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

Abstract

Cross-layer routing and scheduling algorithms design for wireless backhaul mesh network has attracted much research interest recently. The network is expected to support various types of applications with different quality of service (QoS) requirements from both routing and scheduling perspectives. Existing works do not efficiently integrate these QoS constraints in route discovery and maintenance phases and overlook the interaction between medium access control (MAC) and routing algorithms. In this work, we propose a novel crosslayer framework of QoS routing and distributed opportunistic scheduling for wireless mesh network, which provides resource reservation for QoS flows. Studies with different scheduling algorithms and routing protocols have shown that our algorithm successfully guarantees various QoS requirements and achieves higher network throughput when compared with other standard techniques.

Route Capacity Estimation Based Admission Control and QoS Routing for Mesh Networks

“…Furthermore, sessions are randomly chosen to be either premium or regular service class. In network layer, the integrated QoS routing protocol [9], [10] is used to provide sub-optimal candidate routes with multiple QoS constraints. MAC layer uses distributed opportunities scheduler developed in [11].…”

“…The proposed algorithm, referred as "Dist+IQoSR+RC-CAC", is compared with our previous work presented in [9], [10] which does not include different GoS and prediction scheme for admission control "Dist+IQoSR". We also compare our scheme with conventional layer 2 and 3 techniques, the round robin scheduler (RR, [14]) and AODV routing protocol [15], and also the recent research output "SCAC" in [8] as benchmarks.…”

“…By solving quadratic function (9), we show that the route capacity is approximated by (10). If further assuming that f is smooth enough around point (N t0 , T t0 ), i.e., ∃ε ≈ 0, and δ > 0, so that,…”

“…Moreover, Gaussian traffic arrival assumption may not always hold, thus achievable capacity region could be inaccurate. Works [9], [10] study extensively on the integrated QoS routing protocol and the actual interface between the scheduling [11] and routing schemes, to provide optimum routes that guarantee multiple QoS constraints.…”

“…Our previous results in [9], [10] defined a new utility function based on the "dissatisfaction ratio" R that is experienced by each QoS metric, R D k for ETE packet delay, R T k for throughput, and R E k for PER. Hence, a source-to-gateway route k will be feasible if and only if all defined ratios are less than 1, i.e., R…”