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Title

MAXIMIZATION OF SYSTEM UTILITY VALUE FOR TIME-SENSITIVE APPLICATIONS

Creator

Li, Shuhui

Date

2014, 2014-12

Description

Many applications are time-sensitive in the sense that the usefulness or the quality of their end results depends on their completion time....
Show moreMany applications are time-sensitive in the sense that the usefulness or the quality of their end results depends on their completion time. Examples of this type of applications are threat detections in air defense systems [97], radar trackings [36, 85], mobile navigations by Google [79, 44], and online gaming by Nintendo [38], to name a few. Take the threat detection application as an example, clearly, the earlier a threat is detected, the higher utility the application provides, as earlier detection provides more time to eliminate the threat [97]. This demonstrates the time-sensitivity of its utility. Here, the term `utility' means the actual bene t that accrues from the delivery of services [16]. The dependence between an application's accrued utility and its completion time is often modeled by a Time Utility Function (TUF). Apparently, when a system has multiple time-sensitive applications competing for the resources, a question arises: how to schedule their execution orders such that the system can yield maximal accrued utility? This thesis is to address the question. In this thesis, two categories of scheduling problems for time-sensitive applications are investigated: single-task applications in uni-processor systems and parallel multi-task applications in multi-processor systems. For the rst category, a two-TUF application model with given execution time is introduced and two scheduling algorithms for this model are proposed. Di erent from the conventional one-TUF model which only considers the gain utility, the developed model can deal with both the gain and the penalty utilities. The model is further extended to cope with applications whose exact execution times are not known at a priori, rather only their probabilistic execution time distributions are known. For applications with variable execution times, the di culty is how to make judicious decisions about when to start, continue or abort the applications. For the second category, i.e., for parallel multi-task applications in multi-processor systems, di erent from the widely investigated sequential multi-task applications, a parallel multi-task application's execution can have both spatial and temporal in uence on other applications. We propose a metric to measure the spatial-temporal interference among parallel multi-task and time-sensitive applications with respect to accrued utility. Based on the metric, a 2-approximation algorithm is introduced for systems operate in discrete time domains and its lower bound of system total accrued utility value is proved. We also develop a heuristic scheduling algorithm to maximize system's total accrued utility value for continuous time systems. Finally, the thesis discusses how methodologies developed in the thesis can be applied to reduce system's operational cost without sacri cing applications' quality of service. We propose a model to bridge together two orthogonal scheduling criteria, i.e., the system operational cost and application response time, and solve the problem by transforming it to a system accrued utility value optimization problem. The research uses both theoretical and experimental approaches. Theorems and lemmas are developed to provide the foundations for our solutions, and at the same time, extensive experiments are conducted to empirically evaluate the performances of the developed solutions.
Ph.D. in Computer Science, December 2014
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