Online placement of multi-component applications in edge computing environments

File Description SizeFormat 
Shiqiang_Wang_MappingAlgorithm_2017_01.pdfAccepted version1.41 MBAdobe PDFView/Open
Title: Online placement of multi-component applications in edge computing environments
Authors: Wang, S
Zafer, M
Leung, KK
Item Type: Journal Article
Abstract: Mobile edge computing is a new cloud computing paradigm which makes use of small-sized edge-clouds to provide real-time services to users. These mobile edge-clouds (MECs) are located in close proximity to users, thus enabling users to seamlessly access applications running on MECs. Due to the coexistence of the core (centralized) cloud, users, and one or multiple layers of MECs, an important problem is to decide where (on which computational entity) to place different components of an application. This problem, known as the application or workload placement problem, is notoriously hard, and therefore, heuristic algorithms without performance guarantees are generally employed in common practice, which may unknowingly suffer from poor performance as compared to the optimal solution. In this paper, we address the application placement problem and focus on developing algorithms with provable performance bounds. We model the user application as an application graph and the physical computing system as a physical graph, with resource demands/availabilities annotated on these graphs. We first consider the placement of a linear application graph and propose an algorithm for finding its optimal solution. Using this result, we then generalize the formulation and obtain online approximation algorithms with polynomial-logarithmic (poly-log) competitive ratio for tree application graph placement.We jointly consider node and link assignment, and incorporate multiple types of computational resources at nodes.
Issue Date: 8-Feb-2017
Date of Acceptance: 3-Feb-2017
ISSN: 2169-3536
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Start Page: 2514
End Page: 2533
Journal / Book Title: IEEE Access
Volume: 5
Copyright Statement: 6 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information
Sponsor/Funder: IBM United Kingdom Ltd
Funder's Grant Number: PO4603106973
Keywords: Science & Technology
Computer Science, Information Systems
Engineering, Electrical & Electronic
Computer Science
Cloud computing
graph mapping
mobile edge-cloud (MEC)
online approximation algorithm
optimization theory
mobile edge-cloud
Publication Status: Published
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commonsx