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We study averaging algorithms in time-varying networks, and means tomeasure their performance. We present sufficient conditions on these algorithms, which ensure they lead to computation at each node, of the global average of measurements provided by each ...
Max-min fairness is widely used in various areas of networking. In every case where it is used, there is a proof of existence and one or several algorithms for computing it; in most, but not all cases, they are based on the notion of bottlenecks. In spite ...
P2P data management systems provide a scalable alternative to centralized architectures. Their adoption, however, is limited by the lack of possibility to control the access on the resources stored in the system. We address the problem of access control fo ...
The term distributed Consensus denotes the problem of getting a certain number of processes, that could be far away from each other and that exchange messages through some communication means, to all agree on the same value. This problem has been proved im ...
We provide a comparison of a series of original coordination mechanisms for the distributed boundary coverage problem with a swarm of miniature robots. Our analysis is based on real robot experimentation and models at different levels of abstraction. Distr ...
New multimedia embedded applications are increasingly dynamic, and rely on dynamically-allocated data types (DDTs) to store their data. The optimization of DDTs for each target embedded system is a time-consuming process due to the large searching space of ...
This paper presents an approach to automatic verification of asynchronous round-based consensus algorithms. We use model checking, a widely practiced verification method; but its application to asynchronous distributed algorithms is difficult because the s ...
Data security in a mobile context is a critical issue. Over the last few years a new category of location-based services, the Enterprise LBS (ELBS), has emerged focusing on the demands of mobility in organisations. These applications pose challenging requi ...
Iterative Learning Control (ILC) is a technique used to improve the tracking performance of systems carrying out repetitive tasks, which are affected by deterministic disturbances. The achievable performance is greatly degraded, however, when non-repeating ...
Iterative Learning Control (ILC) is a technique used to improve the tracking performance of systems carrying out repetitive tasks, which are affected by deterministic disturbances. The achievable performance is greatly degraded, however, when non-repeating ...
