On packet scheduling with adversarial jamming and speedup

Author:

Böhm Martin,Jeż Łukasz,Sgall Jiří,Veselý PavelORCID

Abstract

AbstractIn Packet Scheduling with Adversarial Jamming, packets of arbitrary sizes arrive over time to be transmitted over a channel in which instantaneous jamming errors occur at times chosen by the adversary and not known to the algorithm. The transmission taking place at the time of jamming is corrupt, and the algorithm learns this fact immediately. An online algorithm maximizes the total size of packets it successfully transmits and the goal is to develop an algorithm with the lowest possible asymptotic competitive ratio, where the additive constant may depend on packet sizes. Our main contribution is a universal algorithm that works for any speedup and packet sizes and, unlike previous algorithms for the problem, it does not need to know these parameters in advance. We show that this algorithm guarantees 1-competitiveness with speedup 4, making it the first known algorithm to maintain 1-competitiveness with a moderate speedup in the general setting of arbitrary packet sizes. We also prove a lower bound of $$\phi +1\approx 2.618$$ ϕ + 1 2.618 on the speedup of any 1-competitive deterministic algorithm, showing that our algorithm is close to the optimum. Additionally, we formulate a general framework for analyzing our algorithm locally and use it to show upper bounds on its competitive ratio for speedups in [1, 4) and for several special cases, recovering some previously known results, each of which had a dedicated proof. In particular, our algorithm is 3-competitive without speedup, matching both the (worst-case) performance of the algorithm by Jurdzinski et al. (Proceedings of the 12th workshop on approximation and online algorithms (WAOA), LNCS 8952, pp 193–206, 2015. http://doi.org/10.1007/978-3-319-18263-6_17) and the lower bound by Anta et al. (J Sched 19(2):135–152, 2016. http://doi.org/10.1007/s10951-015-0451-z).

Funder

Polish National Science Center

Grantová Agentura Èeské Republiky

Grantová Agentura, Univerzita Karlova

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,General Decision Sciences

Reference19 articles.

1. Anta, A. F., Georgiou, C., Kowalski, D. R., Widmer, J., & Zavou, E. (2016). Measuring the impact of adversarial errors on packet scheduling strategies. Journal of Scheduling, 19(2), 135–152. Also appeared in Proceedings of SIROCCO 2013 (pp. 261–273). http://doi.org/10.1007/s10951-015-0451-z.

2. Anta, A. F., Georgiou, C., Kowalski, D. R., & Zavou, E. (2015). Online parallel scheduling of non-uniform tasks: Trading failures for energy. Theoretical Computer Science, 590, 129–146. Also appeared in Proceedings of FCT 2013 (pp. 145–158). http://doi.org/10.1016/j.tcs.2015.01.027.

3. Anta, A. F., Georgiou, C., Kowalski, D. R., & Zavou, E. (2018). Competitive analysis of fundamental scheduling algorithms on a fault-prone machine and the impact of resource augmentation. Future Generation Computer Systems, 78, 245–256. Also appeared in Proceedings of the 2nd international workshop on adaptive resource management and scheduling for cloud computing (ARMS-CC@PODC 2015), LNCS 9438 (pp. 1–16). http://doi.org/10.1016/j.future.2016.05.042.

4. Ben-David, S., Borodin, A., Karp, R. M., Tardos, G., & Wigderson, A. (1994). On the power of randomization in on-line algorithms. Algorithmica, 11(1), 2–14. https://doi.org/10.1007/BF01294260.

5. Böhm, M., Jeż, Ł., Sgall, J., & Veselý, P. (2018). On packet scheduling with adversarial jamming and speedup. In Proceedings of the 15th international workshop on approximation and online algorithms (WAOA) (pp. 190–206). http://doi.org/10.1007/978-3-319-89441-6_15.

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