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In the paper, we consider the dynamic, elastic and flexible task scheduling problem in hybrid clouds. Tasks are linearly dependent, compute-intensive, stochastic, deadline-constrained and executed on elastic and distributed cloud resources. The objective is to finish all jobs before their deadlines with renting virtual machines as less as possible. Firstly, we propose two simple and fast dispatching...
In this paper, we consider the widespread multi-stage job scheduling problem (e.g., in big data processed by MapReduce) in which jobs arrive at hybrid cloud systems stochastically. The objective is to minimize the number of elastic computing instances. Along with hard deadlines of jobs, the problem under study is NP-hard in strong sense. In terms of initial job priorities, timetables are constructed...
In XaaS clouds, resources as services (e.g., infrastructure, platform and software as a service) are sold to applications such as scientific and big data analysis workflows. Candidate services with various configurations (CPU type, memory size, number of machines and so on) for the same task may have different execution time and cost. Further, some services are priced rented by intervals that be shared...
In this paper, the service scheduling problem with start time constraints is considered for distributed collaborative manufacturing systems, which is different from the discrete time-cost tradeoff problem (DTCTP), well studied during the past decades. The assumption that the ability of services is unlimited in DTCTP is seldom true for practical settings. The fact that most services have limited capabilities,...
In Database-as-a-Service (DBaaS), a large number of tenants share DBaaS resources (CPU, I/O and Memory). While the DBaaS provider runs DBaaS to "share" resources across the entire tenant population to maximize resource utilization and minimize cost, the tenants subscribe to DBaaS at a low price point while still having resources conceptually "isolated" according to service level...
Service resources allocation and scheduling is one of the challenging and complex problems in computation-economy-driven open grid service architecture. This paper proposes a time-cost tradeoff workflow scheduling algorithm in which cost is optimized for schedules with the expectation to minimize workflow duration. Dynamic service selection strategy is adopted to adapt to dynamic shared and autonomous...
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