Clusters of workstations/PCs connected by o?-the-shelf networks have become popular as a platform for cost-e?ective parallel computing. Hardware and so- ware technological advances have made this network-based parallel computing platform feasible. A large number of research groups from academia and industry are working to enhance the capabilities of such a platform, thereby improving its cost-e?ectiveness and usability. These developments are facilitating the mig- tion of many existing applications as well as the development of new applications on this platform. Continuing in the tradition of the two previously successful workshops, this 3rd Workshop on Communication, Architecture and Applications for Netwo- based Parallel Computing (CANPC 99) has brought together researchers and practitioners working in architecture, system software, applications and perf- mance evaluation to discuss state-of-the-art solutions for network-based parallel computing systems. This workshop has become an excellent forum for timely dissemination of ideas and healthy interaction on topics at the cutting edge in cluster computing technology. Each submitted paper underwent a rigorous review process, and was assigned to at least 3 reviewers, including at least 2 program committee members. Each paper received at least 2 reviews, most received 3 and some even had 4 reviews."

Over the past three decades, spatial information has become prevalent in numerous applications. To meet the demands of these applications, Spatial Information Management Systems have achieved greatly in storing, retrieving and processing spatial information. The continuing advancement of technologies, however, pushes the need for accessing spatial information in drastically different environments. At one end of the spectrum, the widely popular Google Map and associated Cloud Computing technologies demonstrate the power of accessing spatial information in resource-rich environments. At the other end, the growing location-based applications in Apple iPhone and Google G1 phone platforms highlight the huge potential of accessing spatial information in resource-constrained environments. This monograph is the first of its kind in analyzing spatial index structures from both energy and performance angles in resource-constrained environments. In addition to developing effective techniques to address general selectivity problems, this monograph also examines issues in accessing spatial information in resource-rich environments including clusters and the Web.