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In this paper, we focus on strategy configurations of multiple users to make cloud service reservation. We consider the problem from a game theoretic perspective and formulate it into a non-cooperative game among the multiple cloud users, in which each user is informed with incomplete information of other users. For each user, we design a utility function(More)
The energy aware scheduling problem has been a critical issue in high-performance clusters owing to their high operation cost, environmental impact, and low reliability. An existing technique to reduce energy consumption of applications is dynamic voltage/frequency scaling (DVFS). In this paper, we develop an energy aware scheduling algorithm called EASLA(More)
Energy consumption has been a critical issue in high-performance computing systems, such as clusters and data centers. An existing technique to reduce energy consumption of applications is dynamic voltage/frequency scaling (DVFS). In this paper, we present a novel algorithm called EASLA for energy aware scheduling of precedence-constrained applications in(More)
In this paper, we propose a method about task scheduling and data assignment on heterogeneous hybrid memory multiprocessor systems for real-time applications. In a heterogeneous hybrid memory multiprocessor system, an important problem is how to schedule real-time application tasks to processors and assign data to hybrid memories. The hybrid memory consists(More)
In this paper, we focus on price bidding strategies of multiple users competition for resource usage in cloud computing. We consider the problem from a game theoretic perspective and formulate it into a non-cooperative game among the multiple cloud users, in which each cloud user is informed with incomplete information of other users. For each user, we(More)
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