ZEROTH REVIEW SSW: A SMALL-WORLD-BASED OVERLAY FOR PEER-TO-PEER SEARCH NAME
: P.DEEPASUNDARI K.HARIPRIYA S.SARANYA
ROLL NO.
:21605205007 21605205012 21605205043
DOMAIN: JAVA & NETWORKING GUIDE:Mr.K.SureshKumar
ABSTRACT Existing System In the existing system we use key based search in a Peer-to-Peer systems. For many real-life applications, the number of attributes used to identify data objects and to precisely specify queries is large. A peer-to-peer based secondary key search method and system for cluster databases is disclosed. A cluster database has a plurality of storage nodes and each storage node is assigned with a node number and stores a plurality of records. A search term input means couples to the plurality of storage nodes for retrieving a record at a storage node. The search term input means calculates a first node number based on a hash function of a secondary key, queries the first storage node with the secondary key for retrieving a corresponding primary key, calculates a second node number based on a hash function of the primary key, and then queries the second storage node with the primary key for retrieving a corresponding record.
Limitations of Existing System It is a key based search in peer-to-peer systems which is not tolerable to peer failures Needs a large storage space to store a node number of each node and to store the plurality of records. The number of attributes used to identify data objects and to precisely specify queries is large. There is no efficient algorithms to support various types of queries, including approximate point query and range query It is difficult to facilitate efficient navigation and search in a high dimensional space without incurring high maintenance overhead. Proposed System The primary goal of this study is to design a P2P overlay network that supports efficient semantic-based search. Various digital objects such as documents and multimedia can be represented and stored as data objects in P2P systems. Peer-to-peer (P2P) systems have become a popular platform for sharing and exchanging voluminous information among thousands or even millions of users. The massive amount of information shared in such systems mandates efficient semantic-based search instead of key-based search. The majority of existing proposals can only support simple key-based search rather than semantic-based search. This paper presents the design of an overlay network, namely, semantic small world (SSW) that facilitates efficient semantic-based search in P2P systems. SSW achieves the efficiency based on four ideas: Semantic clustering, where peers with similar semantics organize into peer clusters. Dimension reduction, where to address the high maintenance overhead associated with capturing high-dimensional data semantics in the overlay, peer clusters are adaptively mapped to a one-dimensional naming space,
Small world network, where peer clusters form into a one-dimensional small world network, which is search efficient with low maintenance overhead, and Efficient search algorithms, where peers perform efficient semantic-based search, including approximate point query and range query in the proposed overlay. Extensive experiments using both synthetic data and real data demonstrate that SSW is superior to the state of the art on various aspects, including scalability, maintenance overhead, adaptivity to distribution of data and locality of interest, resilience to peer failures, load balancing, and efficiency in support of various types of queries on data objects with high dimensions. Small world networks can be characterized by the average path length between two nodes in the network and the cluster coefficient, which is defined as the probability that two neighbors of a node are neighbor themselves. A network is said to be small world if it has a small average path length and large cluster coefficient. Studies on a spectrum of networks with small world characteristics show that searches can be efficiently conducted when the network has the following properties: 1) each node in the network knows its local neighbors, called short-range contacts, and 2) each node knows a small number of randomly chosen distant nodes, called long-range contacts. Based on the accumulated knowledge of clustered indexes in the database research community, it is safe to assume that clustering data objects with similar semantics close to each other and indexing them in a certain attribute order can facilitate an efficient search of these data objects based on indexed attributes. Thus, to support efficient Semantic-based search, the peer hosts and data objects should be organized in accordance with the semantic space that they are located in.