Wee Siong Ng

PeerDB: a P2P-based system for distributed data sharing

We present the design and evaluation of PeerDB, a peer-to-peer (P2P) distributed data sharing system. PeerDB distinguishes itself from existing P2P systems in several ways. First, it is a full-fledge data management system that supports fine-grain content-based searching. Second, it facilitates sharing of data without shared schema. Third, it combines the power of mobile agents into P2P systems to perform operations at peers sites. Fourth, PeerDB network is self-configurable, i.e., a node can dynamically optimize the set of peers that it can communicate directly with based on some optimization criterion. By keeping peers that provide most information or services in close proximity (i.e., direct communication), the network bandwidth can be better utilized and system performance can be optimized. We implemented and evaluated PeerDB on a cluster of 32 Pentium II PCs. Our experimental results show that PeerDB can effectively exploit P2P technologies for distributed data sharing.

An adaptive peer-to-peer network for distributed caching of OLAP results

Peer-to-Peer (P2P) systems are becoming increasingly popular as they enable users to exchange digital information by participating in complex networks. Such systems are inexpensive, easy to use, highly scalable and do not require central administration. Despite their advantages, however, limited work has been done on employing database systems on top of P2P networks.Here we propose the PeerOLAP architecture for supporting On-Line Analytical Processing queries. A large number low-end clients, each containing a cache with the most useful results, are connected through an arbitrary P2P network. If a query cannot be answered locally (i.e. by using the cache contents of the computer where it is issued), it is propagated through the network until a peer that has cached the answer is found. An answer may also be constructed by partial results from many peers. Thus PeerOLAP acts as a large distributed cache, which amplifies the benefits of traditional client-side caching. The system is fully distributed and can reconfigure itself on-the-fly in order to decrease the query cost for the observed workload. This paper describes the core components of PeerOLAP and presents our results both from simulation and a prototype installation running on geographically remote peers.

BestPeer: a self-configurable peer-to-peer system

We present BestPeer, a prototype P2P system that we have implemented at the National University of Singapore. BestPeer is a generic P2P system designed to serve as a platform on which P2P applications can be developed easily and efficiently. The network consists of two types of entities: a large number of computers (nodes), and a relatively fewer number of location independent global name lookup (LIGLO) servers. Each participating node runs the BestPeer (Java-based) software and will be able to communicate or share resources with any other nodes (i.e., peers) in the BestPeer network. Each node comprises two types of data: private data and sharable data. Nodes can only access peers data that are sharable.

BuddyWeb: A P2P-Based Collaborative Web Caching System

The peer-to-peer (P2P) computing model has been increasingly deployed for a wide variety of applications, including data mining, replica placement, resource trading, data management and file sharing (see [1,2]). In this paper, we look at yet another application - that of collaborative web caching. Unlike existing web caching techniques that are typically managed at the proxies, we look at how to exploit local caches of nodes (or rather PCs) within an enterprise network.

A content-based resource location mechanism in PeerIS

With the flurry of research on P2P computing, many P2P technical challenges have emerged, one of which is how to efficiently locate desired resources. Advances have been made in this hot research field, where the pioneers are Pastry, CAN, Chord, and Tapestry. By using the functionality of a distributed hash table, they have achieved fair effectiveness. However they have many common limitations, such as ignoring the autonomous nature of peers, and just supporting weakly semantic functions. According to reality in the distributed network, we propose a content-based location mechanism, which not only keeps the autonomy of peers, but also supports approximate query and finer granularity of content sharing. Furthermore, this mechanism also facilitates P2P system to evolve dynamically. We have also used PeerIS, a P2P based information system used to verify it and obtained satisfactory results.

PeerDB: peering into personal databases

In this demonstration, we present a prototype peer-topeer (P2P) application called PeerDB[2] that provides database capabilities. This system has been developed at the National University of Singapore in collaboration with Fudan University, and is being enhanced with more features and applications. The concept behind PeerDB is similar to the analogy of publishing personal web sites, except that it is now applied to personal databases. Unlike personal web sites which are usually hosted together in a central web server, personal databases are stored in the person’s own PC. In addition, it is increasingly common for people to keep their data in common personal DBMS like MySQL, and MSAccess. Therefore, a PeerDB node allows an user to index and publish his/her personal database for other peers to query. PeerDB builds on and extends BestPeer [1] for DBMS applications. Briefly, BestPeer is a generic P2P system designed to serve as a platform to develop P2P applications easily and efficiently. It has the following features: (1) It employs mobile agents; (2) It shares data at a finer granularity as well as computational power; (3) It can dynamically reconfigure the BestPeer network so that a node is always directly connected to peers that provide the best service; (4) It employs a set of location independent global name lookup (LIGLO) servers to uniquely recognize nodes whose IP addresses may change as a result. In the PeerDB network, a set of PeerDB nodes communicate or share resources with each other. Each node comprises four components that are loosely integrated: (a) a data management system (we used MySQL in our implementation) that facilitates storage, manipulation and retrieval of the data at the node, and the associated local and export dictionaries that reflect the meta-data (schema and keywords); (b) a database agent system called DBAgent that provides the environment for mobile agents to operate on; (c) a cache manager for managing remote meta-data and data in secondary storage; and (d) a user-friendly user interface. PeerDB has several distinguishing features. First, it allows users to query data without knowing the schema of data in other nodes. To address this issue, we adopt an Informa-

Answering similarity queries in peer-to-peer networks

A variety of Peer-to-Peer (P2P) systems for sharing digital information are currently available and most of them perform searching by exact key matching. In this paper we focus on similarity searching and describe FuzzyPeer, a generic broadcast-based P2P system which supports a wide range of fuzzy queries. As a case study we present an image retrieval application implemented on top of FuzzyPeer. Users provide sample images whose sets of features are propagated through the peers. The answer consists of the top-k most similar images within the query horizon. In our system the participation of peers is ad-hoc and dynamic, their functionality is symmetric and there is no centralized index. In order to avoid ∞ooding the network with messages, we develop a technique that takes advantage of the fuzzy nature of the queries. Speciflcally, some queries are frozen inside the network, and are satisfled by the streaming results of similar queries that are already running. We describe several optimization techniques for single and multiple-attribute queries, and study their tradeofis. We evaluate the performance of our algorithms by a prototype implementation on our P2P platform and a simulated large-scale network. Our results suggest that by reusing the existing streams, the scalability of the system improves both in terms of number of nodes and query throughput.

Efficient range queries and fast lookup services for scalable p2p networks

In this paper we propose a Peer-To-Peer (P2P) architecture using a tree based indexing scheme which allows for efficient lookup and range query services on documents in the network. We also present a basic load balancing technique by assigning a new node that joins the network to a heavily loaded area to take on some of load of its peers. Given a query, we need to search only a small number of nodes to locate matching documents hence making the architecture scalable. We also take into account the fact that nodes in a P2P environment need not have the same capability. We implemented a simulator and performed experiments to study to the performance of our proposed architecture. The results show that our proposed architecture is scalable and highly efficient when handling range queries.

Identifying tourists from public transport commuters

Tourism industry has become a key economic driver for Singapore. Understanding the behaviors of tourists is very important for the government and private sectors, e.g., restaurants, hotels and advertising companies, to improve their existing services or create new business opportunities. In this joint work with Singapores Land Transport Authority (LTA), we innovatively apply machine learning techniques to identity the tourists among public commuters using the public transportation data provided by LTA. On successful identification, the travelling patterns of tourists are then revealed and thus allow further analyses to be carried out such as on their favorite destinations, region of stay, etc. Technically, we model the tourists identification as a classification problem, and design an iterative learning algorithm to perform inference with limited prior knowledge and labeled data. We show the superiority of our algorithm with performance evaluation and comparison with other state-of-the-art learning algorithms. Further, we build an interactive web-based system for answering queries regarding the moving patterns of the tourists, which can be used by stakeholders to gain insight into tourists travelling behaviors in Singapore.

A Distributed Ranking Strategy in Peer-to-Peer Based Information Retrieval Systems

The state of the art of P2P-based information retrieval is still at its infant stage and confronted with many challenges. One of the most urgent problems is how to rank the results retrieved from different peers. In this paper, we propose a fully distributed strategy to address this challenge. First, we identify the underlying diathesis resulting in the problem. Then we propose a fully distributed strategy to rank and merge results retrieved from different sites, including fully distributed statistics management and distributed ranking processing. Finally, we conduct an extensive experimental study to evaluate the strategy and the results verify the effectiveness of our solution.