Mahmoud El Chamie

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Consider a network whose nodes have some initial values, and it is desired to design an algorithm that builds on neighbor to neighbor interactions with the ultimate goal of convergence to the average of all initial node values or to some value close to that average. Such an algorithm is called generically “distributed averaging”, and our goal in this paper(More)
This paper studies the weight optimization problem for average consensus protocols by reformulating it as a Schatten norm minimization with parameter p. We show that as p approaches infinity, the optimal solution of the Schatten norm induced problem recovers the optimal solution of the original problem. Moreover, by tuning the parameter p in our proposed(More)
Data offloading from the cellular network to low-cost WiFi has been the subject of several research works in the last years. In-network caching has also been studied as an efficient means to further reduce cellular network traffic. In this paper we consider a scenario where mobile users can download popular contents (e.g., maps of a city, shopping(More)
In many application scenarios sensors need to calculate the average of some local values, e.g. of local measurements. A possible solution is to rely on consensus algorithms. In this case each sensor maintains a local estimate of the global average, and keeps improving it by performing a weighted sum of the estimates of all its neighbors. The number of(More)
In-network caching is an important solution for content offloading from content service providers. However despite a rather high maturation in the definition of caching techniques, minor attention has been given to the strategic interaction among the multiple content providers. Situations involving multiple content providers (CPs) and one Internet Service(More)
Clustering of a graph is the task of grouping its nodes in such a way that the nodes within the same cluster are well connected, but they are less connected to nodes in different clusters. In this paper we propose a clustering metric based on the random walks’ properties to evaluate the quality of a graph clustering. We also propose a randomized algorithm(More)
In this paper, we consider optimal design strategies in consensus protocols for networks vulnerable to adversarial attacks. First we study dynamic (multi-stage) weight selection optimal control for consensus protocols. For the general (multi-stage) case, the solution exists but can rarely be expressed in closed-form. In view of this, we apply optimization(More)
Due to increasing computer processing power, Newton’s method is receiving again increasing interest for solving optimization problems. In this paper, we provide a methodology for solving smooth norm optimization problems under some linear constraints using the Newton’s method. This problem arises in many machine learning and graph optimization applications.(More)
An average consensus protocol is an iterative distributed algorithm to calculate the average of local values stored at the nodes of a network. Each node maintains a local estimate of the average and, at every iteration, it sends its estimate to all its neighbors and then updates the estimate by performing a weighted average of the estimates received. The(More)