Search

Most existing wireless networking solutions are best-effort and do not provide any delay guarantee required by important applications, such as mobile multimedia conferencing and real-time control of cyber-physical systems. Recently, Hou and Kumar provided a novel framework for analyzing and designing delay-guaranteed wireless networking solutions. While inspiring, their idle-time-based analysis applies only to flows with a special traffic pattern called the frame-synchronized setting. The problem remains largely open for general traffic patterns. This paper addresses this challenge by proposing a general framework that characterizes and achieves the complete delay-constrained capacity region with general traffic patterns in single-hop downlink access-point wireless networks. We first show that the timely wireless flow problem is fundamentally an infinite-horizon Markov decision process (MDP). Then, we judiciously combine different simplification methods to prove that the timely capacity region can be characterized by a finite-size convex polygon. This for the first time allows us to characterize the timely capacity region of wireless flows with general traffic patterns. We then design three scheduling policies to optimize network utility and/or support feasible timely throughput vectors for general traffic patterns. The first policy achieves the optimal network utility and supports any feasible timely throughput vector but suffers from the curse of dimensionality. The second and third policies are inspired by our MDP framework and are of much lower complexity. Simulation results show that both achieve near-optimal performance and outperform other existing alternatives. [ABSTRACT FROM PUBLISHER]

In this paper, we study the problem of link scheduling for multi-hop wireless networks with per-flow delay constraints under the K-hop interference model. Specifically, we are interested in algorithms that maximize the asymptotic decay-rate of the probability with which the maximum end-to-end backlog among all flows exceeds a threshold, as the threshold becomes large. We provide both positive and negative results in this direction. By minimizing the drift of the maximum end-to-end backlog in the converge-cast on a tree, we design an algorithm, Largest-Weight-First (LWF), that achieves the optimal asymptotic decay-rate for the overflow probability of the maximum end-to-end backlog as the threshold becomes large. However, such a drift minimization algorithm may not exist for general networks. We provide an example in which no algorithm can minimize the drift of the maximum end-to-end backlog. Finally, we simulate the LWF algorithm together with a well known algorithm (the back-pressure algorithm) and a large-deviations optimal algorithm in terms of the sum-queue (the P-TREE algorithm) in converge-cast networks. Our simulation shows that our algorithm performs significantly better not only in terms of asymptotic decay-rate, but also in terms of the actual overflow probability. [ABSTRACT FROM AUTHOR]

We study the delay performance in large-scale wireless multihop networks with unreliable links from percolation perspective. Previous works have showed that the end-to-end delay scales linearly with the source-to-destination distance, and thus the delay performance can be characterized by the delay–distance ratio \gamma. However, the range of \gamma, which may be the most important parameter for delay, remains unknown. We expect that \gamma may depend heavily on the node density \lambda of a wireless multihop network. In this paper, we investigate the fundamental relationship between \gamma and \lambda. Obtaining the exact value of \gamma(\lambda) is extremely hard, mainly because of the dynamically changing network topologies caused by the link unreliability. Instead, we provide both upper bound and lower bound to the delay–distance ratio \gamma(\lambda). Simulations are conducted to verify our theoretical analysis. [ABSTRACT FROM PUBLISHER]