Analysis of Backoff Protocols for Mulitiple AccessChannels
SIAM Journal on Computing
Online computation and competitive analysis
Online computation and competitive analysis
Journal of the ACM (JACM)
Universal-stability results and performance bounds for greedy contention-resolution protocols
Journal of the ACM (JACM)
Competitive on-line switching policies
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Deterministic broadcast on multiple access channels
INFOCOM'10 Proceedings of the 29th conference on Information communications
Competitive and Fair Medium Access Despite Reactive Jamming
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
A perspective on multiaccess channels
IEEE Transactions on Information Theory
Performance analysis of the IEEE 802.11 distributed coordination function
IEEE Journal on Selected Areas in Communications
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We consider the problems of online and stochastic packet queuing in a distributed system of n nodes with queues, where the communication between the nodes is done via a multiple access channel. In each round, an arbitrary number of packets can be injected into the system, each to an arbitrary node's queue. Two measures of performance are considered: the total number of packets in the system, called the total load, and the maximum queue size, called the maximum load. In the online setting, we develop a deterministic algorithm that is asymptotically optimal with respect to both complexity measures, in a competitive way. More precisely, the total load of our algorithm is bigger then the total load of any other algorithm, including centralized offline solutions, by only O(n2), while the maximum queue size of our algorithm is at most n times bigger than the maximum queue size of any other algorithm, with an extra additive O(n). The optimality for both measures is justified by proving the corresponding lower bounds. Next, we show that our algorithm is stochastically optimal for any expected injection rate smaller or equal to 1. To the best of our knowledge, this is the first solution to the stochastic queuing problem on a multiple access channel that achieves such optimality for the (highest possible) rate equal to 1.