Maximum throughput of multiple access channels in adversarial environments

We consider deterministic distributed broadcasting on multiple access channels in the framework of adversarial queuing. Packets are injected dynamically by an adversary that is constrained by the injection rate and the number of packets that may be injected simultaneously; the latter we call burstiness. A protocol is stable when the number of packets in queues at the stations stays bounded. The maximum injection rate that a protocol can handle in a stable manner is called the throughput of the protocol. We consider adversaries of injection rate 1, that is, of one packet per round, to address the question if the maximum throughput 1 can be achieved, and if so then with what quality of service. We develop a protocol that achieves throughput 1 for any number of stations against leaky-bucket adversaries. The protocol has $${\mathcal{O}(n^2+\text{burstiness})}$$ packets queued simultaneously at any time, where n is the number of stations; this upper bound is proved to be best possible. A protocol is called fair when each packet is eventually broadcast. We show that no protocol can be both stable and fair for a system of at least two stations against leaky-bucket adversaries. We study in detail small systems of exactly two and three stations against window adversaries to exhibit differences in quality of broadcast among classes of protocols. A protocol is said to have fair latency if the waiting time of packets is $${\mathcal{O}(\text{burstiness})}$$. For two stations, we show that fair latency can be achieved by a full sensing protocol, while there is no stable acknowledgment based protocol. For three stations, we show that fair latency can be achieved by a general protocol, while no full sensing protocol can be stable. Finally, we show that protocols that either are fair or do not have the queue sizes affect the order of transmissions cannot be stable in systems of at least four stations against window adversaries.

[1]  Aravind Srinivasan,et al.  Contention resolution with constant expected delay , 2000, JACM.

[2]  Adi Ros A Note on Models for Non-Probabilistic Analysis of Packet-Switching Networks , 2002 .

[3]  中村 修,et al.  20世紀の名著名論:Robert M. Metcalfe and David R. Boggs : Ethernet : Distributed Packet Switching for Local Computer Networks , 2003 .

[4]  Robert G. Gallager,et al.  A perspective on multiaccess channels , 1984, IEEE Trans. Inf. Theory.

[5]  Andrzej Lingas,et al.  Performing work in broadcast networks , 2005, Distributed Computing.

[6]  Sampath Kannan,et al.  A bound on the capacity of backoff and acknowledgment-based protocols , 2004, SIAM J. Comput..

[7]  Ashish Goel,et al.  Instability of FIFO at Arbitrarily Low Rates in the Adversarial Queueing Model , 2004, SIAM J. Comput..

[8]  Dariusz R. Kowalski,et al.  Broadcasting Spanning Forests on a Multiple-Access Channel , 2003, Theory of Computing Systems.

[9]  Maria J. Serna,et al.  A Characterization of Universal Stability in the Adversarial Queuing Model , 2004, SIAM J. Comput..

[10]  Boaz Patt-Shamir,et al.  New stability results for adversarial queuing , 2002, SPAA '02.

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

[12]  Ashish Goel,et al.  Instability of FIFO at arbitrarily low rates in the adversarial queuing model , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

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

[14]  Eli Upfal,et al.  Stochastic contention resolution with short delays , 1995, STOC '95.

[15]  Rafail Ostrovsky,et al.  Adaptive packet routing for bursty adversarial traffic , 1998, STOC '98.

[16]  David Gamarnik Stability of Adaptive and Nonadaptive Packet Routing Policies in Adversarial Queueing Networks , 2003, SIAM J. Comput..

[17]  Sampath Kannan,et al.  A Bound on the Capacity of Backoff and Acknowledgement-Based Protocols , 2000, ICALP.

[18]  Robert Metcalfe,et al.  Ethernet: distributed packet switching for local computer networks , 1988, CACM.

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

[20]  Paul G. Spirakis,et al.  The Impact of Network Structure on the Stability of Greedy Protocols , 2003, Theory of Computing Systems.

[21]  Frank Thomson Leighton,et al.  Analysis of Backoff Protocols for Multiple Access Channels , 1996, SIAM J. Comput..

[22]  Norman M. Abramson,et al.  Development of the ALOHANET , 1985, IEEE Trans. Inf. Theory.

[23]  Frank Thomson Leighton,et al.  Analysis of backoff protocols for multiple access channels , 1987, STOC '87.

[24]  Paul G. Spirakis,et al.  The Impact of Network Structure on the Stability of Greedy Protocols , 2003, CIAC.

[25]  Seif Haridi,et al.  Distributed Algorithms , 1992, Lecture Notes in Computer Science.

[26]  P. Ribenboim The new book of prime number records , 1996 .

[27]  Michael A. Bender,et al.  Adversarial contention resolution for simple channels , 2005, SPAA '05.