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Kianoosh Mokhtarian

Researcher at University of Toronto

Publications -  18
Citations -  401

Kianoosh Mokhtarian is an academic researcher from University of Toronto. The author has contributed to research in topics: Cache & Authentication. The author has an hindex of 10, co-authored 18 publications receiving 393 citations. Previous affiliations of Kianoosh Mokhtarian include Simon Fraser University.

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Proceedings ArticleDOI

Caching in video CDNs: building strong lines of defense

TL;DR: This work develops multiple algorithms for caching in these CDNs, using anonymized actual data from a large-scale, global CDN to evaluate the algorithms and draw conclusions on their suitability for different settings.
Journal ArticleDOI

Design and Evaluation of a Proxy Cache for Peer-to-Peer Traffic

TL;DR: It is demonstrated that caching P2P traffic is more complex than caching other Internet traffic, and it needs several new algorithms and storage systems.
Journal ArticleDOI

Authentication schemes for multimedia streams: Quantitative analysis and comparison

TL;DR: Detailed analysis of authentication schemes for nonscalable and scalable multimedia streams reveals the merits and shortcomings of each scheme, provides guidelines on choosing the most appropriate scheme for a given multimedia streaming application, and could stimulate designing new authentication schemes or improving existing ones.
Journal ArticleDOI

Authentication of Scalable Video Streams With Low Communication Overhead

TL;DR: This work proposes an efficient and secure authentication scheme that accounts for the full scalability of video streams, and enables verification of all possible substreams that can be extracted from the original stream, and implements it as an open source library called svcAuth, which can be used as a transparent add-on by any multimedia streaming application.
Journal ArticleDOI

Flexible Caching Algorithms for Video Content Distribution Networks

TL;DR: This work designs multiple algorithms for content caching on the servers of global video CDNs: a LRU-based baseline to address the requirements; a flexible ingress-efficient algorithm; an offline cache aware of future requests (greedy); an optimal offline cache (for limited scales); and an adaptive ingress control algorithm for reducing the server’s peak upstream traffic.