A Framework for Opportunistic Allocation of Wireless Resources

Abstract

-Wireless multi-hop, mesh networks are being considered as a candidate to backhaul data traffic from access networks to the wired Internet. To enhance system performance, scheduling algorithms for wireless mesh networks are desirable to take advantage of multi-user diversity resulted from timevarying channel condition and space-varying path loss. Although many existing scheduling algorithms or medium access protocols have been adopted for the wireless mesh networks, they do not perform well, given that the algorithms are devised for wireless access. In this paper, we study the computational complexity in finding the optimal schedule for a mesh network with time-division-duplexing (TDD) operations. We propose a novel heuristic distributed scheduling framework for wireless mesh networks with open definitions of utility function. Performance analysis shows that our proposed framework is of polynomial-time complexity. Simulation results compare our framework with the tree-structural approach, and reveal that our proposed framework is highly capable of selecting and scheduling links with high utility in a fully distributed manner.

Efficient Cross-Layer Simulator for Performance Evaluation of Wireless Mesh Networks

“…Due to the fact in [10,28,18] that finding a perfect match with the highest network throughput is NP-complete [25,14] for centralized scheduling algorithms, various distributed scheduling algorithms were proposed. Recently, [15,16] proposed a distributed opportunistic scheduling algorithm for backhaul networks, which provides multi-user diversity gain in the wireless environments, enforces resource allocation in the long run and maintains strong temporal correlation for interference, without which channel quality and interference cannot be tracked and predicted with reasonable accuracy.…”

A Novel Cross-Layer QoS Routing Algorithm for Wireless Mesh Networks

“…Due to the fact [12] and [13] that finding a perfect match with the highest network throughput is NP-complete [14]- [15] for centralized scheduling algorithms, various distributed scheduling algorithms have been proposed. Recently, [16]- [17] propose a distributed opportunistic scheduling algorithm for backhaul networks, which provides multi-user diversity gain in the wireless environments, enforces resource allocation in the long run and maintains strong temporal correlation for interference, without which channel quality and interference cannot be tracked and predicted with reasonable accuracy.…”

“…First, by formulating a novel integrated QoS performance metric, various QoS constraints are explicitly considered. Second, we propose a cross-layer QoS routing algorithm interacting with distributed opportunistic scheduler in [16] and [17] to optimize the network performance. To the best of our knowledge, this is the first paper not only explicitly considers with multiple performance metrics, but also takes advantage of channel conditions explored by MAC scheduler and therefore proposes a crosslayer scheduling and routing solution.…”

A Cross-Layer Framework of QoS Routing and Distributed Scheduling for Mesh Networks

“…Medium Access Control: In order to exploit the multiuser diversity gain, the distributed opportunistic proportional fair scheduler proposed in [4][5] is considered in our crosslayer framework. This scheduling scheme has been proven not only to achieve a network throughput improvement but at the same time to allow for more accurate channel predictions by providing high level of temporal correlation of interference.…”

“…Due to the fact in [2] and [12] that finding a perfect match with the highest network throughput is NP-complete ( [10], [3]) for centralized scheduling algorithms, various distributed scheduling algorithms were proposed. Recently, [4] and [5] proposed a distributed opportunistic scheduling algorithm for backhaul networks, which provides multi-user diversity gain in the wireless environments, enforces resource allocation in the long run and maintains strong temporal correlation for interference, without which channel quality and interference cannot be tracked and predicted with reasonable accuracy.…”