Abstract

International audience; The annual number of flights in Western Europe has increased from about 2.6 million in 1982 to about 4.5 million in 1992, an increase of 73%. Acute congestion of the Air Traffic Control system has been the result. One way to reduce this congestion is to modify the flight plans (slot of departure and route) in order to adapt the demand to the available capacity. This paper addresses the general time-route assignment problem. A state of the art of the existing methods shows that this problem is usually partially treated and the whole problem remains unsolved due to the complexity induced. We perform our research on the application of stochastic methods on real traffic data, and without using the flow network concept, but by simulating the flight of each aircraft. The first results shows that our Genetic Algorithms based method is able to reduce congestion of the french airspace by a factor 2. Special coding techniques and operators are used to improve the quality of the genetic search. Document type: Part of book or chapter of book

Abstract

The design of large-scale critical infrastructures demands for innovative data dissemination services, able to jointly provide reliability and timeliness guarantees. Current middleware solutions do not address both these aspects. Indeed, fault tolerance is typically achieved at the cost of severe performance fluctuations, or timeliness is always obtained by softening the fault-tolerance requirements. In this paper we propose to fulfill this lack by combining two different approaches, namely coding and gossiping. We provide a theoretical model to evaluate the potential benefit of coding on the information delivery performance. These results are also confirmed by an experimental analysis conducted on a real air traffic control workload, which evidences how coding mitigates latency and overhead penalties to ensure reliable event notification. Document type: Part of book or chapter of book