Wireless Scheduling Design for Optimizing Both Service Regularity and Mean Delay in Heavy-Traffic Regimes
Wireless Scheduling Design for Optimizing Both Service Regularity and Mean Delay in Heavy-Traffic Regimes
复制标题
用于优化大流量情况下的服务规律性和平均延迟的无线调度设计
DOI：
10.1109/tnet.2015.2432119
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
A. Eryilmaz
中科院分区：
文献类型：
--
作者：
Bin Li;Ruogu Li;A. Eryilmaz
我们认为，在多跳无线网络的吞吐量最优调度策略的设计，也具有良好的平均延迟性能，并提供定期服务的所有链路的关键指标的实时应用程序。为此，我们研究了一个参数类的最大权重类型的调度策略，称为定期服务保证（RSG）算法，其中每个链接的权重包括自己的队列长度和一个计数器，跟踪时间，因为最后一次服务，即时间，因为最后一次服务（TSLS）。RSG算法不仅是吞吐量最优的，而且实现了服务规则性性能和平均延迟之间的折衷，即，RSG算法的服务规则性是以增加平均时延为代价的。这促使我们调查是否满意的服务规律性和低平均延迟可以同时通过RSG算法，仔细选择其设计参数。为此，我们进行了一种新的基于Lyapunov漂移的随机网络的稳态行为的分析。我们的分析表明，RSG算法可以最小化总的平均队长，建立平均延迟最优的重负载条件下，只要设计参数的加权TSLS的规模不快于[1/（{5}<${ε}）]的顺序，其中ε衡量的网络负载的能力区域的边界的接近程度。据我们所知，这是第一个工作，提供定期服务的所有链接，同时也实现了平均队列长度的大流量最优。
We consider the design of throughput-optimal scheduling policies in multihop wireless networks that also possess good mean delay performance and provide regular service for all links-critical metrics for real-time applications. To that end, we study a parametric class of maximum-weight-type scheduling policies, called Regular Service Guarantee (RSG) Algorithm, where each link weight consists of its own queue length and a counter that tracks the time since the last service, namely Time-Since-Last-Service (TSLS). The RSG Algorithm not only is throughput-optimal, but also achieves a tradeoff between the service regularity performance and the mean delay, i.e., the service regularity performance of the RSG Algorithm improves at the cost of increasing mean delay. This motivates us to investigate whether satisfactory service regularity and low mean-delay can be simultaneously achieved by the RSG Algorithm by carefully selecting its design parameter. To that end, we perform a novel Lyapunov-drift-based analysis of the steady-state behavior of the stochastic network. Our analysis reveals that the RSG Algorithm can minimize the total mean queue length to establish mean delay optimality under heavily loaded conditions as long as the design parameter weighting for the TSLS scales no faster than the order of [1/({5}√{ε})], where ε measures the closeness of the network load to the boundary of the capacity region. To the best of our knowledge, this is the first work that provides regular service to all links while also achieving heavy-traffic optimality in mean queue lengths.