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Distributed Indexing Networks for Efficient Large-Scale Group Communication
Abstract
Recently a new category of communication network paradigms has emerged: overlay networks for content distribution and group communication, application level multicast and distributed hash tables for efficient indexing and look-up of network resources, etc. As these ideas mature, new Internet architectures emerge. The authors describe here an autonomic, self-optimizing, network virtualization middleware architecture designed for large scale distributed applications. The proposed architecture uses end-hosts and proxies at the edge of the network as the forwarding nodes for distributing content to multiple receivers using simple point-to-point communication. Routing nodes have the capability to process the content prior to forwarding to meet the heterogeneous requirements of receivers. The proposed architecture builds upon a new network abstraction. Distributed indexing networks (DIN) is a new paradigm of communication networks design that relies on assigning indices to communication entities, communication infrastructure nodes and distributed infrastructure resources to control and disseminate information. DINs are in essence overlay networks whose topology is defined by a set of connectivity rules on indices assigned to network nodes. DINs route data packets using network indices (identifiers) and descriptors contained in the application level routing header; messages are routed hop by hop by querying at each node an application level routing indexing structure. As an application of DINs, the authors present an index-based routing multicast protocol together with its distribution tree optimization algorithm. To support applications involving large dynamic multicast groups, the application level multicast scheme uses hierarchical group membership aggregation and stateless forwarding within clusters of network nodes. The authors define the information space (IS) as the multidimensional space that indexes all information available in the network. The information includes infrastructure information (network nodes addresses, storage nodes location), network measurements data, distributed content descriptors, communication group identifiers, real-time published streams and other application dependent communication semantics, etc. The entity communication interest (ECI) is the vector describing the time-dependent information preferences of a network entity (multicast group client, user, etc.). Communication control architecture partitions the IS into interest cells mapped to multicast communication groups. The proposed control algorithm uses proximity-based clustering of network nodes and hierarchical communication interest aggregation to achieve scalability. The authors show that large-scale group communication in the proposed distributed indexing networks requires low computation overhead with a controlled degradation of the end-to-end data path performance.
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