose dual optimal solution "exponentially attracts" the network backlog process under QLA. In particular, the probability that the backlog vector under QLA deviates from the attractor is exponentially decreasing in their Euclidean distance. This suggests that one can roughly "subtract out" a Lagrange multiplier from the system induced by QLA. We thus develop a family of Fast Quadratic Lyapunov based Algorithms (FQLA) that achieve an [O(1/V),O(log2(V))] performance-delay tradeoff. These results highlight the "network gravity" role of Lagrange Multipliers in network scheduling. This role can be viewed as the counterpart of the "shadow price" role of Lagrange Multipliers in flow regulation for classic flow-based network problems.