Vladimir Zadorozhny

Contagious Diseases in the United States from 1888 to the Present

Using data from digitized weekly surveillance reports of notifiable diseases for U.S. cities and states for 1888 through 2011, the authors derived a quantitative history of disease reduction in the United States, focusing particularly on the effects of vaccination programs.

Learning response time for WebSources using query feedback and application in query optimization

Abstract. The rapid growth of the Internet and support for interoperability protocols has increased the number of Web accessible sources, WebSources. Current wrapper mediator architectures need to be extended with a wrapper cost model (WCM) for WebSources that can estimate the response time (delays) to access sources as well as other relevant statistics. In this paper, we present a Web prediction tool (WebPT), a tool that is based on learning using query feedback from WebSources. The WebPT uses dimensions time of day, day, and quantity of data, to learn response times from a particular WebSource, and to predict the expected response time (delay) for some query. Experiment data was collected from several sources, and those dimensions that were significant in estimating the response time were determined. We then trained the WebPT on the collected data, to use the three dimensions mentioned above, and to predict the response time, as well as a confidence in the prediction. We describe the WebPT learning algorithms, and report on the WebPT learning for WebSources. Our research shows that we can improve the quality of learning by tuning the WebPT features, e.g., training the WebPT using a logarithm of the input training data; including significant dimensions in the WebPT; or changing the ordering of dimensions. A comparison of the WebPT with more traditional neural network (NN) learning has been performed, and we briefly report on the comparison. We then demonstrate how the WebPT prediction of delay may be used by a scrambling enabled optimizer. A scrambling algorithm identifies some critical points of delay, where it makes a decision to scramble (modify) a plan, to attempt to hide the expected delay by computing some other part of the plan that is unaffected by the delay. We explore the space of real delay at a WebSource, versus the WebPT prediction of this delay, with respect to critical points of delay in specific plans. We identify those cases where WebPT overestimation or underestimation of the real delay results in a penalty in the scrambling enabled optimizer, and those cases where there is no penalty. Using the experimental data and WebPT learning, we test how good the WebPT is in minimizing these penalties.

Efficient evaluation of queries in a mediator for WebSources

We consider an architecture of mediators and wrappers for Internet accessible WebSources of limited query capability. Each call to a source is a WebSource Implementation (WSI) and it is associated with both a capability and (a possibly dynamic) cost. The multiplicity of WSIs with varying costs and capabilities increases the complexity of a traditional optimizer that must assign WSIs for each remote relation in the query while generating an (optimal) plan. We present a two-phase Web Query Optimizer (WQO). In a pre-optimization phase, the WQO selects one or more WSIs for a pre-plan; a pre-plan represents a space of query evaluation plans (plans) based on this choice of WSIs. The WQO uses cost-based heuristics to evaluate the choice of WSI assignment in the pre-plan and to choose a good pre-plan. The WQO uses the pre-plan to drive the extended relational optimizer to obtain the best plan for a pre-plan. A prototype of the WQO has been developed. We compare the effectiveness of the WQO, i.e., its ability to efficiently search a large space of plans and obtain a low cost plan, in comparison to a traditional optimizer. We also validate the cost-based heuristics by experimental evaluation of queries in the noisy Internet environment.

A framework for extending the synergy between MAC layer and query optimization in sensor networks

Queries in sensor networks are expected to produce results in a timely manner and for long periods, as needed. This implies that sensor queries need to be optimized with respect to both response time and energy consumption. With these requirements in mind, we develop novel cross-layer optimization techniques that utilize information about how the medium access control (MAC) layer operates while processing queries in large scale sensor network environments. The central framework of our approach is a Data Transmission Algebra that uniformly captures the structure of data transmissions along with their constraints and requirements. Our framework enables both qualitative analysis and quantitative cost-based optimization of sensor queries. We illustrate the effectiveness of our framework by developing a collision-aware scheduler and evaluating it experimentally.

Wireless Sensor Network Technologies for the Information Explosion Era

This volume aims to cover both theoretical and practical aspects related to this challenge, and it explores directions for future research to enable efficient utilization of WSNs in the information-explosion era. The book is organized in three main parts that consider (1) technical issues of WSNs, (2) the integration of multiple WSNs, and (3) the development of WSNs systems and testbeds for conducting practical experiments. Each part consists of three chapters.

A Novel Approach to Trust Management in Unattended Wireless Sensor Networks

Unattended Wireless Sensor Networks (UWSNs) are characterized by long periods of disconnected operation and fixed or irregular intervals between sink visits. The absence of an online trusted third party implies that existing WSN trust management schemes are not applicable to UWSNs. In this paper, we propose a trust management scheme for UWSNs to provide efficient and robust trust data storage and trust generation. For trust data storage, we employ a geographic hash table to identify storage nodes and to significantly decrease storage cost. We use subjective logic based consensus techniques to mitigate trust fluctuations caused by environmental factors. We exploit a set of trust similarity functions to detect trust outliers and to sustain trust pollution attacks. We demonstrate, through extensive analyses and simulations, that the proposed scheme is efficient, robust and scalable.

A User Modeling Server for Contemporary Adaptive Hypermedia: An Evaluation of the Push Approach to Evidence Propagation

Despite the growing popularity of user modeling servers, little attention has been paid to optimizing and evaluating the performance of these servers. We argue that implementation issues and their influence on server performance should become the central focus of the user modeling community, since there is a sharply increasing real-life load on user modeling servers, This paper focuses on a specific implementation-level aspect of user modeling servers --- the choice of pushor pullapproaches to evidence propagation. We present a new push-based implementation of our user modeling server CUMULATE and compare its performance with the performance of the original pull-based CUMULATE server.

An open integrated exploratorium for database courses

In this paper, we present an open architecture that combines different SQL learning tools in an integrated Exploratorium for database courses. The integrated Exploratorium provides a unique learning environment that allows database students to take complimentary advantages of multiple advanced learning tools.

Timely data delivery in sensor networks using whirlpool

In this paper, we introduce a rotating interrogation technique for sensor networks called Whirlpool. Whirlpool provides opportunities to optimize data delivery in time-critical monitoring applications. We explore concurrency opportunities while delivering data using the whirlpool strategy and investigate several whirlpool algorithms. We also demonstrate extra benefits of using whirlpool with our algebraic optimization framework based on Data Transmission Algebra.

Validating an Access Cost Model for Wide Area Applications

In this paper, we describe a case study in developing an access cost model for WebSources in the context of a wrapper mediator architecture. We document our experiences in validating this model, and note successes and lessons learned. Using experimental data of query feedback from several WebSources, we develop a Catalog and Access Cost model. We identify WebSource characteristics of the query feedback that are reflective of the particular WebSource behavior and identify groupings of WebSources based on these characteristics. We also characterize the Access Cost model as having High or Low Prediction Accuracy, with respect to its ability to predict access costs for the WebSources. We then correlate WebSource characteristics and groupings of WebSources with High or Low prediction accuracy of the model.