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Sonia Fahmy

Researcher at Purdue University

Publications -  222
Citations -  11620

Sonia Fahmy is an academic researcher from Purdue University. The author has contributed to research in topics: Asynchronous Transfer Mode & Wireless sensor network. The author has an hindex of 39, co-authored 217 publications receiving 11177 citations. Previous affiliations of Sonia Fahmy include Ohio State University & Hewlett-Packard.

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Proceedings ArticleDOI

Detecting the unintended in BGP policies

TL;DR: A language that allows analysis of network-wide configurations at the high-level is defined, which can be used to verify desired properties of routing protocols and hence detect potential unintended states of BGP.
Book

Wired/Wireless Internet Communications

TL;DR: This paper optimize an existing implementation of a CPU-based channelizer and implement a novel GPU-basedChannelizer, which delivers an overall improvement of 30 % for the CPU optimization on Intel Core i7-4790 @ 3.60 GHz, and a 3.2-fold improvement for the GPU implementation on AMD R9 290, when compared to the originalCPU-based implementation.
Proceedings ArticleDOI

A framework for virtual channel onto virtual path multiplexing in ATM-ABR

TL;DR: Preliminary simulation results indicate that the algorithm achieves the required fair allocations, while controlling queue sizes, and an algorithm for allocating the VPC capacity to the multiplexed VCCs is described.

An energy-efficient architecture for wireless sensor networks

TL;DR: This work designs distributed protocols for topology management and network synchronization for heavily-loaded sensor networks serving applications that can exploit data aggregation, and considers applications and protocols that require node synchronization, and design a framework for time synchronization in multi-hop hierarchical networks that is based on relative synchronization.

On Detecting Bandwidth Theft Attacks and SLA Violations in QoS Networks

TL;DR: A detection system to measure QoS in differentiated services networks that detects a number of bandwidth theft and denial of service attacks and can be useful in developing mechanisms for response and damage control in QoS enabled networks.