Proceedings of Fourth International Conference on Computer Communications and Networks - IC3N'95
DOI: 10.1109/icccn.1995.540168
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Scheduling for quality of service guarantees via service curves

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Cited by 85 publications
(60 citation statements)
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“…The concepts of service and arrival curves have been used by Cruz and Sariowan [31], [32], Georgiadis, Guérin, Peris and Rajan [12] to design schedulers that optimize the combination of delay guarantees, buffer and bit rate requirements, and go beyond the initial design ideas of Kalmanek, Kanakia and Restrick [10] and H. Zhang and Ferrari [11]. Some of these schedulers are designed to have have service curves that are not ratelatency, therefore, their properties are not well exploited within the IntServ framework.…”
Section: B Intserv and Service Curvesmentioning
confidence: 99%
“…The concepts of service and arrival curves have been used by Cruz and Sariowan [31], [32], Georgiadis, Guérin, Peris and Rajan [12] to design schedulers that optimize the combination of delay guarantees, buffer and bit rate requirements, and go beyond the initial design ideas of Kalmanek, Kanakia and Restrick [10] and H. Zhang and Ferrari [11]. Some of these schedulers are designed to have have service curves that are not ratelatency, therefore, their properties are not well exploited within the IntServ framework.…”
Section: B Intserv and Service Curvesmentioning
confidence: 99%
“…The idea of modeling schedulers with service constraint functions originated in [22], [23], [24], [25], [28], [29], and [45]. Workload and service constraint functions have been used for the direct schedulability test in [45], [46], [47], [48], [49], [50], [51], [52], [53] among many others, but none of them are used for the utilization-based schedulability test.…”
Section: Related Workmentioning
confidence: 99%
“…This significantly complicates both the data and the control path implementations. For example, admission control requires checking whether a two-piece linear function representing the new reservation ever exceeds an n-piece linear function representing the available link resources (capacity), where, in the worst case, n represents the number of flows [90]. Thus, storing the representation of the available capacity requires an amount of state proportional to the number of flows, which is unacceptable for a stateless solution.…”
Section: Decoupling Bandwidth and Delay Allocationsmentioning
confidence: 99%
“…In the stateful world, several solutions have been proposed to address this problem [90,106,124]. A future direction would be to emulate these solutions in the SCORE/DPS framework.…”
Section: Decoupling Bandwidth and Delay Allocationsmentioning
confidence: 99%