Cloud workflow scheduling with deadlines and time
slot availability
Abstract
Allocating service capacities in cloud
computing is based on the assumption that they are unlimited and can be used at
any time. However, available service capacities change with workload and cannot
satisfy users’ requests at any time from the cloud provider’s perspective
because cloud services can be shared by multiple tasks. Cloud service providers
provide available time slots for new user’s requests based on available capacities.
In this paper, we consider workflow scheduling with deadline and time slot availability
in cloud computing. An iterated heuristic framework is presented for the
problem under study which mainly consists of initial solution construction,
improvement, and perturbation. Three initial solution construction strategies,
two greedy- and fair-based improvement strategies and a perturbation strategy
are proposed. Different strategies in the three phases result in several
heuristics. Experimental results show that different initial solution and
improvement strategies have different effects on solution qualities.
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