Measuring the Impact of Adversarial Errors on Packet Scheduling Strategies
In this paper we explore the problem of achieving efficient packet transmission over unreliable links with worst case occurrence of errors. In such a setup, even an omniscient offline scheduling strategy cannot achieve stability of the packet queue, nor is it able to use up all the available bandwidth. Hence, an important first step is to identify an appropriate metric for measuring the efficiency of scheduling strategies in such a setting. To this end, we propose a relative throughput metric which corresponds to the long term competitive ratio of the algorithm with respect to the optimal. We then explore the impact of the error detection mechanism and feedback delay on our measure. We compare instantaneous error feedback with deferred error feedback, that requires a faulty packet to be fully received in order to detect the error. We propose algorithms for worst-case adversarial and stochastic packet arrival models, and formally analyze their performance. The relative throughput achieved by these algorithms is shown to be close to optimal by deriving lower bounds on the relative throughput of the algorithms and almost matching upper bounds for any algorithm in the considered settings. Our collection of results demonstrate the potential of using instantaneous feedback to improve the performance of communication systems in adverse environments.
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- 1.Ajtai, M., Aspnes, J., Dwork, C., Waarts, O.: A theory of competitive analysis for distributed algorithms. In: 1994 Proceedings of the 35th Annual Symposium on Foundations of Computer Science, pp. 401–411. IEEE (1994)Google Scholar
- 3.Anta, A.F., Georgiou, C., Kowalski, D.R., Widmer, J., Zavou, E.: Measuring the impact of adversarial errors on packet scheduling strategies. ArXiv (2013)Google Scholar
- 4.Awerbuch, B., Kutten, S., Peleg, D.: Competitive distributed job scheduling. In: Proceedings of the Twenty-fourth Annual ACM Symposium on Theory of Computing, pp. 571–580. ACM (1992)Google Scholar
- 6.Kesselheim, T.: Dynamic packet scheduling in wireless networks. In: PODC, pp. 281–290 (2012)Google Scholar
- 8.Meiners, C., Torng, E.: Mixed criteria packet scheduling. In: Algorithmic Aspects in Information and Management, pp. 120–133 (2007)Google Scholar
- 9.Pinedo, M.L.: Scheduling: theory, algorithms, and systems. Springer (2012)Google Scholar
- 10.Pruhs, K., Torng, E., et al.: Online scheduling (2007)Google Scholar
- 12.Richa, A., Scheideler, C., Schmid, S., Zhang, J.: Competitive throughput in multi-hop wireless networks despite adaptive jamming. In: Distributed Computing, pp. 1–13 (2012)Google Scholar