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

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Extra info 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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It is a big challenge to manage the effect of increasing security overhead on overloading. The tuning with increased security level, hashes may lead to overloading. 1 Multicast Congestion Control 19 Computer networks uses the channels for transmit the data from source to receivers. If source rate increases the capacity of channel then congestion occur [7]. There are various multicast congestion control algorithms viz. RLM [4], TFMC [9, 10], FLIDDL [2], RLC [13], WEBREC [9], QIACCRM [5], EJLRDMC [11] etc.

In: International Conference on Soft Computing and Intelligent Systems (ICSCIS 2007), Jabalpur (December 2007) 13. : Receiver-driven Layered Multicast. In: Proceedings of ACM SIGCOMM (August 1996) 14. Athens/Glyfada, Greece, Replay Attack of Dynamic Rights within an Authorised Domain. In: Proc. of IEEE, Third International Conference on Emerging Security Information, Systems and Technologies (2009) 15. RFC 4046, Multicast Security (MSEC) Group Key Management Architecture (April 2005) 16. RFC-3740, The Multicast Group Security Architecture (March 2004) 17.

Cost of network usage, Data Rate, End-to-End Delay, Reliability (in terms of Packet Loss and Bit Error Rate-BER) and Outage Probability. Since the values of these parameters for any available networks may depend on a large number of factors and thus vary from place to place, it is not justifiable to define the QoS requirements in the form of crisp values. We, therefore generate QoS requirements in linguistic terms which are then represented by fuzzy variables as shown in fig. 8. 1 Clinical Case Study - Diabeters Diabetes, a common and globally widespread disease, has been taken as a clinical case to study the proposed network selection scheme.

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