On Degree-Based Decentralized Search in Complex Networks

Computer Communications, 2008

We propose a P2P search solution, called EZSearch, that enables efficient multidimensional search for remotely located contents that best match the search criteria. EZSearch is a hierarchical approach; it organizes the network into a hierarchy in a way fundamentally different from existing search techniques. EZSearch is based on Zigzag, a P2P overlay architecture known for its scalability and robustness under network growth and dynamics. The indexing architecture of EZSearch is built on top of the Zigzag hierarchy, that allows both k-nearest-neighbor and range queries to be answered with low search overhead and worst-case search time logarithmic with the network size. The indices are fairly distributed over a small number of nodes at a modest cost for index storage and update. The performance results of EZSearch drawn from our performance study are encouraging.

Lecture Notes in Computer Science, 2009

We present a decentralized self-X architecture for distributed neighborhood based search problems using an overlay network based on random graphs. This approach provides a scalable and robust architecture with low requirements for bandwidth and computational power as well as an adequate neighborhood topology, e.g. for several instances of parallel local search and distributed learning. Together with an adapted load balancing schema our architecture is self-organizing, self-healing and self-optimizing.

Europhysics Letters (EPL), 2006

The ability to perform an efficient search in a complex network is of great importance in real-world systems. We suggest a method for searching for nodes when the source does not possess full information about the shortest path to the destination. By assigning new short names to nodes we are able to reduce significantly the amount of information stored at the nodes, such that the required memory needed scales only logarithmically with the network size; yet we succeed in finding the destination node through paths very close in distance to the shortest ones. The method is shown to perform particularly well on scale-free networks, exploiting its unique characteristics. This, together with other properties, makes our method extremely useful for realistic systems such as the Internet.

2005

This paper presents an analytical framework to study search strategies in large-scale decentralized unstructured peer-to-peer (P2P) networks. The peers comprising the P2P network and their application-level connections are modeled as generalized random graphs (GRGs) whose simple and efficient analysis is accomplished using the generating function of the graph's degree distribution.

Sufficient uptime is the main concern in a distributed system where there is no centralized organization and control. Therefore searching in P2P file sharing systems is still a big problem due to the high churn rate of nodes. To find a particular piece of data within the network P2P systems explicitly or implicitly provide a lookup mechanism, which largely depends on the availability of nodes. In this paper we propose a stable node based ranking technique by detecting reliable nodes with adequate uptime by nature to ensure efficient searching and un-interruption during the data receiving. We have simulated an unstructured file-sharing environment to evaluate our proposed technique.

In order to use Internet resources efficiently we need to search and locate information efficiently. System performance diminishes by either duplicating a large quantity of data on each and every node or flooding query to all the nodes in the network. Firstly, this paper reviews various searching algorithms. Search techniques can be classified as blind search in which information about neighbors is not kept by the peer and informed search where peers store information for routing queries to other nodes. It discusses how range queries can be processed efficiently by rotating scheme over structured P2P systems and secure searching algorithm based on topology adaptation which penalizes the malicious peers. Genetic algorithm providing parallel search are also covered in the paper. Lastly, it focuses on merits, demerits and applicability of these algorithms in different situations.

Lecture Notes in Computer Science, 2004

In this paper, we report a decentralized algorithm, termed ImmuneSearch, for searching p2p networks. ImmuneSearch avoids query message flooding; instead it uses an immune-systems-inspired concept of proliferation and mutation for message movement. In addition, a protocol is formulated to change the neighborhoods of the peers based upon their proximity with the queried item. This results in topology evolution of the network whereby similar contents cluster together. The topology evolution help the p2p network to develop 'memory', as a result of which the search efficiency of the network improves as more and more individual peers perform searches. Moreover, the algorithm is extremely robust and its performance is stable even when peers are transient.

2005

Existing cluster-based searching schemes in unstructured peer-to-peer (P2P) networks employ flooding/random forwarding on connected dominating sets (CDS) of networks. There exists no upper bound on the size of CDS of a network. Both flooding and CDS hinder query efficiency. Random forwarding worsens the recall ratio. In this paper, we propose a cluster-based searching scheme that intelligently forward queries on the maximum independent sets (MIS) of networks. Our approach partitions the entire network into disjoint clusters with one clusterhead (CH) per cluster. CHs form a MIS and are connected through gateway nodes. Each node takes one role, a CH, a gateway, or an ordinary node. A CH looks up the data for the entire cluster using data summaries of cluster members, which are represented by bloom filters. Between clusters, CHs intelligently forward queries via gateways to the best neighbor CHs that are most likely to return query results. The experimental results demonstrate that our scheme greatly improves the query efficiency without degrading the quality of the query results, compared to existing approaches.

When searching for specific nodes in a network an agent hops from one node to another by traversing network links. If the network is large, the agent typically possesses partial background knowledge or certain intuitions about the network. This background knowledge steers the agent's decisions when selecting the link to traverse next. In previous research two types of background knowledge have been applied to design and evaluate search algorithms: homophily (node similarity) and node popularity (typically represented by the degree of the node). In this paper we present a method for evaluating the relative importance of those two features for an e cient network search. Our method is based on a probabilistic model that represents those two features as a mixture distribution, i.e. as a convex combination of link selection probabilities based on the candidate node popularity and similarity to a given target node in the network. We also demonstrate this method by analyzing four networks, including social as well as information networks. Finally, we analyze strategies for dynamically adapting the mixture distribution during navigation. The goal of our analysis is to shed more light into appropriate configurations of the background knowledge for e cient search in various networks. The preliminary results provide promising insights into the influence of structural features on network search e ciency.

Computing Research Repository, 2002

We review a number of message-passing algorithms that can be used to search through power-law networks. Most of these algorithms are meant to be improvements for peer-to-peer file sharing systems, and some may also shed some light on how unstructured social networks with certain topologies might function relatively efficiently with local information. Like the networks that they are designed for,

Proceedings IEEE INFOCOM 2005. 24th Annual …, 2005

Efficient discovery of information, based on partial knowledge, is a challenging problem faced by many large scale distributed systems. This paper presents a peer-to-peer search protocol that addresses this problem. The proposed system provides an efficient mechanism for advertising a binary pattern, and discovering it using any subset of its 1-bits. A pattern (e.g., Bloom filter) summarizes the properties (e.g., keywords or service description) associated with a shared object (e.g., document or service).

Lecture Notes in Computer Science, 2005

Performing efficient decentralized search is a fundamental problem in Peer-to-Peer (P2P) systems. There has been a significant amount of research recently on developing robust self-organizing P2P topologies that support efficient search. In this paper we discuss four structured and unstructured P2P models (CAN, Chord, PRU, and Hypergrid) and three characteristic search algorithms (BFS, k-Random Walk, and GAPS) for unstructured networks. We report on the results of simulations of these networks and provide measurements of search performance, focusing on search in unstructured networks. We find that the proposed models produce small-world networks, and yet none exhibit power-law degree distributions. Our simulations also suggest that random graphs support decentralized search more effectively than the proposed unstructured P2P models. We also find that on these topologies, the basic breadth-first search algorithm and its simple variants have the lowest search cost.

International Journal of Computer Applications, 2013

Peer-to-Peer (P2P) [1] are widely used for file sharing purposes. This type of usage provides decentralized solutions over centralized complex architecture. Peer-to-Peer networks are gaining attention from both the scientific perspective as well as the large Internet community. Popular applications utilizing this new technology offer many attractive features to a growing number of users. P2P is an architecture which is all-together a different class of applications that use the concept of distributed resources to perform an important crucial function in a decentralized manner. The popularity and bandwidth consumption attributed to current Peer-to-Peer filesharing applications makes the operation of these distributed systems very important for the Internet community. Efficiently discovering the queried resource is the initial and most important step in establishing an efficient peer-to-peer communication. Here, we will be describing and analyzing the performances of some existing search mechanisms deployed for the peer discovery and the content look up.

2005