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2016
DOI: 10.1007/978-3-319-47217-1_14
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Some Applications of Multiple Classes G-Networks with Restart

Abstract: Abstract.We show how to model system management tasks such as load-balancing and delayed download with backoff penalty using G-networks with restart. We use G-networks with a restart signal, multiple classes or positive customers, PS discipline and arbitrary PH service distribution. The restart signal models the possibility to abort a task and send it again after changing its class and its service distribution. These networks have been proved to have a product form steady-state distribution.

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Cited by 4 publications
(4 citation statements)
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“…Stability conditions for G-networks were given in [58]. Multiple class models and relevant work were developed in a series of papers [12,22,23,47,95]. A special type of customer known as a "trigger" which is able to push an existing customer at a queue to another queue was introduced in [30].…”
Section: G-networkmentioning
confidence: 99%
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“…Stability conditions for G-networks were given in [58]. Multiple class models and relevant work were developed in a series of papers [12,22,23,47,95]. A special type of customer known as a "trigger" which is able to push an existing customer at a queue to another queue was introduced in [30].…”
Section: G-networkmentioning
confidence: 99%
“…There are also other G-network models. For instance, G-networks with "resets" [42,70], with "adders" [20] and with restarts [22,23], which have been developed and adopted in a number of applications in computer systems modeling and other fields.…”
Section: G-networkmentioning
confidence: 99%
See 1 more Smart Citation
“…When "adder" [8] which is another type of customer arrives at a service center, it acts as a load regulator to probabilistically change the queue length at the service center. G-networks have also been applied to restart problems [9,10] where the user can abort and resubmit a running job which exceeds a deadline. The tandem G-networks were investigated to study the response time probability distribution in [40] and the computer networks with blocking in [36].…”
Section: Introductionmentioning
confidence: 99%