A Modular Design for Geo-Distributed Querying: Work in Progress Report

International audienceMost distributed storage systems provide limited abilities for querying data by attributes other than their primary keys. Supporting efficient search on secondary attributes is challenging as applications pose varying requirements to query processing systems, and no single system design can be suitable for all needs. In this paper, we show how to overcome these challenges in order to extend distributed data stores to support queries on secondary attributes. We propose a modular architecture that is flexible and allows query processing systems to make trade-offs according to different use case requirements. We describe adap-tive mechanisms that make use of this flexibility to enable query processing systems to dynamically adjust to query and write operation workloads

Towards application-specific query processing systems

Database systems use query processing subsystems for enabling efficient query-based data retrieval. An essential aspect of designing any query-intensive application is tuning the query system to fit the application's requirements and workload characteristics. However, the configuration parameters provided by traditional database systems do not cover the design decisions and trade-offs that arise from the geo-distribution of users and data. In this paper, we present a vision towards a new type of query system architecture that addresses this challenge by enabling query systems to be designed and deployed in a per use case basis. We propose a distributed abstraction called Query Processing Unit that encapsulates primitive query processing tasks, and show how it can be used as a building block for assembling query systems. Using this approach, application architects can construct query systems specialized to their use cases, by controlling the query system's architecture and the placement of its state. We demonstrate the expressiveness of this approach by applying it to the design of a query system that can flexibly place its state in the data center or at the edge, and show that state placement decisions affect the trade-off between query response time and query result freshness

When the Hammer Meets the Nail: Multi-Server PIR for Database-Driven CRN with Location Privacy Assurance

We show that it is possible to achieve information theoretic location privacy for secondary users (SUs) in database-driven cognitive radio networks (CRNs) with an end-to-end delay less than a second, which is significantly better than that of the existing alternatives offering only a computational privacy. This is achieved based on a keen observation that, by the requirement of Federal Communications Commission (FCC), all certified spectrum databases synchronize their records. Hence, the same copy of spectrum database is available through multiple (distinct) providers. We harness the synergy between multi-server private information retrieval (PIR) and database- driven CRN architecture to offer an optimal level of privacy with high efficiency by exploiting this observation. We demonstrated, analytically and experimentally with deployments on actual cloud systems that, our adaptations of multi-server PIR outperform that of the (currently) fastest single-server PIR by a magnitude of times with information theoretic security, collusion resiliency, and fault-tolerance features. Our analysis indicates that multi-server PIR is an ideal cryptographic tool to provide location privacy in database-driven CRNs, in which the requirement of replicated databases is a natural part of the system architecture, and therefore SUs can enjoy all advantages of multi-server PIR without any additional architectural and deployment costs.Comment: 10 pages, double colum

Feeds as Query Result Serializations

Many Web-based data sources and services are available as feeds, a model that provides consumers with a loosely coupled way of interacting with providers. The current feed model is limited in its capabilities, however. Though it is simple to implement and scales well, it cannot be transferred to a wider range of application scenarios. This paper conceptualizes feeds as a way to serialize query results, describes the current hardcoded query semantics of such a perspective, and surveys the ways in which extensions of this hardcoded model have been proposed or implemented. Our generalized view of feeds as query result serializations has implications for the applicability of feeds as a generic Web service for any collection that is providing access to individual information items. As one interesting and compelling class of applications, we describe a simple way in which a query-based approach to feeds can be used to support location-based services

Towards OpenMath Content Dictionaries as Linked Data

"The term 'Linked Data' refers to a set of best practices for publishing and connecting structured data on the web". Linked Data make the Semantic Web work practically, which means that information can be retrieved without complicated lookup mechanisms, that a lightweight semantics enables scalable reasoning, and that the decentral nature of the Web is respected. OpenMath Content Dictionaries (CDs) have the same characteristics - in principle, but not yet in practice. The Linking Open Data movement has made a considerable practical impact: Governments, broadcasting stations, scientific publishers, and many more actors are already contributing to the "Web of Data". Queries can be answered in a distributed way, and services aggregating data from different sources are replacing hard-coded mashups. However, these services are currently entirely lacking mathematical functionality. I will discuss real-world scenarios, where today's RDF-based Linked Data do not quite get their job done, but where an integration of OpenMath would help - were it not for certain conceptual and practical restrictions. I will point out conceptual shortcomings in the OpenMath 2 specification and common bad practices in publishing CDs and then propose concrete steps to overcome them and to contribute OpenMath CDs to the Web of Data.Comment: Presented at the OpenMath Workshop 2010, http://cicm2010.cnam.fr/om

A content-based retrieval system for UAV-like video and associated metadata

In this paper we provide an overview of a content-based retrieval (CBR) system that has been specifically designed for handling UAV video and associated meta-data. Our emphasis in designing this system is on managing large quantities of such information and providing intuitive and efficient access mechanisms to this content, rather than on analysis of the video content. The retrieval unit in our system is termed a "trip". At capture time, each trip consists of an MPEG-1 video stream and a set of time stamped GPS locations. An analysis process automatically selects and associates GPS locations with the video timeline. The indexed trip is then stored in a shared trip repository. The repository forms the backend of a MPEG-211 compliant Web 2.0 application for subsequent querying, browsing, annotation and video playback. The system interface allows users to search/browse across the entire archive of trips and, depending on their access rights, to annotate other users' trips with additional information. Interaction with the CBR system is via a novel interactive map-based interface. This interface supports content access by time, date, region of interest on the map, previously annotated specific locations of interest and combinations of these. To develop such a system and investigate its practical usefulness in real world scenarios, clearly a significant amount of appropriate data is required. In the absence of a large volume of UAV data with which to work, we have simulated UAV-like data using GPS tagged video content captured from moving vehicles