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Mobile Wireless Communications using visual studio .net todraw barcode standards 128 on asp.net web,windows application Barcodes for Mobile Applications scheduling pr Code128 for .NET ocedures proposed in these papers, each of which builds on the one appearing before. Consider Kalia et al.

(2000) rst. It is assumed in this paper that a backlogged slave, i.e.

, one with further data to send, so indicates to the master by setting a bit in its reply packet when polled by the master. (Note that this approach is somewhat similar to the one adopted for DQRUMA, described in 11.) The master can then distinguish between backlogged slaves and those with nothing to send.

There are clearly four categories of master slave pairs now resulting: pairs with both master and slave waiting to transmit a packet to the other, referred to as the 1 1 state; pairs with the master only ready to transmit a packet to the slave, the slave having nothing to transmit, the 1 0 state; pairs with the reverse the master has no data to send to the slave, while the slave is ready to transmit, but can only do so on being polled, the 0 1 state; and the nal category with neither device having anything to transmit, 0 0. Kalia et al. propose two scheduling policies that use this information, and compare them with pure round-robin scheduling.

The rst policy is called a Priority Policy, PP, in which the 1 1 state, with both master and slave backlogged, is given priority over the other states, using a variable priority parameter; slaves in the 0 0 state, with neither the master nor the slave having anything to transmit, are skipped over and not polled at all. The second policy, called a K-Fairness Policy, KFP, carries out round-robin scheduling over the three states 1 1, 1 0, and 0 1, allowing the devices in the 1 1 state to receive longer service, but not more than K slots, K a parameter. Their simulations then show that the KFP procedure provides a higher throughput than the PP procedure and provides a better measure of fairness.

Both procedures perform better than the pure round-robin one. Capone et al. (2001) builds on Kalia et al.

(2000), pointing out that a master s knowledge of the backlogged state of a given slave is not always accurate, a slave having indicated it had nothing to send when last polled, having perhaps become backlogged in the interim. They then propose a number of procedures that do not rely on knowledge of slave queues, comparing them with idealized strategies in which the master is assumed to have knowledge of slave queues. These procedures are based on optimum polling strategies proposed previously in the literature.

One such scheme is exhaustive round robin, ERR, in which all packets queued at a given device are transmitted before moving on to the next device in the round-robin cycle. This strategy is obviously not fair, since a master slave pair in this case could capture the channel. To avoid this problem and introduce a measure of fairness, the authors propose a modi ed procedure, Limited Round Robin, LRR, with a given pair limited in the number of packets they can transmit.

A modi ed version of this polling strategy, Limited and Weighted Round Robin, LWRR, applies a priority weight to a station, depending on the observed queue status. A station is rst given the maximum weight, MP. This weight is reduced by 1 each time the station is polled and no data are exchanged.

Once the weight reaches the lowest value of 1, it is not polled again for MP-1 cycles, potentially leading to long waits. Any time data are exchanged during a poll, however, the weight is increased again to MP. The focus in comparatively evaluating these various algorithms was packet delay.

Simulation studies indicated that the exhaustive round-robin procedure performed almost as well as an idealized scheme in which the master, assumed to know the queue lengths at all slave stations, serves slaves exhaustively in order of the summed length of master to.
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