Micro service has been increasingly recognized as a promising architectural style for constructing large-scale cloud-based applications within and across organizational boundaries. This micro service-based architecture greatly increases application scalability, but mean while incurs an expensive performance overhead, which calls for a careful design of performance modeling and task scheduling.However, these problems have thus far remained largely unexplored. In this paper, we develop a performance modeling and prediction method for independent micro services, design a three-layer performance model for micro service-based applications, formulate a Micro service-based Application Workflow Scheduling problem for minimum end-to-end delay under a user-specified Budget Constraint (MAWS-BC), and propose a heuristic micro service scheduling algorithm. The performance modeling and prediction method are validated and justified by experimental results generated through a well-known micro service benchmark on disparate computing nodes, and the performance superiority of the proposed scheduling solution is illustrated by extensive simulation results in comparison with existing algorithms.
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