Sastry S. Duri

Personalization of Supermarket Product Recommendations

We describe a personalized recommender system designed to suggest new products to supermarket shoppers. The recommender functions in a pervasive computing environment, namely, a remote shopping system in which supermarket customers use Personal Digital Assistants (PDAs) to compose and transmit their orders to the store, which assembles them for subsequent pickup. The recommender is meant to provide an alternative source of new ideas for customers who now visit the store less frequently. Recommendations are generated by matching products to customers based on the expected appeal of the product and the previous spending of the customer. Associations mining in the product domain is used to determine relationships among product classes for use in characterizing the appeal of individual products. Clustering in the customer domain is used to identify groups of shoppers with similar spending histories. Cluster-specific lists of popular products are then used as input to the matching process.The recommender is currently being used in a pilot program with several hundred customers. Analysis of results to date have shown a 1.8% boost in program revenue as a result of purchases made directly from the list of recommended products. A substantial fraction of the accepted recommendations are from product classes new to the customer, indicating a degree of willingness to expand beyond present purchase patterns in response to reasonable suggestions.

Framework for security and privacy in automotive telematics

Automotive telematics may be defined as the information-intensive applications that are being enabled for vehicles by a combination of telecommunications and computing technology. Telematics by its nature requires the capture of sensor data, storage and exchange of data to obtain remote services. In order for automotive telematics to grow to its full potential, telematics data must be protected. Data protection must include privacy and security for end-users, service providers and application providers. In this paper, we propose a new framework for data protection that is built on the foundation of privacy and security technologies. The privacy technology enables users and service providers to define flexible data model and policy models. The security technology provides traditional capabilities such as encryption, authentication, non-repudiation. In addition, it provides secure environments for protected execution, which is essential to limiting data access to specific purposes.

An application of Petri net reduction for Ada tasking deadlock analysis

As part of our continuing research on using Petri nets to support automated analysis of Ada tasking behavior, we have investigated the application of Petri net reduction for deadlock analysis. Although reachability analysis is an important method to detect deadlocks, it is in general inefficient or even intractable. Net reduction can aid the analysis by reducing the size of the net while preserving relevant properties. We introduce a number of reduction rules and show how they can be applied to Ada nets, which are automatically generated Petri net models of Ada tasking. We define a reduction process and a method by which a useful description of a detected deadlock state can be obtained from the reduced nets information. A reduction tool and experimental results from applying the reduction process are discussed.

Application and experimental evaluation of state space reduction methods for deadlock analysis in Ada

An emerging challenge for software engineering is the development of the methods and tools to aid design and analysis of concurrent and distributed software. Over the past few years, a number of analysis methods that focus on Ada tasking have been developed. Many of these methods are based on some form of reachability analysis, which has the advantage of being conceptually simple, but the disadvantage of being computationally expensive. We explore the effectiveness of various Petri net-based techniques for the automated deadlock analysis of Ada programs. Our experiments consider a variety of state space reduction methods both individually and in various combinations. The experiments are applied to a number of classical concurrent programs as well as a set of “real-world” programs. The results indicate that Petri net reduction and reduced state space generation are mutually beneficial techniques, and that combined approaches based on Petri net models are quite effective, compared to alternative analysis approaches.

An approach to providing a seamless end-user experience for location-aware applications

With an increasing number of businesses considering the possibility of launching location-aware, mobile commerce applications, the quality of the end-user experience will become more and more critical. We propose dynamic bookmarks and location domains as mechanisms to give consumers simple and straightforward access to a dynamically changing set of location-based services. Dynamic bookmarks are descriptions of services, which are bound to actual, registered, services as a users location changes. Location domains provide meaningful location context for location-aware services. We discuss the motivation and background of our work in progress, describe the key concepts involved, and present a system architecture we have adopted.

The Design and Implementation of a Smart Building Control System

A significant proportion of total worldwide energy is consumed by buildings. For example, buildings in the US account for about 40 percent of total energy consumption and greenhouse gas emission. Making buildings more energy-efficient is an important step to reduce our energy consumption and carbon emission in the combat with global climate change. Broad participation by consumers, business owners, and governments is required to continuously improve on energy efficiency for new and existing buildings and to achieve the global greenhouse gas emission reduction objectives. This paper provides a software system perspective of improving energy efficiency for buildings. It proposes an architecture that allows for phased investments in technologies to capture the returns from energy savings in various use cases. In addition, it addresses the needs and objectives of different stakeholders, including owners, operators, users, and utility providers. A proof-of-concept implementation of the architecture is used to demonstrate the support for building-wide energy conservation policies using real-time energy pricing and individual occupants’ locations and preferences. It shows that the proposed architecture enables fine-grained building control and reduces energy consumption while maximizing its occupants’ comfort.

The Coyote Project: Framework for Multi-party E-Commerce

The Internet provides the opportunity for quickly setting up deals between businesses for promoting each others products, and to jointly offer new services. Specification and enforcement of such deals stretch traditional transaction processing concepts in several directions since they involve independent businesses with their own internal processes. First, the greater variability in response time in business to business interaction creates a need for asynchronous and event-driven processing, in which correct handling of reissued and cancelled requests is critical. Second, a new transaction processing paradigm is required that supports different views of a unit of business for all participants, i.e., service providers as well as end consumers. Between any two interacting parties, there may be several related interactions dispersed in time, creating a long running conversation. This paper describes our approach (Coyote) to solving these problems including use of a service contract for specifying the rules of interaction across businesses, and directly generating code for enforcement of the contract. We finally describe the architecture and a prototype of a system which implements the Coyote concepts.

Data protection and data sharing in telematics

Automotive telematics may be defined as the information-intensive applications enabled for vehicles by a combination of telecommunications and computing technology. Telematics by its nature requires the capture, storage, and exchange of sensor data to obtain remote services. Such data likely include personal, sensitive information, which require proper handling to protect the drivers privacy. Some existing approaches focus on protecting privacy through anonymous interactions or by stopping information flow altogether. We complement these by concentrating instead on giving different stakeholders control over data sharing and use. In this paper, we identify several data protection challenges specifically related to the automotive telematics domain, and propose a general data protection framework to address some of those challenges. The framework enables data aggregation before data is released to service providers, which minimizes the disclosure of privacy sensitive information. We have implemented the core component, the privacy engine, to help users manage their privacy policies and to authorize data requests based on policy matching. The policy manager provides a flexible privacy policy model that allows data subjects to express rich constraint-based policies, including event-based, and spatio-temporal constraints. Thus, the policy engine can decide on a large number of requests without user assistance and causes no interruptions while driving. A performance study indicates that the overhead is stable with an increasing number of data subjects.

RFID Meets the Internet

After several years of development, networked RFID is moving beyond the early adopter phase as more and more industry sectors are using this technology for increasingly diverse applications. Two main technological advances have made this possible: the wider availability of very low-cost and higher-range passive RFID tags that require no battery to operate, and the use of the Internet to interconnect standalone RFID systems and software through robust fixed- and mobile-communication networks. This special issue presents some recent work in RFID middleware, services, overlaying, and the network edge.

Using state space reduction methods for deadlock analysis in Ada tasking

Over the past few years, a number of research investigations have been initiated for static analysis of concurrent and distributed software. In this paper we report on experiments with various optimization techniques for reachability-based deadlock detection in Ada programs using Petri net models. Our experimental results show that various optimization techniques are mutually beneficial with respect to the effectiveness of the analysis.