Mehdi Malboubi

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Traffic matrix measurement provides essential information for network design, operation and management. In today's networks, it is challenging to get accurate and timely traffic matrix due to the hard resource constraints of network devices. Recently, Software-Defined Networking (SDN) technique enables customizable traffic measurement, which can provide(More)
In this paper, the cooperative spectrum sensing is probabilistically modeled as a mixture of two Gaussian distributions and EM algorithm is applied for learning the parameters and classifying these two classes. Also, in order to exploit the dependencies of the states of the primary user in time, a Hidden Markov Model is used to improve the performance of(More)
Fine-grained traffic flow measurement, which provides useful information for network management tasks and security analysis, can be challenging to obtain due to monitoring resource constraints. The alternate approach of inferring flow statistics from partial measurement data has to be robust against dynamic temporal/spatial fluctuations of network traffic.(More)
Network inference or tomography problems, such as traffic matrix estimation or completion and link loss inference, have been studied rigorously in different networking applications. These problems are often posed as under-determined linear inverse UDLI problems and solved in a centralized manner, where all the measurements are collected at a central node,(More)
We have previously introduced Multiple Description Fusion Estimation (MDFE) framework that partitions a largescale Under-Determined Linear Inverse (UDLI) problem into smaller sub-problems that can be solved independently and in parallel. The resulting estimates, referred to as multiple descriptions, can then be fused together to compute the global estimate(More)
A key requirement for network management is the accurate and reliable monitoring of relevant network characteristics. In today’s large-scale networks, this is a challenging task due to the scarcity of network measurement resources and the hard constraints that this imposes. This paper proposes a new framework, SNIPER, which leverages the flexibility(More)
This paper describes a new efficient and simple multiple description image coding system for the reliable communication of images in wireless communication systems. This system uses the inherent redundancy in an image to create several balanced descriptions. Each description is coded using a minimum complexity JPEG image coder and at the decoder, based on(More)
In this paper, we introduce a new technique for partitioning a large-scale under-determined linear inverse problem into multiple smaller subproblems that can be efficiently solved independently, and in parallel. When it is impossible or inefficient to solve a large-scale under-determined linear inverse problem, this technique can be used to significantly(More)
Accurate and efficient network-wide traffic measurement is crucial for network management. Recently, Software-defined networking (SDN) has opened up new opportunities in network measurement and inference. In this work, we demonstrate an efficient flow measurement and inference framework which performs adaptive measurement with online learning. Using the(More)