Toward Risk Reduction for Mobile Service Composition

被引:39
作者
Deng, Shuiguang [1 ]
Huang, Longtao [2 ]
Li, Ying [1 ]
Zhou, Honggeng [3 ]
Wu, Zhaohui [1 ]
Cao, Xiongfei [4 ]
Kataev, Mikhail Yu [5 ]
Li, Ling [6 ]
机构
[1] Zhejiang Univ, Coll Comp Sci & Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Chinese Acad Sci, Inst Informat Engn, Beijing 100190, Peoples R China
[3] Zhejiang Univ, Sch Management, Hangzhou 310027, Peoples R China
[4] Univ Sci & Technol China, Sch Management, Hefei 230026, Peoples R China
[5] Tomsk State Univ Control Syst & Radioelect, Dept Control Syst, Tomsk 634050, Russia
[6] Old Dominion Univ, Dept Informat Technol & Decis Sci, Norfolk, VA 23529 USA
基金
中国国家自然科学基金;
关键词
Mobile service; risk reduction; service composition; service selection; OPTIMIZATION; PREDICTION; MANAGEMENT; SELECTION;
D O I
10.1109/TCYB.2015.2446443
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The advances in mobile technologies enable us to consume or even provide services through powerful mobile devices anytime and anywhere. Services running on mobile devices within limited range can be composed to coordinate together through wireless communication technologies and perform complex tasks. However, the mobility of users and devices in mobile environment imposes high risk on the execution of the tasks. This paper targets reducing this risk by constructing a dependable service composition after considering the mobility of both service requesters and providers. It first proposes a risk model and clarifies the risk of mobile service composition; and then proposes a service composition approach by modifying the simulated annealing algorithm. Our objective is to form a service composition by selecting mobile services under the mobility model and to ensure the service composition have the best quality of service and the lowest risk. The experimental results demonstrate that our approach can yield near-optimal solutions and has a nearly linear complexity with respect to a problem size.
引用
收藏
页码:1807 / 1816
页数:10
相关论文
共 44 条
[1]   A Hybrid Approach for Efficient Web Service Composition with End-to-End QoS Constraints [J].
Alrifai, Mohammad ;
Risse, Thomas ;
Nejdl, Wolfgang .
ACM TRANSACTIONS ON THE WEB, 2012, 6 (02)
[2]  
[Anonymous], 2014, SERVICE COMPUTING CO
[3]   A Hybrid Memetic Framework for Coverage Optimization in Wireless Sensor Networks [J].
Chen, Chia-Pang ;
Mukhopadhyay, Subhas Chandra ;
Chuang, Cheng-Long ;
Lin, Tzu-Shiang ;
Liao, Min-Sheng ;
Wang, Yung-Chung ;
Jiang, Joe-Air .
IEEE TRANSACTIONS ON CYBERNETICS, 2015, 45 (10) :2309-2322
[4]  
DENG S, IEEE T SERV COMPUT, DOI DOI 10.1109/TSC.2014.2361138
[5]   Mobility-Enabled Service Selection for Composite Services [J].
Deng, Shuiguang ;
Huang, Longtao ;
Hu, Daning ;
Zhao, J. Leon ;
Wu, Zhaohui .
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2016, 9 (03) :394-407
[6]   Computation Offloading for Service Workflow in Mobile Cloud Computing [J].
Deng, Shuiguang ;
Huang, Longtao ;
Taheri, Javid ;
Zomaya, Albert Y. .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2015, 26 (12) :3317-3329
[7]   Deploying Data-Intensive Service Composition with a Negative Selection Algorithm [J].
Deng, Shuiguang ;
Huang, Longtao ;
Li, Ying ;
Yin, Jianwei .
INTERNATIONAL JOURNAL OF WEB SERVICES RESEARCH, 2014, 11 (01) :76-93
[8]   Top-k Automatic Service Composition: A Parallel Method for Large-Scale Service Sets [J].
Deng, Shuiguang ;
Huang, Longtao ;
Tan, Wei ;
Wu, Zhaohui .
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2014, 11 (03) :891-905
[9]   Parallel Optimization for Data-Intensive Service Composition [J].
Deng, Shuiguang ;
Huang, Longtao ;
Wu, Bin ;
Xiong, Lirong .
JOURNAL OF INTERNET TECHNOLOGY, 2013, 14 (05) :817-824
[10]   Efficient planning for top-K Web service composition [J].
Deng, Shuiguang ;
Wu, Bin ;
Yin, Jianwei ;
Wu, Zhaohui .
KNOWLEDGE AND INFORMATION SYSTEMS, 2013, 36 (03) :579-605