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

ISBN-10: 3642379486

ISBN-13: 9783642379482

ISBN-10: 3642379494

ISBN-13: 9783642379499

This ebook constitutes the completely refereed post-conference complaints of the ninth foreign convention on Heterogeneous Networking for caliber, Reliability, protection and Robustness, QShine 2013, which was once held in nationwide Capital sector (NCR) of India in the course of January 2013. The 87 revised complete papers have been conscientiously 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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Extra 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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Local based approach provide better performance than global based approach. RTN The communication overhead CO = ∑ R n ∑ n ∗ CO where CO is communication overhead of one receiver to communicate first level node for only one layer authentication information and description of n , n , n are given in table 2. Integrated Approach for Multicast Source Authentication and Congestion Control 25 At this cost (communication overhead) receiver access the authentic information in network overload situation and it verify the genuinity of source while performing the overload management operation.

Simulation setup with four test networks, four patient devices as source, and one medical practitioner’s device as destination Table 4. four patients with different disease stages and their corresponding selected networks as a result of simulation Patient No. 1 2 3 4 Disease Stage Marginally High Normal Marginally Hgh Very High Selected Network N2 N1 N2 N3 40 R. Agrawal and A. Sehgal Clinical parameter values for four different diabetic cases falling under disease stages – Normal, Marginally High and Very High were used to generate the network requirements in terms of QoS parameter (Data for Critical stages was not available and hence not simulated).

Fig. 12 and table 4 give the simulated results. )/disease stage Vs. /disease Stage Selected Network Fig. 12. Selected Network for patients at different disease stages 5 Conclusion The Proposed work presents a fuzzy based approach to map the stage of patient’s disease with the selection of an optimum network for remote monitoring services. The selection of right network will ensure the transfer of vital clinical parameters to the control centre irrespective of the location of the patient and availability of high performance network.

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Quality, Reliability, Security and Robustness in Heterogeneous Networks: 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers by Rahul Johari, Neelima Gupta, Sandhya Aneja (auth.), Karan Singh, Amit K. Awasthi (eds.)


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