Guest editorial - policy-based networking

Chadha, Ritu; Lapiotis, G.; Wright, Steven A.

doi:10.1109/mnet.2002.993217

Cited by 35 publications

(11 citation statements)

References 0 publications

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“…Some, such as code-carrying packets, are quite different from the 4D approach, but others, such as creating a minimal kernel of functionality implemented on each router/switch to be invoked from another location [34] [38]. While very useful for specific tasks, network-management tools and PBN approaches usually assume the existing control-plane protocols, focus on a small portion of the configuration state (e.g., packet filters, but not routing), and do not consider the interactions among multiple mechanisms.…”

Section: Traditional Telecommunications Networkmentioning

confidence: 99%

A clean slate 4D approach to network control and management

Greenberg

Hjálmtýsson

Maltz

et al. 2005

SIGCOMM Comput. Commun. Rev.

498

265

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Today's data networks are surprisingly fragile and difficult to manage. We argue that the root of these problems lies in the complexity of the control and management planes-the software and protocols coordinating network elements-and particularly the way the decision logic and the distributed-systems issues are inexorably intertwined. We advocate a complete refactoring of the functionality and propose three key principles-network-level objectives, network-wide views, and direct control-that we believe should underlie a new architecture. Following these principles, we identify an extreme design point that we call "4D," after the architecture's four planes: decision, dissemination, discovery, and data. The 4D architecture completely separates an AS's decision logic from protocols that govern the interaction among network elements. The AS-level objectives are specified in the decision plane, and enforced through direct configuration of the state that drives how the data plane forwards packets. In the 4D architecture, the routers and switches simply forward packets at the behest of the decision plane, and collect measurement data to aid the decision plane in controlling the network. Although 4D would involve substantial changes to today's control and management planes, the format of data packets does not need to change; this eases the deployment path for the 4D architecture, while still enabling substantial innovation in network control and management. We hope that exploring an extreme design point will help focus the attention of the research and industrial communities on this crucially important and intellectually challenging area.

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Section: Traditional Telecommunications Networkmentioning

confidence: 99%

A clean slate 4D approach to network control and management

Greenberg

Hjálmtýsson

Maltz

et al. 2005

SIGCOMM Comput. Commun. Rev.

498

265

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“…Examples include epidemic algorithms [5] for distributing data, Bayesian networks for learning [4], rank aggregation to enable a web of trust [6], constraint satisfaction algorithms [21], and policy-based management techniques [23,24].…”

Section: Creating a Knowledge Plane 51 Possible Building Blocksmentioning

confidence: 99%

A knowledge plane for the internet

Clark

Partridge²,

Ramming

et al. 2003

Proceedings of the 2003 Conference on Applications, Technologies, Architectures, and Protocols for Computer Communications - S

126

133

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We propose a new objective for network research: to build a fundamentally different sort of network that can assemble itself given high level instructions, reassemble itself as requirements change, automatically discover when something goes wrong, and automatically fix a detected problem or explain why it cannot do so.We further argue that to achieve this goal, it is not sufficient to improve incrementally on the techniques and algorithms we know today. Instead, we propose a new construct, the Knowledge Plane, a pervasive system within the network that builds and maintains highlevel models of what the network is supposed to do, in order to provide services and advice to other elements of the network. The knowledge plane is novel in its reliance on the tools of AI and cognitive systems. We argue that cognitive techniques, rather than traditional algorithmic approaches, are best suited to meeting the uncertainties and complexity of our objective.

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“…Even though, paper [16] is to compare the performance of client server architecture and fault tolerance mobile agent system, and cared about security aspects too. A mobile agent is created and dispatched to the certificate authority [7,16].…”

Section: Related Workmentioning

confidence: 99%

“…Mobile code, and in particular mobile agents, will be an essential tool for allowing such access. Mobile agents are considered as a program, though they have some special properties that differentiate them from the principal programs like mandatory and orthogonal (optional) properties [5][6][7]. Agents can work without the human interruption or others, reactive or proactive decision making.…”

Section: Introductionmentioning

confidence: 99%