Sonia Fahmy

Bio: 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.

On the Cost of Network Inference Mechanisms

Abstract: A number of network path delay, loss, or bandwidth inference mechanisms have been proposed over the past decade. Concurrently, several network measurement services have been deployed over the Internet and intranets. We consider inference mechanisms that use O(n) end-to-end measurements to predict the O(n2) end-to-end pairwise measurements among n nodes, and investigate when it is beneficial to use them in measurement services. In particular, we address the following questions : 1) For which measurement request patterns would using an inference mechanism be advantageous? 2) How does a measurement service determine the set of hosts that should utilize inference mechanisms, as opposed to those that are better served using direct end-to-end measurements? We explore three solutions that identify groups of hosts which are likely to benefit from inference. We compare these solutions in terms of effectiveness and algorithmic complexity. Results with synthetic data sets and data sets from a popular peer-to-peer system demonstrate that our techniques accurately identify host subsets that benefit from inference, in significantly less time than an algorithm that identifies optimal subsets. The measurement savings are large when measurement request patterns exhibit small-world characteristics, which is often the case. (Part of this work (focusing on one of three solutions presented in this paper) appeared in).

Mitigating interference in a network measurement service

Abstract: Shared measurement services offer key advantages over conventional ad-hoc techniques for network monitoring. A measurement service may receive measurement requests concurrently from different applications and network administrators. These measurement requests are often served by injecting active network measurement traffic between two hosts. Two active measurements are said to interfere when the probe packets of one measurement tool are viewed as network traffic by the other. This may lead to faulty measurement readings. In this paper, we model the measurement interference problem, and show how to schedule measurement tasks to reduce interference and hence increase measurement accuracy. We propose twelve computationally tractable algorithms that decrease the total completion time (makespan) of measurement tasks, while avoiding interference. Our evaluation shows that the algorithm we refer to as Largest Area First, Busiest Node First — Earliest Interval Schedule (LAFBNF-EIS) has a mean makespan of about 5% more than the theoretical lower bound over our set of measurement workloads.1

HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks

Abstract: Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. We propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in O(1) iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks. Simulation results demonstrate that our proposed approach is effective in prolonging the network lifetime and supporting scalable data aggregation.

Topology Control in Wireless Ad Hoc and Sensor Networks

Abstract: Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes' transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey state-of-the-art solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field.