QoS-aware networking applications such as real-time streaming and video surveillance systems require nearly fixed average end-to-end delay over long periods to communicate efficiently, although may tolerate some delay variations in short periods. This variability exhibits complex dynamics that makes rate control of such applications a formidable task. This paper addresses rate allocation for heterogeneous QoS-aware applications that preserves the long-term end-to-end delay constraint while, similar to Dynamic Network Utility Maximization (DNUM), strives to achieve the maximum network utility aggregated over a fixed time interval. Since capturing temporal dynamics in QoS requirements of sources is allowed in our system model, we incorporate a novel time-coupling constraint in which delay-sensitivity of sources is considered such that a certain end-to-end average delay for each source over a pre-specified time interval is satisfied. We propose DA-DNUM algorithm, as a dual-based solution, which allocates source rates for the next time interval in a distributed fashion, given the knowledge of network parameters in advance. Through numerical experiments, we show that DA-DNUM gains higher average link utilization and a wider range of feasible scenarios in comparison with the best, to our knowledge, rate control schemes that may guarantee such constraints on delay.
In another set of works @cite_3 @cite_8 @cite_14 @cite_22 , the source delay is incorporated as constraints of the optimization problems. By introducing Virtual Link Capacity Margin (VLCM) to characterize source delay as constraint of the problem, the authors in @cite_14 @cite_4 have proposed a joint rate allocation and scheduling scheme in multi-hop wireless networks. By a different approach in @cite_8 , another variant of NUM problem is formulated to address joint power and rate control. Moreover, in @cite_3 , using an elegant fluid model of multi-class flows with different delay requirements, another distributed and stable delay-aware algorithm is proposed. Despite these single-period NUM-based studies, NUM framework is intrinsically incapable of capturing temporal variations in network characteristics especially when these characteristics evolve with time scales comparable to those of the underlying dual-based algorithms. Generally speaking, (single-period) NUM along with delay constraints is subject to limited degrees of freedom, and as a result, one may face a broad range of infeasible problems. We will investigate this phenomenon in details in our experiments in .
@cite_14 @cite_4 @cite_22 @cite_8 @cite_3
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This paper investigates the optimal rate allocation problem with end-to-end delay constraints in multi-hop wireless networks. We introduce Virtual Link Capacity Margin (VLCM), which is the gap between the schedulable link capacity and the maximum allowable flow rate over a link, for link delay control. We formulate the problem as a utility maximization framework with two sets of constraints: 1) capacity and schedulability constraints and 2) end-to-end delay constraints. By dual decomposition of the original optimization problem, we present a control algorithm that jointly tunes the flow rates and VLCMs, through a double-price scheme derived with regard to the constraints: the link congestion price reflecting the traffic load of a link, and the flow delay price reflecting the margin between the average packet delay and the delay requirement of a flow. We prove that the algorithm converges to a global optimum where the aggregate network utility defined over the flow rate set is maximized, while the delay constraints are satisfied. A key feature of our algorithm is it does not rely on a specific traffic model. The algorithm is implemented distributedly via joint wireless link scheduling and congestion control. Simulation results show that our algorithm outperforms heuristic rate allocation algorithms while satisfying the end-to-end delay constraints. This paper studies the problem of scheduling in single-hop wireless networks with real-time traffic, where every packet arrival has an associated deadline and a minimum fraction of packets must be transmitted before the end of the deadline. Using optimization and stochastic network theory we study the problem of scheduling to meet quality of service (QoS) requirements under heterogeneous delay constraints and time-varying channel conditions. Our analysis results in an optimal scheduling algorithm which fairly allocates data rates to all flows while meeting long-term delay demands. We also prove that under a simplified scenario our solution translates into a greedy strategy that makes optimal decisions with low complexity. Allocating limited resources such as bandwidth and power in a multi-hop wireless network can be formulated as a Network Utility Maximization (NUM) problem. In this approach, both transmitting source nodes and relaying link nodes exchange information allowing for the NUM problem to be solved in an iterative distributed manner. Some previous NUM formulations of wireless network problems have considered the parameters of data rate, reliability, and transmitter powers either in the source utility function which measures an application's performance or as constraints. However, delay is also an important factor in the performance of many applications. In this paper, we consider an additional constraint based on the average queueing delay requirements of the sources. In particular, we examine an augmented NUM formulation in which rate and power control in a wireless network are balanced to achieve bounded average queueing delays for sources. With the additional delay constraints, the augmented NUM problem is non-convex. Therefore, we present a change of variable to transform the problem to a convex problem and we develop a solution which results in a distributed rate and power control algorithm tailored to achieving bounded average queueing delays. Simulation results demonstrate the efficacy of the distributed algorithm. A fluid model of multi-class flows with priority packet scheduling is considered for controlling the flow rates, their end-to-end delays and their packet losses. We derive a globally stable distributed rate and delay combined control when no information time lags are present. By properly sizing the router buffers, the stable rates attain the end-to- end delay requirements without any packet loss. By further enhancing the network with bandwidth reservation and admission control, we also show that minimum rate is guaranteed. The stability properties of the discrete time version of our control are also derived when no information time lags are present. The stability in the presence of information time lags is studied numerically by computing the delay and rate trajectories for a real test-bed network.