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Abhay Parekh
Researcher at University of California, Berkeley
Publications - 34
Citations - 7853
Abhay Parekh is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Distributed algorithm & Minimax. The author has an hindex of 16, co-authored 34 publications receiving 7740 citations. Previous affiliations of Abhay Parekh include IBM & Google.
Papers
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Journal ArticleDOI
A generalized processor sharing approach to flow control in integrated services networks: the multiple node case
Abhay Parekh,Robert G. Gallager +1 more
TL;DR: Worst-case bounds on delay and backlog are derived for leaky bucket constrained sessions in arbitrary topology networks of generalized processor sharing (GPS) servers and the effectiveness of PGPS in guaranteeing worst-case session delay is demonstrated under certain assignments.
Proceedings ArticleDOI
A generalized processor sharing approach to flow control in integrated services networks-the multiple node case
Abhay Parekh,Robert G. Gallager +1 more
TL;DR: The authors propose the use of a packet service discipline at the nodes of the network that is based on a multiplex scheme called generalized processor sharing (GPS) that is combined with leaky bucket rate admission control to provide flexible, efficient and fair use of the links.
Journal ArticleDOI
Spectrum sharing for unlicensed bands
TL;DR: This work investigates whether efficiency and fairness can be obtained with self-enforcing spectrum sharing rules, and presents examples that illustrate that in many cases the performance loss due to selfish behavior is small.
Journal ArticleDOI
The Approximate Capacity of the Many-to-One and One-to-Many Gaussian Interference Channels
TL;DR: A central theme emerges: the use of lattice codes for alignment of interfering signals on the signal level in the Gaussian interference channel to within a constant number of bits.
Journal ArticleDOI
Optimal multiplexing on a single link: delay and buffer requirements
TL;DR: This paper addresses the problem of characterizing and designing scheduling policies that are optimal in the sense of minimizing buffer and/or delay requirements under the assumption of commonly accepted traffic constraints, and investigates buffer requirements under three typical memory allocation mechanisms which represent tradeoffs between efficiency and complexity.