On Using Multi-agent Systems in End to End Adaptive Monitoring

Merghem, Leïla; Gaïti, Dominique; Pujolle, Guy

doi:10.1007/978-3-540-39404-4_32

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…Meskaoui et al [11] propose to manage a DiffServ network architecture by using a MAS. In Merghem et al [12], the idea is to monitor end-to-end fl ows thanks to agents collaborating within MAS. Bieszczad et al [13] discuss the benefi ts of using mobile agents to manage the whole network.…”

Section: Our Multi-agent Systems-based Approachmentioning

confidence: 99%

A situatedness‐based Knowledge Plane for autonomic networking

Bullot

Khatoun

Hugues³

et al. 2008

Int J Network Mgmt

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SUMMARYIP networks, and particularly the Internet, were proposed to be a simple and robust support for homogeneous communications. This implies that only basic control mechanisms have to be performed by network elements. Communication management has to be performed by the terminals. However, the integration of new services and the increasing need for QoS require the network to be increasingly more fl exible and adaptive. New algorithms and protocols have been proposed by many research teams to address these issues, but these new algorithms tend to make network management and control more fl exible. Thus, manual confi guration of such fl exible and adaptive network architectures is very complex, if not impossible. Self-management is then a good opportunity to address this new complexity, and then to integrate more easily new services into the network. However, this self-management requires the equipment to carry much more knowledge and information than the actual control and management planes do. Global knowledge management schemes are therefore necessary to achieve this, including new policies for knowledge gathering, computing, sharing and providing. To address this particular need for knowledge management, several studies have proposed building a new plane, called the 'Knowledge Plane' (KP). This paper studies different propositions for this KP, and presents an original vision of what this KP should be. Our vision of the KP relies on the paradigm of situatedness. This paradigm was developed by research studies in the fi eld of multi-agent systems, which tend to solve complex problems using collaborative and autonomous agents (multi-agent technology has been largely described in Artifi cial Intelligence literature). These agents in our proposition are embedded within the network elements themselves. Their role is to share local and situated knowledge composing the global KP. We have also developed, as an illustration, a distributed intrusion detection system (IDS) based on the local IDS Snort.

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Section: Our Multi-agent Systems-based Approachmentioning

confidence: 99%

A situatedness‐based Knowledge Plane for autonomic networking

Bullot

Khatoun

Hugues³

et al. 2008

Int J Network Mgmt

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“…The approach we propose is different [16], [17], [18], [19]. In fact, every node has one cognitive agent that supervises, monitors, and manages a set of reactive agents.…”

Section: Adaptive and Autonomous Systemmentioning

confidence: 99%

Autonomous Network Equipments

Gaïti

Pujolle

Salaun

et al. 2006

Lecture Notes in Computer Science

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Abstract. IP networks are now well established. However, control, management and optimization schemes are provided in a static and basic way. Network control and management schemes using an autonomy based technology offer a new way to master quality of service, security and mobility management. This new paradigm allows a dynamic and intelligent control of the equipment in a local manner, a global network control in a cooperative manner, a more powerful network management, and a better guaranty of all vital functionalities like end to end quality of service and security. In this paper, we provide a way to implement such a paradigm through the use of the agent and multi agent concept. A testbed of an architecture based on autonomous network equipment has been developed. This autonomous architecture is able to optimize the quality of service through the networks.

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“…Their role is to share local and situated knowledge, in order to control and optimize the existing control mechanism of the router. Our work is based and inspired by several papers in the literature, including [MES03] which proposes a multi agent based architecture to share knowledge and control DiffServ; [MER03] which presents a 2 layer end to end adaptive monitoring mechanism based on collaborative agents. In a similar field, [BIE98] proposes to base the network management on a mobile agent system.…”

Section: Introductionmentioning

confidence: 99%

Towards autonomic networking and self-configurating routers

Bullot

Gaïti

2006

IFIP International Federation for Information Processing

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Abstract. IP Networks, and particularly the Internet, were proposed to be a simple and robust support for heterogeneous communications. This implies that only basic controls have to be done by network elements. Connection management, along with transport, and more generally communication management, has to be done by the terminals. For example, error detection mechanisms, error recovery mechanisms with "Slow Start", are implemented within the transport protocol, managed by the terminals. However, integration of new services and increasing need for QoS require the network to be more and more flexible and adaptive. New algorithms and protocols are then proposed to address these issues, and include new configuration layers. Manual configuration of such network architectures is then very complex, if not impossible. We think that future core network elements will have to be more adaptive, but also more autonomic. Auto configuration is indeed a necessary condition to integrate new services in the network. We believe that auto configuration requires new knowledge provisioning and computing policies. This paper then presents an architecture of software agents, collaborative and autonomic. These agents are embedded inside the routers. Their role is to share local and situated knowledge, in order to control and optimize the existing control mechanism of the router.

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On Using Multi-agent Systems in End to End Adaptive Monitoring

Cited by 10 publications

References 17 publications

A situatedness‐based Knowledge Plane for autonomic networking

A situatedness‐based Knowledge Plane for autonomic networking

Autonomous Network Equipments

Towards autonomic networking and self-configurating routers

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