25-02-2013, 02:29 PM
ON WIRELESS SCHEDULING ALGORITHMS FOR MINIMIZING THE QUEUE-OVERFLOW PROBABILITY
ON WIRELESS SCHEDULING.doc (Size: 28 KB / Downloads: 19)
Abstract:
In this paper, we are interested in wireless scheduling algorithms for the downlink of a single cell that can minimize the queue-overflow probability. Specifically, in a large-deviation set-ting, we are nterested in algorithms that maximize the asymptotic decay rate of the queue-overflow probability, as the queue-over-flow threshold approaches infinity. We first derive an upper bound on the decay rate of the queue-overflow probability over all sched-uling policies. We then focus on a class of scheduling algorithms collectively referred to as the “ -algorithms.” For a given , the -algorithm picks the user for service at each time that has the largest product of the transmission rate multiplied by the backlog raised to the power . We show that when the overflow metric is appropriately modified, the minimum-cost-to-overflow under the -algorithm can be achieved by a simple linear path, and it can be written as the solution of a vector-optimization problem. Using this structural property, we then show that when approaches in-finity, the -algorithms asymptotically achieve the largest decay rate of the queue-overflow probability. Finally, this result enables us to design scheduling algorithms that are both close to optimal in terms of the asymptotic decay rate of the overflow probability and empirically shown to maintain small queue-overflow probabilities over queue-length ranges of practical interest.
Existing System:
The Constrained queuing system is used as a model of a radio networks, the server correspond to the link and the constraints disallows simultaneous transmission. At each time slot routing decision are taken for served customer and eligible set consider for activation.
Proposed System:
In scheduling algorithms collectively referred to as the “alpha algorithms.” For a given, the alpha algorithm picks the user for service at each time that has the largest product of the transmission rate. This result enables us to design scheduling algorithms that are both close to optimal in terms of the asymptotic decay rate of the overflow probability and empirically shown to maintain small queue-overflow probabilities over queue-length ranges of practical interest.
Request Send :
Here Client request will be send to Router with transmission Rate .For Example If client Request for Account summary that request will be processed through router with the transmission rate of the specific request in the router.
Queuing in Router :
Router design will contain the client name, requested service, Request status, Transmission rate and Server Name. In router request will be maintained in the queue until it reaches the threshold value, after it reaches the request will be processed based on the transmission rate.
Server Response
In this Server will get the details of the client request from the router based on the transmission each request will be served back to router and response will be send to client.
After receiving the response from the server it request status will be changed.