Broadcasting is an efficient and scalable way of transmitting data over wireless channels to an unlimited number of clients. In this paper the problem of allocating data to multiple channels is studied, assuming flat data scheduling per channel and the presence of unrecoverable channel transmission errors. The objective is that of min- imizing the average expected delay experienced by the clients. Two different channel error models are considered: the Bernoulli model and the simplified Gilbert-Elliot one. In the former model, each packet transmission has the same probability to fail and each transmission error is indepen- dent from the others. In the latter one, bursts of erroneous or error-free packet transmissions due to wireless fading channels are modeled. Particular cases are detected where optimal solutions can be found in polynomial time. For general cases, simulations show that good sub-optimal solutions can be found on benchmarks whose item popu- larities follow Zipf distributions.

Allocating data for broadcasting over wireless channels subject to transmission errors

Barsocchi P.;Potorti' F.
2010

Abstract

Broadcasting is an efficient and scalable way of transmitting data over wireless channels to an unlimited number of clients. In this paper the problem of allocating data to multiple channels is studied, assuming flat data scheduling per channel and the presence of unrecoverable channel transmission errors. The objective is that of min- imizing the average expected delay experienced by the clients. Two different channel error models are considered: the Bernoulli model and the simplified Gilbert-Elliot one. In the former model, each packet transmission has the same probability to fail and each transmission error is indepen- dent from the others. In the latter one, bursts of erroneous or error-free packet transmissions due to wireless fading channels are modeled. Particular cases are detected where optimal solutions can be found in polynomial time. For general cases, simulations show that good sub-optimal solutions can be found on benchmarks whose item popu- larities follow Zipf distributions.
2010
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Wireless communication
Data broadcasting
Multiple channels
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/40004
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