Minimization methods for non-differentiable functions
Minimization methods for non-differentiable functions
Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Utility-based rate control in the Internet for elastic traffic
IEEE/ACM Transactions on Networking (TON)
Energy, congestion and dilation in radio networks
Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures
Convex Optimization
Flow Allocation in Multi-hop Wireless Networks: A Cross-Layer Approach
IEEE Transactions on Wireless Communications
The capacity of wireless networks
IEEE Transactions on Information Theory
Impact of node density on throughput and delay scaling in multi-hop wireless networks
IEEE Transactions on Wireless Communications
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This paper addresses service differentiation with interference consideration for traffic with different priorities in multi-hop wireless networks. Specifically, we propose a cross-layer framework which supports different service levels in terms of queuing delays for concurrent sessions of different priorities. The system architecture is composed of two major components: a priority-based flow scheduler and an interference-aware bandwidth allocation unit. The priority-based flow scheduler differentiates the queueing delay for data packets being relayed to the next hop according to their priorities. As a result, the sessions of higher priority are guaranteed to have lower queueing delay at each intermediate node on the path to the receiver while the starvation of the lower priority session can be avoided. To utilize wireless resources optimally, we formulate the bandwidth allocation problem with interference consideration as a convex optimization problem. The problem can be solved by a subgradient algorithm in a distributed fashion. We then develop a distributed protocol for our proposed algorithm. The simulation results show that the proposed algorithm can achieve different levels of bandwidth allocation efficiently with a limited number of iterations. In addition, our algorithm scales well when the number of sessions and the size of the session increase. Together with the priority-based flow scheduler, the end-to-end throughput and delay can be effectively differentiated based on different levels of bandwidth allocation.