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Full-Text Articles in Physical Sciences and Mathematics
Scheduling Many-Task Computing Applications For A Hybrid Cloud, Shifat Perveen Mithila
Scheduling Many-Task Computing Applications For A Hybrid Cloud, Shifat Perveen Mithila
LSU Doctoral Dissertations
A centralized scheduler can become a bottleneck for placing the tasks of a many-task application on heterogeneous cloud resources. Previously, it was demonstrated that a decentralized vector scheduling approach based on performance measurements can be used successfully for this task placement scenario. In this dissertation, we extend this approach to task placement based on latency measurements. Each node collects performance metrics from its neighbors on an overlay graph, measures the communication latency, and then makes local decisions on where to move tasks. We present a decentralized and a centralized algorithm for configuring the overlay graph based on latency measurements and …
Decentralized Scheduling For Many-Task Applications In The Hybrid Cloud, Brian Lyle Peterson
Decentralized Scheduling For Many-Task Applications In The Hybrid Cloud, Brian Lyle Peterson
LSU Doctoral Dissertations
While Cloud Computing has transformed how we solve many computing tasks, some scientific and many-task applications are not efficiently executed on cloud resources. Decentralized scheduling, as studied in grid computing, can provide a scalable system to organize cloud resources and schedule a variety of work. By measuring simulations of two algorithms, the fully decentralized Organic Grid, and the partially decentralized Air Traffic Controller from IBM, we establish that decentralization is a workable approach, and that there are bottlenecks that can impact partially centralized algorithms. Through measurements in the cloud, we verify that our simulation approach is sound, and assess the …