Hierarchical P2P Architecture Research Articles

Hierarchical P2P architecture for efficient content distribution

Mutualcast is a one-to-many (peer-to-peer) scheme for content distribution that maximizes the overall throughput during a broadacast session. It is based on a fully-connected graph (full mesh topology), which introduces benefits such as robustness or simultaneous transmission from/to multiple devices. The main disadvantage of Mutualcast is scalability; it is constraint to a small P2P group for content distribution. In this paper, we make Mutualcast scalable. We propose a highly collaborative and scalable P2P tree-based architecture made of two main components: 1) Peer grouping or clustering and 2) Hierarchical tree-based content distribution. In step 1), peer nodes (content receivers) are grouped into equal-size clusters by using a proposed heuristic size-constrained algorithm based on k-means. In step 2), clusters (which become the nodes of the tree) are organized into a single hierarchical n-ary tree-based architecture, in which the root of the tree (Root Cluster) is the one closest to source peer, while intermediate and leaf clusters are positioned in the tree according to their delay-proximity to previously inserted clusters. During content distribution, the root cluster receives the blocks of content before any other cluster in the tree and directly from (and only from) the source peer; blocks are then passed on to the next hierarchical level down the tree in order (higher levels of the tree receive the content before lower levels). Inter-clusters and intra-clusters content distribution is performed concurrently and takes into account peers upload/download capacities to relay blocks of content. The evaluation of our hierarchical P2P architecture concentrates on the following metrics: scalability of the systems, overall end-to-end delay distribution, and efficient cluster size. Finally, our architecture is compared against two well-known P2P technologies in the literature, Super-Peer and Kademlia.

A scalable and hierarchical P2P architecture based on Pancake graph for group communication

A scalable and hierarchical P2P architecture based on Pancake graph for group communication

A Tag-Based Scheme to Realize Real-Time File Search in Hierarchical Peer-to-Peer Systems

In this paper, we propose a new method to realize quick update of information concerned with shared contents in Peer-to-Peer (P2P) networks. The proposed method is a combination of a hierarchical P2P architecture and a tag-based file management scheme. The hierarchical architecture consists of three layers: the top layer consisting of a collection of central servers, the middle layer consisting of a set of sub-servers, and the bottom layer consisting of a number of user peers. Indexes of files held by each user peer are stored at the sub-servers in the middle layer, and the correlation between file indexes and sub-servers is maintained by central servers using tags. We implemented a prototype of the proposed method using Java, and evaluated the performance through simulations using PeerSim 1.0.4. The results of our experiments indicate that the proposed method is a good candidate for “real-time search engines” in P2P systems; e.g., it completes an upload of 10, 000 file indexes to the relevant sub-servers in a few minutes and achieves query forwarding to relevant peers within 100ms.

A Content-Based Multilevel Caching Policy for Super-Peer Networks

We propose a novel scheme, called Content-based Multilevel Caching Policy (CMCP) for super-peer networks that support hierarchical P2P architecture. Peers share information according the content between peers and between shared files to self-organise into clustered groups. Simulation experiments show that the CMCP policy achieves significant improvements in terms of access latency and global cache hit ratio.