## Abstract

Today's large-scale parallel workflows are often processed on heterogeneous distributed computing platforms. From an economic perspective, computing resource providers should minimize the cost while offering high service quality. It has become well-recognized that energy consumption accounts for a large part of a computing system's total cost, and timeliness and reliability are two important service indicators. This work studies the problem of scheduling a parallel workflow that minimizes the system energy consumption under the constraints of response time and reliability. We first mathematically formulate this problem as a Non-linear Mixed Integer Programming problem. Since this problem is hard to solve directly, we present some highly-efficient heuristic solutions. Specifically, we first develop an algorithm that minimizes the schedule length while meeting reliability requirement, on top of which we propose a processor-merging algorithm and a slack time reclamation algorithm using a dynamic voltage frequency scaling (DVFS) technique to reduce energy consumption. The processor-merging algorithm tries to turn off some energy-inefficient processors such that energy consumption can be minimized. The DVFS technique is applied to scale down the processor frequency at both processor and task levels to reduce energy consumption. Experimental results on two real-life workflows and extensive synthetic parallel workflows demonstrate their effectiveness.

Original language | English (US) |
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Pages (from-to) | 2766-2779 |

Number of pages | 14 |

Journal | IEEE Transactions on Services Computing |

Volume | 15 |

Issue number | 5 |

DOIs | |

State | Published - 2022 |

## All Science Journal Classification (ASJC) codes

- Information Systems and Management
- Hardware and Architecture
- Computer Networks and Communications
- Computer Science Applications

## Keywords

- Dynamic voltage frequency scaling
- heuristics
- non-linear mixed integer programming
- optimization
- reliability
- response time
- workflow scheduling