Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지
DOI QR코드

DOI QR Code

Multi-Devices Composition and Maintenance Mechanism in Mobile Social Network

  • Li, Wenjing (Beijing University of Posts and Telecommunications) ;
  • Ding, Yifan (Beijing University of Posts and Telecommunications) ;
  • Guo, Shaoyong (Beijing JiaoTong University) ;
  • Qiu, Xuesong (Beijing University of Posts and Telecommunications)
  • Received : 2014.08.24
  • Published : 2015.04.30
⟨ Previous Next ⟩

Abstract

In mobile social network, it is a critical challenge to select an optimal set of devices to supply high quality service constantly under dynamic network topology and the limit of device capacity in mobile ad-hoc network (MANET). In this paper, a multi-devices composition and maintenance problem is proposed with ubiquitous service model and network model. In addition, a multi-devices composition and maintenance approach with dynamic planning is proposed to deal with this problem, consisting of service discovery, service composition, service monitor and service recover. At last, the simulation is implemented with OPNET and MATLAB and the result shows this mechanism is better applied to support complex ubiquitous service.

Keywords

References

  1. R. LanLan et al., "Theil utility based multi-device cooperation mechanism for service quality equilibrium in ubiquitous stub environments," China Commun., pp. 140-150, June 2014.
  2. W. Qing et al., "CACTSE: Cloudlet aided cooperative terminals service environment for mobile proximity content delivery," China Commun., vol. 10, no. 6, pp. 47-59, 2013. https://doi.org/10.1109/CC.2013.6549258
  3. D. Niu et al., "A composition and recovery strategy for mobile social network service in disaster," Comput. J., pp. 1-9, June 3, 2014.
  4. S. Jiang, Y. Xue, and D. C. Schmidt, "Minimum disruption service composition and recovery in mobile ad hoc networks," Comput. Netw., vol. 53, no. 10, pp. 1649-1665, 2009. https://doi.org/10.1016/j.comnet.2008.10.017
  5. P. Basu, W. Ke, and T.D.C. Little, "Dynamic task-based anycasting in mobile ad hoc networks," Mobile Netw. Appl., vol. 8(5), pp. 593-612, 2003. https://doi.org/10.1023/A:1025198129990
  6. W.-T. Su, Y.-H. Kuo, and P.-C. Huang, "A QoS-driven approach for service-oriented device anycasting in ubiquitous environments," Comput. Netw., vol. 52, no. 18, pp. 3342-3357, 2008. https://doi.org/10.1016/j.comnet.2008.09.001
  7. A. Furno and E. Zimeo, "Self-scaling cooperative discovery of service compositions in unstructured P2P networks," J. Parallel Distrib. Comput., vol. 74, no. 10, pp. 2994-3025, Oct. 2014. https://doi.org/10.1016/j.jpdc.2014.06.006
  8. Y.-S. Luo et al., "A multi-criteria network-aware service composition algorithm in wireless environments," Computer Commun., vol. 35, no. 15, pp. 1882-1892, Sept. 2012. https://doi.org/10.1016/j.comcom.2012.02.009
  9. L. Chunlin, H. J. Hui, and L. Layuan, "A Market based approach for sensor resource allocation in the grid," Informatica Slovenia, vol. 36, no. 2, pp. 167-176, 2012.
  10. F. Ye and Y. Li, "An extended TOPSIS model based on the Possibility theory under fuzzy environment," Knowledge-Based Syst., vol. 67, pp. 263-269, Sept. 2014. https://doi.org/10.1016/j.knosys.2014.04.046
  11. S. W.-Tsung et al., "Service-oriented device composition in resource-constrained ubiquitous environments," in Proc. IEEE WCNC, 2008, pp. 3110-3115.
  12. Y. Jiang and J. Jiang, "Contextual resource negotiation-based task allocation and load balancing in complex software systems," IEEE Trans. Parallel Distrib. Syst., vol. 20, no. 5, pp. 641-653, 2009. https://doi.org/10.1109/TPDS.2008.133
  13. W. C.-ru, TianHui, and M. Jie, "Research on device aggregative selection algorithm based on multi-objective evolutionary," J. Electron. Inform. Technol., vol. 33, no. 10, pp. 2340-2346, 2011. https://doi.org/10.3724/SP.J.1146.2010.01445
  14. S. Guo et al., "An effective cooperation mechanism among multi-devices in ubiquitous network," in Proc. CNSM, 2012, pp. 199-203.
  15. A. Gopalan and T. Znati, "SARA: A service architecture for resource aware ubiquitous environments," Pervasive Mobile Comput., vol. 6, no. 1, pp. 1-20, 2010. https://doi.org/10.1016/j.pmcj.2009.04.004
  16. R. C. T. Lee et al., Introduction to the Design and Analysis of Algorithms. McGraw-Hill Education, 2005.
  17. C.-L. Chen et al., "Noise-referred energy-proportional routing with packet length adaption for clustered sensor networks," J. Ad Hoc Ubiquitous Computing, pp. 224-265, 2008.
  18. Y. Yang et al., "A self-adaptive method of task allocation in clustering-based MANETs," in Proc. IEEE NOMS, 2010, pp. 440-447.