Scheduling strategies to mitigate the impact of bursty traffic in wireless networks
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Modiano_Scheduling strategies.pdf
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Author(s)
Jagannathan, Krishna Prasanna
Jiang, Libin
Naik, Palthya Lakshma
Modiano, Eytan H.
Date Issued
May 2013
Journal
Proceedings of the 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Jagannathan, Krishna et al. "Scheduling strategies to mitigate the impact of bursty traffic in wireless networks." IEEE 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), 2013.
Version
Author's final manuscript
Abstract
Recent work has shown that certain queue-length based scheduling algorithms, such as max-weight, can lead to poor delays in the presence of bursty traffic. To overcome this
phenomenon, we consider the problem of designing scheduling policies that are robust to bursty traffic, while also amenable to practical implementation. Specifically, we discuss two mechanisms, one based on adaptive CSMA, and the second based on maximum-weight scheduling with capped queue lengths. We consider a simple queueing network consisting of two conflicting links. The traffic served by the first link is bursty, and is modeled as being heavy-tailed, while traffic at the second link is modeled using a light-tailed arrival process. In this setting, previous work has shown that even the light-tailed traffic would experience heavy-tailed delays under max-weight scheduling. In contrast, we demonstrate a threshold phenomenon in the relationship between the arrival rates and the queue backlog distributions. In particular, we show that with an adaptive CSMA scheme, when the arrival rate of the light-tailed traffic is less than a threshold value, the light-tailed traffic experiences a light-tailed queue backlog at steady state, whereas for arrival rates above the same threshold, the light-tailed traffic experiences a heavy-tailed queue backlog. We also show that a similar threshold behavior for max-weight scheduling with capped queue lengths
MIT Department
Massachusetts Institute of Technology. Communications and Networking Research Group
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6576469
