Adaptive connection management for mission critical applications over ATM networks

Sahoo, Anirudha; Devalla, B.; Guan, Yong Liang; Bettati, Riccardo; Zhao, Wei

doi:10.1109/naecon.1998.710107

Cited by 7 publications

(1 citation statement)

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“…Sample systems range from embedded subsystems like communication infrastructures [11,2,22], to embedded systems composed of a moderate number of tasks running on homogeneous platforms, like radar [14] and robot control systems [23], and to systems composed of dynamic sets of components executing on heterogeneous distributed computing platforms, like the Navy Surface Combatant Ship SC-21 [10]. In such systems, unexpected workloads are caused by new application arrivals and, more critically, by changes in the resource requirements of existing applications.…”

Section: Introductionmentioning

confidence: 99%

FARACost: an adaptation cost model aware of pending constraints

Rosu

Schwan²

Proceedings 20th IEEE Real-Time Systems Symposium (Cat. No.99CB37054)

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The perturbations induced by adaptation and resource allocation decisions on the adapted applications may have the undesirable side effect of causing timing constraint failures. In order to benefit from available adaptation capabilities yet avoid critical timing failures, the dynamic resource allocation mechanism should be aware of the perturbation induced by its decisions. Therefore, the impact of adaptation on short-term performance should be considered a first-class decision criterion, along with traditional criteria such as long-term performance and application criticality. Towards this end, we propose the FARACost, an adaptation cost model that captures the impact of application-specific adaptation procedures and uses this information to evaluate adaptation choices. Experimental evaluations with two applications demonstrate that the use of models like FARACost reduces or prevents pending timing constraint failures, while leading to long-term performance improvements. The experiments are conducted in a cluster environment with a fully implemented infrastructure for adaptation and resource allocation based on the FARA framework.

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