At the moment, in order to satisfy the demands of transported applications, several service quality architectures have been proposed, but what they have in common is that they propose a static approach to an environment which is highly dynamic.
The algorithms are often complex and only give good results on very precise data and at particular moments.
Along this axis we have chosen to carry out auto- piloting of algorithms for monitoring and managing various existing networks. The idea is to make the network autonomic.
Under this heading, the approach chosen to pilot the networks comes from techniques of distributed artificial intelligence and mainly from agent systems. The dynamics of the system represented by the agents; decision-making is loaded in the network element which can thus become autonomic and react to a problem. This approach gives a permanent guarantee of satisfaction for the network user and operator. The technology produced can be described briefly as a set of agents which will function in coordination to solve a problem or find a solution in a given situation.
One of the main themes is experimentation of proposals made. Two test and assessment platforms are used. The first is a local environment with standard equipment used for IP, MPLS, or service quality. As for large-scale tests, they are carried out within the Planet-lab network. In this way the test environment is as wide as the Internet. Peer-to-peer network applications are assessed in this framework. Lastly, the team also develops its own simulation and experimentation tools.
The ERA team has developed specialized research in the field of networks and their management and also gained recognition for competence in multi-agent technologies.
This dual skill is indisputably the team’s strength even more so as it is assisted by a complete set of testing and simulation tools.
The “Autonomic Networking Environment” Team was started in January 2008.
Its scientific research theme was previously included in the M2S research axes.
The ERA team has defined its research objectives from the theme of autonomic networking.
This key theme (a solution to the complexity of present networks) is far-reaching as it combines the field of network architecture, protocols, management and monitoring and also the tools which will be the backbone of future autonomic networks. Team activities go from low layers to application layers through protocol stacks.