Adaptive packet scheduling over a wireless channel under constrained jamming

In this work we consider the communication over a wireless link, between a sender and a receiver, being disrupted by a jammer. The objective of the sender is to transmit as much data as possible to the receiver in the most efficient way. The data is sent as the payload of packets, and becomes useless if the packet is jammed. We consider a jammer with constrained power, defined by parameters and , which represent the rate at which the adversary may jam the channel, and the length of the largest burst of jams it can cause, respectively. This definition translates to the Adversarial Queuing Theory (AQT) constraints, typically used for packet arrivals.We propose deterministic algorithms that decide the length of the packets sent in order to maximize the goodput rate; i.e., the amount of useful payload successfully transmitted over time. To do so, we first define and study a static version of the problem, which is used as a building block for the dynamic problem. We start by assuming packets of the same length and characterizing the corresponding quasi-optimal length. Then, we show that by adapting the length of the packets, the goodput rate can be improved. Hence, we develop optimal adaptive algorithms that choose the packet lengths depending on the jams that have occurred up to that point in time, in order to maximize the total payload transmitted successfully over a period T in the presence of up to f jams.

[1]  Christian Scheideler,et al.  Competitive and fair throughput for co-existing networks under adversarial interference , 2012, PODC '12.

[2]  Rachid Guerraoui,et al.  Of malicious motes and suspicious sensors: On the efficiency of malicious interference in wireless networks , 2009, Theor. Comput. Sci..

[3]  Kirk Pruhs Competitive online scheduling for server systems , 2007, PERV.

[4]  Christian Scheideler,et al.  Competitive MAC under adversarial SINR , 2013, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[5]  Stefan Schmid,et al.  Dynamic Internet Congestion with Bursts , 2006, HiPC.

[6]  Dariusz R. Kowalski,et al.  Stability of Adversarial Routing with Feedback , 2013, NETYS.

[7]  Zhenyu Guo,et al.  Risk analysis of Unmanned Aerial Vehicle hijacking and methods of its detection , 2013, 2013 IEEE Systems and Information Engineering Design Symposium.

[8]  David J. Thuente,et al.  Intelligent jamming in wireless networks with applications to 802.11b and other networks , 2006 .

[9]  Christian Scheideler,et al.  A jamming-resistant MAC protocol for single-hop wireless networks , 2008, PODC '08.

[10]  Allan Borodin,et al.  Adversarial queuing theory , 2001, JACM.

[11]  Elif Uysal-Biyikoglu,et al.  Energy-efficient packet transmission over a wireless link , 2002, TNET.

[12]  Chryssis Georgiou,et al.  Packet Scheduling over a Wireless Channel: AQT-Based Constrained Jamming , 2015, NETYS.

[13]  Baruch Awerbuch,et al.  Universal-stability results and performance bounds for greedy contention-resolution protocols , 2001, JACM.

[14]  Kirk Pruhs,et al.  Online scheduling , 2003 .

[15]  Dariusz R. Kowalski,et al.  Universal routing in multi hop radio network , 2014, FOMC '14.

[16]  Stefan Schmid,et al.  A TCP with guaranteed performance in networks with dynamic congestion and random wireless losses , 2006, WICON '06.

[17]  Dariusz R. Kowalski,et al.  Adversarial Queuing on the Multiple Access Channel , 2012, TALG.

[18]  Satish K. Tripathi,et al.  Enhancing throughput over wireless LANs using channel state dependent packet scheduling , 1996, Proceedings of IEEE INFOCOM '96. Conference on Computer Communications.

[19]  Dariusz R. Kowalski,et al.  Stability of the Multiple-Access Channel Under Maximum Broadcast Loads , 2007, SSS.

[20]  Leandros Tassiulas,et al.  Exploiting wireless channel State information for throughput maximization , 2004, IEEE Trans. Inf. Theory.

[21]  Srikanth V. Krishnamurthy,et al.  Denial of Service Attacks in Wireless Networks: The Case of Jammers , 2011, IEEE Communications Surveys & Tutorials.

[22]  Srinivasan Seshan,et al.  Understanding and mitigating the impact of RF interference on 802.11 networks , 2007, SIGCOMM 2007.

[23]  Christian Scheideler,et al.  Towards jamming-resistant and competitive medium access in the SINR model , 2011, S3 '11.

[24]  Michal Jakubiak Cellular network coverage analysis using UAV and SDR , 2015 .

[25]  Haiyun Luo,et al.  The impact of multihop wireless channel on TCP throughput and loss , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[26]  Antonio Fernández Anta,et al.  Relative Throughput - Measuring the Impact of Adversarial Errors on Packet Scheduling Strategies: Talk Announcement at the Ninth International Workshop on Foundations of Mobile Computing , 2013 .

[27]  Christian Scheideler,et al.  Competitive and Fair Medium Access Despite Reactive Jamming , 2011, 2011 31st International Conference on Distributed Computing Systems.

[28]  Dariusz R. Kowalski,et al.  Universal Routing in Multi-hop Radio Networks , 2016, ArXiv.

[29]  Rachid Guerraoui,et al.  Reliable distributed computing on unreliable radio channels , 2009, MobiHoc S3 '09.