An Identifier and Locator Decoupled Multicast Approach (ILDM) Based on ICN

Many bandwidth-intensive applications (such as online live, online games, etc.) are more suitable for using multicast to transmit information. Due to the advantages in scalability, Shared Tree (ST) is more suitable for large-scale deployment than Source-Based Tree (SBT). However, in ST-based multicast, all multicast sources need to send multicast data to a center node called a core, which will lead to core overload and traffic concentration. Besides, most existing multicast protocols use the shortest path between the source or the core and each receiver to construct the multicast tree, which will result in traffic overload on some links. In this paper, we propose an Identifier and Locator Decoupled Multicast approach (ILDM) based on Information-Centric Networking (ICN). ILDM uses globally unique names to identify multicast services. For each multicast service, the mapping between the multicast service name and the addresses of multicast tree nodes is stored in the Name Resolution System (NRS). To avoid core overload and traffic aggregation, we presented a dynamic core management and selection mechanism, which can dynamically select a low-load core for each multicast service. Furthermore, we designed a path state-aware multicast tree node selection mechanism to achieve traffic load balancing by using low-load links more effectively. Experimental results showed that our proposed multicast approach outperformed some other multicast methods in terms of core load, number of join requests, link load, traffic concentration, and routing state.

NPLP: An Improved Routing-Forwarding Strategy Utilizing Node Profile and Location Prediction for Opportunistic Networks

Opportunistic networks are considered as the promising network structures to implement traditional and typical infrastructure-based communication by enabling smart mobile devices in the networks to contact with each other within a fixed communication area. Because of the intermittent and unstable connections between sources and destinations, message routing and forwarding in opportunistic networks have become challenging and troublesome problems recently. In this paper, to improve the data dissemination environment, we propose an improved routing-forwarding strategy utilizing node profile and location prediction for opportunistic networks, which mainly includes three continuous phases: the collecting and updating of routing state information, community detection and optimization and node location prediction. Each mobile node in the networks is able to establish a network routing matrix after the entire process of information collecting and updating. Due to the concentrated population in urban areas and relatively few people in remote areas, the distribution of location prediction roughly presents a type of symmetry in opportunistic networks. Afterwards, the community optimization and location prediction mechanisms could be regarded as an significant foundation for data dissemination in the networks. Ultimately, experimental results demonstrate that the proposed algorithm could slightly enhance the delivery ratio and substantially degrade the network overhead and end-to-end delay as compared with the other four routing strategies.

Optimising P2P Networks by Adaptive Overlay Construction

Distributed Hash Tables (DHTs) have been used in Peer-to-Peer networks to provide query lookups in typically O(log n) messages whilst requiring maintenance of only small amounts of routing state. We propose ROME, a layer which runs on top of the Chord DHT to provide control over network size through monitoring of node workload and propose the use of processes to control the addition or removal of nodes from the network. We show that this technique can reduce further the hop counts in networks where available node capacity exceeds workload, without the need to modify any processes of the underlying Chord protocol.

Content-Based XML Data Dissemination

XML-based data dissemination networks are rapidly gaining momentum. In these networks XML content is routed from data producers to data consumers throughout an overlay network of content-based routers. Routing decisions are based on XPath expressions (XPEs) stored at each router. To enable efficient routing, while keeping the routing state small, we introduce advertisement-based routing algorithms for XML content, present a novel data structure for managing XPEs, especially apt for the hierarchical nature of XPEs and XML, and develop several optimizations for reducing the number of XPEs required to manage the routing state. The experimental evaluation shows that our algorithms and optimizations reduce the routing table size by up to 90%, improve the routing time by roughly 85%, and reduce overall network traffic by about 35%. Experiments running on PlanetLab show the scalability of our approach.