Quality, Reliability, Security and Robustness in by Rahul Johari, Neelima Gupta, Sandhya Aneja (auth.), Karan

By Rahul Johari, Neelima Gupta, Sandhya Aneja (auth.), Karan Singh, Amit K. Awasthi (eds.)

This e-book constitutes the completely refereed post-conference lawsuits of the ninth foreign convention on Heterogeneous Networking for caliber, Reliability, protection and Robustness, QShine 2013, which was once held in nationwide Capital quarter (NCR) of India in the course of January 2013. The 87 revised complete papers have been rigorously chosen from 169 submissions and current the hot technological advancements in broadband high-speed networks, peer-to-peer networks, and instant and cellular networks.

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Additional resources for Quality, Reliability, Security and Robustness in Heterogeneous Networks: 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers

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Comp_MSL(G) = Max (SL( ), SL( )…………… SL( ) v. remove authentic information for layer whose number is less than Max_SL (G) break; Case: Operation =Leave i. SL ( ) = {Already SL } - {Leave Layer} ii. Comp_MSL (G) = max ( SL ( ), SL( ),…………… )) SL( iii. add authentic information to the group manager break; Case: Operation = Deaf_ resumption Integrated Approach for Multicast Source Authentication and Congestion Control 23 i. Contact group manager for authentic information If (required information is available with group) i.

In: Proceedings of the 14th ACM International Conference on Mobile Computing and Networking, MobiCom 2008, pp. 58–69. ACM, New York (2008) 13. : Encounter: based routing in dtns. SIGMOBILE Mob. Comput. Commun. Rev. 13(1), 56–59 (2009) 14. : Daknet: Rethinking connectivity in developing nations. Computer 37(1), 78–83 (2004) 15. edu/cambridge/haggle/imote/intel 16. : Data mules: modeling and analysis of a three-tier architecture for sparse sensor networks. Ad Hoc Networks 1(2-3), 215–233 (2003) DSG-PC: Dynamic Social Grouping Based Routing 15 17.

To further keep the approach generalized and applicable to several diverse medical situations, fuzzification of clinical parameters has been done before it can be used for generating network requirements. Fig. 1. Remote healthcare system based on mobile devices communicating through heterogeneous networks. Body sensors monitoring various clinical parameters provide necessary information to frame selection criterion at the communicator device. Rest of the paper is organized as follows. Section II presents fuzzy functions for some of the commonly used clinical parameters.

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