Optimal Resource Scheduling and Allocation in Distributed Computing Systems

TL;DR

This paper develops a cost-aware optimal scheduling and resource allocation strategy for distributed computing systems, minimizing response time and service costs through a combined policy and AIMD mechanism.

Contribution

It introduces a novel cost function-based approach and synchronously derives optimal scheduling and allocation policies, incorporating AIMD to adapt to request arrivals.

Findings

Optimal request scheduling policy derived

Resource allocation policy optimized for cost minimization

AIMD mechanism effectively models request arrival effects

Abstract

The essence of distributed computing systems is how to schedule incoming requests and how to allocate all computing nodes to minimize both time and computation costs. In this paper, we propose a cost-aware optimal scheduling and allocation strategy for distributed computing systems while minimizing the cost function including response time and service cost. First, based on the proposed cost function, we derive the optimal request scheduling policy and the optimal resource allocation policy synchronously. Second, considering the effects of incoming requests on the scheduling policy, the additive increase multiplicative decrease (AIMD) mechanism is implemented to model the relation between the request arrival and scheduling. In particular, the AIMD parameters can be designed such that the derived optimal strategy is still valid. Finally, a numerical example is presented to illustrate the derived results.