Title
Cost-Aware Streaming Workflow Allocation on Geo-Distributed Data Centers.
Abstract
The virtual machine (VM) allocation problem in cloud computing has been widely studied in recent years, and many algorithms have been proposed in the literature. Most of them have been successfully applied to batch processing models such as MapReduce; however, none of them can be applied to streaming workflow well because of the following weaknesses: 1) failure to capture the characteristics of tasks in streaming workflow for the short life cycle of data streams; 2) most algorithms are based on the assumptions that the price of VMs and traffic among data centers (DCs) are static and fixed. In this paper, we propose a streaming workflow allocation algorithm that takes into consideration the characteristics of streaming work and the price diversity among geo-distributed DCs, to further achieve the goal of cost minimization for streaming big data processing. First, we construct an extended streaming workflow graph (ESWG) based on the task semantics of streaming workflow and the price diversity of geo-distributed DCs, and the streaming workflow allocation problem is formulated into mixed integer linear programming based on the ESWG. Second, we propose two heuristic algorithms to reduce the computational space based on task combination and DC combination in order to meet the strict latency requirement. Finally, our experimental results demonstrate significant performance gains with lower total cost and execution time.
Year
DOI
Venue
2017
10.1109/TC.2016.2595579
IEEE Trans. Computers
Keywords
Field
DocType
Resource management,Semantics,Minimization,Cloud computing,Data models,Big data,Heuristic algorithms
Data modeling,Data stream mining,Heuristic,Workflow technology,Computer science,Parallel computing,Real-time computing,Integer programming,Workflow management system,Workflow,Distributed computing,Cloud computing
Journal
Volume
Issue
ISSN
66
2
0018-9340
Citations 
PageRank 
References 
6
0.47
26
Authors
3
Name
Order
Citations
PageRank
Wuhui Chen130734.07
Incheon Paik224138.80
Zhenni Li39914.48