期刊
IEEE-ACM TRANSACTIONS ON NETWORKING
卷 24, 期 2, 页码 954-967出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNET.2015.2404852
关键词
Congestion control; delay optimal control; dynamic backpressure algorithms; dynamic programming; Lyapunov drift; throughput optimal control
类别
资金
- National Science Foundation of China [61401272]
- National Science Foundation [CNS-1205562]
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1423250] Funding Source: National Science Foundation
For general multi-hop queueing networks, delay optimal network control has unfortunately been an outstanding problem. The dynamic backpressure (BP) algorithm elegantly achieves throughput optimality, but does not yield good delay performance in general. In this paper, we obtain an asymptotically delay optimal control policy, which resembles the BP algorithm in basing resource allocation and routing on a backpressure calculation, but differs from the BP algorithm in the form of the backpressure calculation employed. The difference suggests a possible reason for the unsatisfactory delay performance of the BP algorithm, i.e., the myopic nature of the BP control. Motivated by this new connection, we introduce a new class of enhanced backpressure-based algorithms which incorporate a general queue-dependent bias function into the backpressure term of the traditional BP algorithm to improve delay performance. These enhanced algorithms exploit queue state information beyond one hop. We prove the throughput optimality and characterize the utility-delay tradeoff of the enhanced algorithms. We further focus on two specific distributed algorithms within this class, which have demonstrably improved delay performance as well as acceptable implementation complexity.
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