Open AccessA Cost-Optimized Resource Provisioning Policy for Heterogeneous Cloud Environments
Author(s) -
Xin Chen,
Feng Ding,
Tiantian Zhang,
Gang Hou,
Lan Lan
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2778145
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
To avoid the drawbacks of a pricing mechanism in heterogeneous cloud environments that considers only single resources, we propose a multi-resource combinatorial pricing mechanism in this paper. This approach jointly considers the principal resources (i.e., CPU, memory, storage, and bandwidth) with the goal of minimizing the total cost. Then, a cost-optimized resource provisioning policy (CORPP) based on game theory is applied to this mechanism that considers the Nash equilibrium between cloud users as well as the Stackelberg equilibrium between users and the cloud provider. The experimental results show that the proposed combinatorial pricing mechanism is more suitable in a heterogeneous cloud environment when running various types of cloudlets. Moreover, CORPP is effective in reducing users’ total costs when using both random cloudlets and PlanetLab cloudlets.
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