A priority, power and traffic-aware virtual machine placement of IoT applications in cloud data centers

• Published in: Journal of systems architecture Vol. 115; p. 101996
• Main Authors: Omer, Shvan, Azizi, Sadoon, Shojafar, Mohammad, Tafazolli, Rahim
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2021
• Subjects: Cloud computing; Cloud data center (CDC); Internet of Thing (IoT); Power consumption; Priority-aware; Traffic-aware; Virtual machine placement (VMP); Internet of Thing (IoT); Cloud computing; Priority-aware; Virtual machine placement (VMP); Power consumption; Cloud data center (CDC); Traffic-aware
• ISSN: 1383-7621; 1873-6165
• DOI: 10.1016/j.sysarc.2021.101996

Recent telecommunication paradigms, such as big data, Internet of Things (IoT), ubiquitous edge computing (UEC), and machine learning, are encountering with a tremendous number of complex applications that require different priorities and resource demands. These applications usually consist of a set of virtual machines (VMs) with some predefined traffic load between them. The efficiency of a cloud data center (CDC) as prominent component in UEC significantly depends on the efficiency of its VM placement algorithm applied. However, VM placement is an NP-hard problem and thus there exist practically no optimal solution for this problem. In this paper, motivated by this, we propose a priority, power and traffic-aware approach for efficiently solving the VM placement problem in a CDC. Our approach aims to jointly minimize power consumption, network consumption and resource wastage in a multi-dimensional and heterogeneous CDC. To evaluate the performance of the proposed method, we compared it to the state-of-the-art on a fat-tree topology under various experiments. Results demonstrate that the proposed method is capable of reducing the total network consumption up to 29%, the consumption of power up to 18%, and the wastage of resources up to 68%, compared to the second-best results.