Greedy routing and virtual coordinates for future networks

At the core of the Internet, routers are continuously struggling with ever-growing routing and forwarding tables. Although hardware advances do accommodate such a growth, we anticipate new requirements e.g. in data-oriented networking where each content piece has to be referenced instead of hosts, such that current approaches relying on global information will not be viable anymore, no matter the hardware progress. In this thesis, we investigate greedy routing methods that can achieve similar routing performance as today but use much less resources and which rely on local information only. To this end, we add specially crafted name spaces to the network in which virtual coordinates represent the addressable entities. Our scheme enables participating routers to make forwarding decisions using only neighbourhood information, as the overarching pseudo-geometric name space structure already organizes and incorporates "vicinity" at a global level. A first challenge to the application of greedy routing on virtual coordinates to future networks is that of "routing dead-ends" that are local minima due to the difficulty of consistent coordinates attribution. In this context, we propose a routing recovery scheme based on a multi-resolution embedding of the network in low-dimensional Euclidean spaces. The recovery is performed by routing greedily on a blurrier view of the network. The different network detail-levels are obtained though the embedding of clustering-levels of the graph. When compared with higher-dimensional embeddings of a given network, our method shows a significant diminution of routing failures for similar header and control-state sizes. A second challenge to the application of virtual coordinates and greedy routing to future networks is the support of "customer-provider" as well as "peering" relationships between participants, resulting in a differentiated services environment. Although an application of greedy routing within such a setting would combine two very common fields of today's networking literature, such a scenario has, surprisingly, not been studied so far. In this context we propose two approaches to address this scenario. In a first approach we implement a path-vector protocol similar to that of BGP on top of a greedy embedding of the network. This allows each node to build a spatial map associated with each of its neighbours indicating the accessible regions. Routing is then performed through the use of a decision-tree classifier taking the destination coordinates as input. When applied on a real-world dataset (the CAIDA 2004 AS graph) we demonstrate an up to 40% compression ratio of the routing control information at the network's core as well as a computationally efficient decision process comparable to methods such as binary trees and tries. In a second approach, we take inspiration from consensus-finding in social sciences and transform the three-dimensional distance data structure (where the third dimension encodes the service differentiation) into a two-dimensional matrix on which classical embedding tools can be used. This transformation is achieved by agreeing on a set of constraints on the inter-node distances guaranteeing an administratively-correct greedy routing. The computed distances are also enhanced to encode multipath support. We demonstrate a good greedy routing performance as well as an above 90% satisfaction of multipath constraints when relying on the non-embedded obtained distances on synthetic datasets. As various embeddings of the consensus distances do not fully exploit their multipath potential, the use of compression techniques such as transform coding to approximate the obtained distance allows for better routing performances

Virtual Network Stacks

In this paper, we get inspiration from peer to peer file sharing networks to provide a new way of inter-networking. In our proposal, nodes having access to multiple network types can share their networking resources with other peers residing in networks with different protocols and (potentially) different addressing schemes. Such neighbor nodes will form a peer to peer overlay backbone; the purpose of it being to offer to applications and protocols access to remote network stacks that their running hosts do not implement or have no direct access to. This creates RPC-like access to foreign network stacks well in line with a federation approach that avoids introducing a global overlay for integrating heterogeneous networks

The Autonomic Network Architecture (ANA)

The objective of autonomic networking is to enable the autonomous formation and parametrization of nodes and networks by letting protocols sense and adapt to the networking environment at run time. Besides its dynamic aspects, a core requirement of autonomic networking is to define a structured framework and execution environment that enables algorithms to operate in a continously changing environment. This paper presents the major design principles of the Autonomic Network Architecture (ANA) and reports on a first implementation. The guiding principle of ANA is to strive for flexibility and genericity at all levels of the architecture. In our approach we explicitly avoid to impose a "one-size-fits-all'' architecture (where communication protocols and paradigms are fixed by the architecture). To this end, ANA introduces generic abstractions, for example "information dispatch points'' instead of addressable endpoints, as well as communication primitives that support network heterogeneity, adaptability, and evolution. These core abstractions allow for the coexistance of multiple and diverse networking styles and protocols. With the public release of the ANA prototype, we aim at federating autonomics related networking projects, enabling different actors to share, compare, and build upon each other's work. The ANA runtime can host clean slate network designs as well as legacy Internet technology and serves as a platform for demonstrating autonomic communication principles.