Chiang Lee

Dynamic load balancing in multicomputer database systems using partition tuning

Shared nothing multiprocessor architecture is known to be more scalable to support very large databases. Compared to other join strategies, a hash-based join algorithm is particularly efficient and easily parallelized for this computation model. However, this hardware structure is very sensitive to the skew in tuple distribution. Unless the parallel hash join algorithm includes some dynamic load balancing mechanism, the skew effect can severely deteriorate the system performance. In this paper, we investigate this issue. In particular, three parallel hash join algorithms are presented. We implement a simulator to study the effectiveness of these schemes. The simulation model is validated by comparing the simulation results to those produced by the actual implementation of the algorithms running on a multiprocessor system. Our performance study indicates that a naive approach is not able to provide tangible savings. However, the carefully designed strategies can offer substantial improvement over conventional techniques for a wide range of skew conditions.

Optimizing large join queries using a graph-based approach

Although many query tree optimization strategies have been proposed in the literature, there still is a lack of a formal and complete representation of all possible permutations of query operations (i.e., execution plans) in a uniform manner. A graph-theoretic approach presented in the paper provides a sound mathematical basis for representing a query and searching for an execution plan. In this graph model, a node represents an operation and a directed edge between two nodes indicates the older of executing these two operations in an execution plan. Each node is associated with a weight and so is an edge. The weight is an expression containing optimization required parameters, such as relation size, tuple size, join selectivity factors. All possible execution plans are representable in this graph and each spanning tree of the graph becomes an execution plan. It is a general model which can be used in the optimizer of a DBMS for internal query representation. On the basis of this model, we devise an algorithm that finds a near optimal execution plan using only polynomial time. The algorithm is compared with a few other popular optimization methods. Experiments show that the proposed algorithm is superior to the others under most circumstances.

Performance Evaluation of Forwarding Strategies for Location Management in Mobile Networks

This paper presents a methodology for evaluating the performance of forwarding strategies for location management in a personal communication services (PCS) mobile network. A forwarding strategy in the PCS network can be implemented by two mechanisms: a forwarding operation which follows a chain of databases to locate a mobile user and a resetting operation which updates the databases in the chain so that the current location of a mobile user can be known directly without having to follow a chain of databases. In this paper, we consider the PCS network as a server whose function is to provide services to the mobile user for ‘updating the location of the user as the user moves across a database boundary’ and ‘locating the mobile user’. We use a Markov chain to describe the behavior of the mobile user and analyze the best time when forwarding and resetting should be performed in order to optimize the service rate of the PCS network. We demonstrate the applicability of our approach with hexagonal and mesh coverage models for the PCS network and provide a physical interpretation of the result.

Effects of Internet Popular Opinion Leaders (iPOL) Among Internet-Using Men Who Have Sex With Men

Background The Internet has become a popular venue for facilitating sex networking for men who have sex with men (MSM). Objective The study aimed to evaluate the effectiveness of Internet popular opinion leaders (iPOL) in disseminating information about the human immunodeficiency virus (HIV), increasing the frequency of HIV testing, and reducing risky behaviors among MSM in Taiwan. Methods A quasi-experimental study with a nonequivalent control website for comparison was used to estimate the effectiveness of iPOL. A community-level intervention, iPOL, was conducted at the Facebook social networking website and at top1069 as a control. The iPOLs actively disseminated HIV-related information via the platform of Internet opinion leaders and AIDS information center, and discussed and responded to questions or replied to Internet-using MSM. Results A total of 369 iPOLs posted 432 articles and 503 replies to others, influencing 959,088 persons on Facebook. A total of 1037 MSM, 552 (53.23%) from an intervention website and 485 (46.76%) from a control website, participated in the follow-up study survey (response rate 96%). At the 6-month follow-up after the intervention was conducted, MSM who visited the intervention website were more likely to receive HIV-related information (25.49% versus 10.47%, P<.001), discuss HIV issues with others (41.88% versus 23.79%, P<.001), review articles about HIV (90.58% versus 79.73%, P<.001), and be asked about or discuss HIV-related questions (51.11% versus 31.78%, P<.001) than those on the control website. In addition, MSM were more likely to have HIV tests within 6 months (43.89% versus 22.31%, P<.001) and consistently use condoms during anal sex with online sex partners than those using the control website (34.15% versus 26.19%, P=.004). Conclusions The study showed the feasibility and effectiveness of the iPOL intervention as an online HIV prevention program. These findings underscore the importance of disseminating HIV information online, as well as the challenges inherent in the efforts of iPOL to reduce HIV-related risky behaviors among Internet-using MSM.

Agent-based forwarding strategies for reducing location management cost in mobile networks

An important issue in location management for dealing with user mobility in wireless networks is to reduce the cost associated with location updates and searches. The former operation occurs when a mobile user moves to a new location registration area and the network is being informed of the mobile users current location; the latter operation occurs when there is a call for the mobile user and the network must deliver the call to the mobile user. In this paper, we propose and analyze a class of new agent-based forwarding schemes with the objective to reduce the location management cost in mobile wireless networks. We develop analytical models to compare the performance of the proposed schemes with existing location management schemes to demonstrate their feasibility and also to reveal conditions under which our proposed schemes are superior to existing ones. Our proposed schemes are particularly suitable for mobile networks with switches which can cover a large number of location registration areas.

Continuous K-Nearest Neighbor Query for Moving Objects with Uncertain Velocity

One of the most important queries in spatio-temporal databases that aim at managing moving objects efficiently is the continuous K-nearest neighbor (CKNN) query. A CKNN query is to retrieve the K-nearest neighbors (KNNs) of a moving user at each time instant within a user-given time interval [ts, te]. In this paper, we investigate how to process a CKNN query efficiently. Different from the previous related works, our work relieves the past assumption, that an object moves with a fixed velocity, by allowing that the velocity of the object can vary within a known range. Due to the introduction of this uncertainty on the velocity of each object, processing a CKNN query becomes much more complicated. We will discuss the complications incurred by this uncertainty and propose a cost-effective P2KNN algorithm to find the objects that could be the KNNs at each time instant within the given query time interval. Besides, a probability-based model is designed to quantify the possibility of each object being one of the KNNs. Comprehensive experiments demonstrate the efficiency and the effectiveness of the proposed approach.

Continuous K-Nearest Neighbor Query over Moving Objects in Road Networks

Continuous K -Nearest Neighbor (CK NN) query is an important type of spatio-temporal queries. A CK NN query is to find among all moving objects the K -nearest neighbors (K NNs) of a moving query object at each timestamp. In this paper, we focus on processing such a CK NN query in road networks, where the criterion for determining the K NNs is the shortest network distance between objects. We first highlight the limitations of the existing approaches, and then propose a cost-effective algorithm, namely the Continuous KNN algorithm , to overcome these limitations. Comprehensive experiments are conducted to demonstrate the efficiency of the proposed approach.

Improving location management for mobile users with frequency visited locations

Abstract In wireless computing environment, users’ mobility brings new challenges to traditional computing systems. The explosive growth of demand in communication bandwidth requires new schemes to effectively and efficiently locate users. The Basic HLR/VLR locating scheme does not exploit the fact that many mobile users’ (such as commuters’) moving patterns are likely to be known. In this paper, we propose one locating scheme, the frequently visited locations first (FVLF) scheme, to efficiently locate a mobile user. The FVLF scheme is proposed to prestore the RAs that a mobile user frequently visits according to the probabilities of the RAs that the mobile user may appear. When the system receives a call, these prestored RAs are examined first to locate the callee. This scheme can avoid the high cost of querying the callee’s HLR. The cost model of the proposed scheme is derived and the optimal number of prestored RAs is also found. Our evaluation shows that benefit does exist in various conditions by using this scheme.

An aspect of query optimization in multidatabase systems

It is becoming increasingly important to manage databases as a repository resource and to allow application programs to access this resource in a heterogeneous distributed environment. Data requested by a query are sometimes available in multiple sites such that the query becomes executable in different ways. Under this circumstance, choosing the best execution plan becomes an important task for optimizing the query execution. Until today, however, query optimization in multidatabase systems has not been discussed much in the literature. In this work, we utilize the knowledge of scope relationship of relations in multidatabases to identify the sites that will return the same results. Then, we propose a novel way of optimizing queries which takes advantage of the conflicts of schemas in searching for the execution plan with the least execution cost. We achieve the goal by first classifying various schema conflicts into different types. The costs of executing the same relational operation on relations of conflicting schemas are evaluated and a weight is assigned to each of the cases to reflect the complexity of executing the operation. As this method only involves simple iterative computations of the weights and the saving of a query execution time can be dramatic, the method developed here can be regarded as an effective way of optimizing query processing in a multidatabase environment.

Top- k combinatorial skyline queries

The problem of top-k skyline computation has attracted considerable research attention in the past few years. Given a dataset, a top-k skyline returns k “most interesting” skyline tuples based on some kind of preference specified by the user. We extend the concept of top-k skyline to a so-called top-k combinatorial skyline query (k-CSQ). In contrast to the existing top-k skyline query (which is mainly to find the interesting skyline tuples), a k-CSQ is to find the interesting skyline tuples from various kinds of combinations of the given tuples. The k-CSQ is an important tool for areas such as decision making, market analysis, business planning, and quantitative economics research. In this paper, we will formally define this new problem, propose an intelligent method to resolve this problem, and also conduct a set of experiments to show the effectiveness and efficiency of the proposed algorithm.