DocumentCode :
2474546
Title :
Practical solutions for QoS-based resource allocation problems
Author :
Rajkumar, Ragunathan Raj ; Lee, Chen ; Lehoczky, J.P. ; Siewiorek, Daniel P.
Author_Institution :
Dept. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
1998
fDate :
2-4 Dec 1998
Firstpage :
296
Lastpage :
306
Abstract :
The QoS based Resource Allocation Model (Q-RAM) proposed by R. Rajkumar et al. (1998) presented an analytical approach for satisfying multiple quality of service dimensions in a resource constrained environment. Using this model, available system resources can be apportioned across multiple applications such that the net utility that accrues to the end users of those applications is maximized. We present several practical solutions to allocation problems that were beyond the limited scope of Q-RAM. We show that the Q-RAM problem of finding the optimal resource allocation to satisfy multiple QoS dimensions is NP hard. We then present a polynomial solution for this resource allocation problem which yields a solution within a provably fixed and short distance from the optimal allocation. Secondly, Q-RAM dealt mainly with the problem of apportioning a single resource to satisfy multiple QoS dimensions. We study the converse problem of apportioning multiple resources to satisfy a single QoS dimension. In practice, this problem becomes complicated, since a single QoS dimension perceived by the user can be satisfied using different combinations of available resources. We show that this problem can be formulated as a mixed integer programming problem that can be solved efficiently to yield an optimal resource allocation. We also present the run times of these optimizations to illustrate how these solutions can be applied in practice. A good understanding of these solutions will yield insights into the general problem of apportioning multiple resources to satisfy simultaneously multiple QoS dimensions of multiple concurrent applications
Keywords :
computational complexity; integer programming; quality of service; resource allocation; NP hard; QoS based Resource Allocation Model; QoS based resource allocation problems; QoS dimensions; analytical approach; mixed integer programming problem; multiple QoS dimensions; multiple concurrent applications; multiple quality of service dimensions; multiple resources; optimal allocation; optimal resource allocation; polynomial solution; resource allocation problem; resource constrained environment; run times; single QoS dimension; system resources; Computer science; Control systems; Delay; Electrical capacitance tomography; Operating systems; Polynomials; Radar tracking; Read-write memory; Resource management; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Real-Time Systems Symposium, 1998. Proceedings., The 19th IEEE
Conference_Location :
Madrid
Print_ISBN :
0-8186-9212-X
Type :
conf
DOI :
10.1109/REAL.1998.739755
Filename :
739755
Link To Document :
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