A Workflow for Fast Evaluation of Mapping Heuristics Targeting Cloud Infrastructures

TL;DR

This paper introduces a framework for quickly evaluating resource mapping heuristics in cloud infrastructures, focusing on execution time and energy consumption to improve management tools.

Contribution

It presents a new workflow that enables fast simulation and assessment of cloud resource mappings specified in AMALTHEA format, aiding cloud infrastructure management.

Findings

Framework allows rapid evaluation of mapping heuristics.

Supports assessment of execution time and energy consumption.

Facilitates better resource allocation decisions in cloud management.

Abstract

Resource allocation is today an integral part of cloud infrastructures management to efficiently exploit resources. Cloud infrastructures centers generally use custom built heuristics to define the resource allocations. It is an immediate requirement for the management tools of these centers to have a fast yet reasonably accurate simulation and evaluation platform to define the resource allocation for cloud applications. This work proposes a framework allowing users to easily specify mappings for cloud applications described in the AMALTHEA format used in the context of the DreamCloud European project and to assess the quality for these mappings. The two quality metrics provided by the framework are execution time and energy consumption.