M
Mohit Aron
Researcher at Rice University
Publications - 14
Citations - 1636
Mohit Aron is an academic researcher from Rice University. The author has contributed to research in topics: Web server & Server. The author has an hindex of 11, co-authored 14 publications receiving 1631 citations.
Papers
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Journal ArticleDOI
Locality-aware request distribution in cluster-based network servers
Vivek S. Pai,Mohit Aron,Gaurov Banga,Michael Svendsen,Peter Druschel,Willy Zwaenepoel,Erich M. Nahum +6 more
TL;DR: A simple, practical strategy for locality-aware request distribution (LARD), in which the front-end distributes incoming requests in a manner that achieves high locality in the back-ends' main memory caches as well as load balancing.
Proceedings Article
Scalable content-aware request distribution in cluster-based networks servers
TL;DR: In this architecture, a level-4 switch acts as the point of contact for the server on the Inernet and distributes the incoming requests to a number of back-end nodes, rather than being centralized in the front-end node.
Proceedings ArticleDOI
Cluster reserves: a mechanism for resource management in cluster-based network servers
TL;DR: This paper presents a design and evaluates a prototype implementation that extends existing techniques for performance isolation on a single node server to cluster based servers, and demonstrates that cluster reserves are effective in ensuring performance isolation while enabling high utilization of the server resources.
Proceedings Article
Efficient support for P-HTTP in cluster-based web servers
TL;DR: Two mechanisms for the efficient, content-based distribution of HTTP/1.1 requests among the back-end nodes of a cluster server, combined with an extension of the locality-aware request distribution (LARD) policy, are presented.
Journal ArticleDOI
Soft timers: efficient microsecond software timer support for network processing
Mohit Aron,Peter Druschel +1 more
TL;DR: This paper proposes and evaluates soft timers, a new operating system facility that allows the efficient scheduling of software events at agranularity down to tens of microseconds, and shows that this technique can improve the throughput of a Web server by up to 25%.