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We consider a probabilistic model for workload input into a telecommunication system. It captures the dynamics of packet generation in data traffic as well as accounting for long-range dependence and self-similarity exhibited by real traces. The workload is found by aggregating the number of packets, or their sizes, generated by the arriving sessions. The(More)
For large-scale peer-to-peer applications, bio-inspired epidemic protocols have considerable advantages as they are robust against network failures, scalable and provide probabilistic reliability guarantees. While providing reliability, a key issue to consider is the usage of system wide buffer space. In this context, we introduce a novel scheme called(More)
In order to deliver innovative and cost-effective IP multimedia applications over mobile devices, there is a need to develop a unified service platform for the future mobile Internet referred as the Next Generation (NG) all-IP network. It is convincingly demonstrated by numerous recent studies that modern multimedia network traffic exhibits long-range(More)
Numerous recent studies have proven that traffic patterns generated by multimedia services are different from traditional Poisson traffic. It has been shown that multimedia network traffic exhibits long-range dependency (LRD) and self-similar characteristics. The area of wireless IP traffic modeling in terms of providing assured QoS to the end-user is still(More)
The dramatic increase in demand for wireless Internet access has lead to the introduction of new wireless architectures and systems including 3G, Wi-Fi and WiMAX. 3G systems such as UMTS and CDMA2000 are leaning towards an all-IP architecture for transporting IP multimedia services, mainly due to its scalability and promising capability of inter-working(More)
We consider peer-to-peer anti-entropy paradigms for epidemic information diffusion, namely pull, push and hybrid cases, and provide exact performance measures for them. Major benefits of the proposed epidemic algorithms are that they are fully distributed, utilize local information only via pair-wise interactions, and provide eventual consistency,(More)
An analytical framework is developed for establishing exact performance measures for peer-to-peer (P2P) anti-entropy paradigms used in biologically inspired epidemic data dissemination. Major benefits of these paradigms are that they are fully distributed, selforganizing, utilize local data only via pair-wise interactions, and provide eventual consistency,(More)
We consider buffer management in support of large-scale gossip-based peer-to-peer data dissemination protocols. Coupled with an efficient buffering mechanism, system-wide buffer usage can be optimized while providing reliability and scalability in such protocols. We propose a novel approach, Stepwise Fair-share Buffering, that provides uniform load(More)
Over the past few years, we have witnessed a growing popularity of new wireless architectures such as 3G, Wi-Fi and Wi-Max due to the increase in demand for wireless Internet access. The all-IP based future mobile and wireless network model is expected to be the most dominant architecture for QoS provisioning in next-generation wireless networks, mainly due(More)
We propose and design a peer-to-peer system, SeCond, addressing the distribution of large sized content to a large number of end systems in an efficient manner. In contrast to prior work, it employs a self-organizing epidemic dissemination scheme for state propagation of available blocks and initiation of block transmissions. In order to exploit(More)