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Traffic Management for the Available Bit Rate (ABR) Service in ...

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like ERICA+ which uses <strong>the</strong> queue<strong>in</strong>g delay to calculate feedback (<strong>in</strong> addition to<br />

<strong>in</strong>put rate etc). The basic ERICA algorithm without queue control cannot handle<br />

this level of variation.<br />

The ERICA+ algorithm uses <strong>the</strong> queue length as a secondary metric to reduce <strong>the</strong><br />

high allocation of rates. However, ERICA+ has a limit on how much it can reduce<br />

<strong>the</strong> allocation. Given su cient variation, <strong>the</strong> limit can be reached. This means that<br />

even <strong>the</strong> m<strong>in</strong>imum rate allocation by ERICA+ causes <strong>the</strong> queues to diverge. This<br />

reason, along with <strong>the</strong> discussion on ON-OFF times and feedback delays expla<strong>in</strong>s <strong>the</strong><br />

divergent cases <strong>in</strong> Tables 8.7 and 8.8.<br />

Reduc<strong>in</strong>g <strong>the</strong> E ects of Variation In ERICA+<br />

We tackle <strong>the</strong>se problems by reduc<strong>in</strong>g <strong>the</strong> e ect of variation on <strong>the</strong> scheme mea-<br />

surements <strong>in</strong> three ways (described <strong>in</strong> detail <strong>in</strong> chapter 6):<br />

1. First, we observethatoneway to reduce variation <strong>in</strong> measurements is to measure<br />

quantities over longer <strong>in</strong>tervals. Longer <strong>in</strong>tervals yield averages which have less<br />

variance. However, mak<strong>in</strong>g <strong>the</strong> <strong>in</strong>tervals too long <strong>in</strong>creases <strong>the</strong> response time,<br />

and queues may build up <strong>in</strong> <strong>the</strong> <strong>in</strong>terim.<br />

2. Second, we average <strong>the</strong> measurements over several successive <strong>in</strong>tervals. The<br />

ERICA scheme uses two important measurements: <strong>the</strong> overload factor (z)which<br />

is <strong>the</strong> ratio of <strong>the</strong> <strong>in</strong>put rate and <strong>the</strong> target <strong>ABR</strong> rate, and <strong>the</strong> numberofactive<br />

sources (Na). We re-exam<strong>in</strong>e how <strong>the</strong> scheme depends on <strong>the</strong>se metrics and<br />

design an appropriate averag<strong>in</strong>g technique <strong>for</strong> each of <strong>the</strong>m.<br />

The overload factor (z) is used to divide <strong>the</strong> current cell rate of <strong>the</strong> source<br />

to give what we call <strong>the</strong> \VC share". The VC share is one of <strong>the</strong> rates<br />

308

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