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A Pseudo-Bayesian ALOHA algorithm with mixed priorities
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IEEE/ACM Transactions on Networking (TON)
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IEEE/ACM Transactions on Networking (TON)
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An analysis of generalized slotted-Aloha protocols
IEEE/ACM Transactions on Networking (TON)
A distributed contention resolution algorithm in multi-packet reception ALOHA systems
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Lookup algorithm for adapting frame size in DFSA of passive UHF-GEN2 RFID
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Linear model of adapting frame size in DFSA of passive GEN2 RFID systems
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IEEE/ACM Transactions on Networking (TON)
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Bayesian estimation in dynamic framed slotted ALOHA algorithm for RFID system
Computers & Mathematics with Applications
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FASA: accelerated S-ALOHA using access history for event-driven M2M communications
IEEE/ACM Transactions on Networking (TON)
Hi-index | 754.84 |
A transmission control strategy is described for slotted-ALOHA-type broadcast channels with ternary feedback. At each time slot, each station estimates the probability that n stations are ready to transmit a packet for eachn, using Bayes' rule and the observed history of collisions, successful transmissions, and holes (empty slots). A station transmits a packet in a probabilistic manner based on these estimates. This strategy is called Bayesian broadcast. An elegant and very practical strategy--pseudo-Bayesian broadcast--is then derived by approximating the probability estimates with a Poisson distribution with meannuand further simplifying. Each station keeps a copy ofnu, transmits a packet with probability1/nu, and then updatesnuin two steps: For collisions, incrementnuby(e-2)^{-l}=1.39221 cdots. For successes and holes, decrementnuby1. Setnutomax (nu + hat{lambda}, 1), wherehat{lambda}is an estimate of the arrival ratelambdaof new packets into the system. Simulation results are presented showing that pseudo-Bayesian broadcast performs well in practice, and methods that can be used to prove that certain versions of pseudo-Bayesian broadcast are stable forlambda < e^{-1}are discussed.