Semantic-based delivery of OLAP summary tables in wireless environments

Abstract

With the rapid growth in mobile and wireless technologies and the availability, pervasiveness and cost effectiveness of wireless networks, mobile computers are quickly becoming the normal front-end devices for accessing enterprise data. In this paper, we are addressing the issue of efficient delivery of business decision support data in the form of summary tables to mobile clients equipped with OLAP front-end tools. Towards this, we propose a new on-demand scheduling algorithm, called SBS, that exploits both the derivation semantics among OLAP summary tables and the mobile clients' capabilities of executing simple SQL queries. It maximizes the aggregated data sharing between clients and reduces the broadcast length compared to the already existing techniques. The degree of aggregation can be tuned to control the tradeoff between access time and energy consumption. Further, the proposed scheme adapts well to different request rates, access patterns and data distributions. The algorithm effectiveness with respect to access time and power consumption is evaluated using simulation.

Efficient Top-k Keyword Search Over Multidimensional Databases

“…To the best of our knowledge, there is no existing work on supporting keyword search for mobile OLAP. Sharaf and Chrysanthis (2002) addresses the issue of efficient delivery of business decision support data in the form of summary tables to mobile clients equipped with OLAP front-end tools. Maniatis (2004) introduces the term Mobile OLAP to express the porting of requirements and specifications for OLAP applications into the wireless and mobile computing world.…”

A Presentation Model & Non-Traditional Visualization for OLAP

“…As a whole, as we compare CubeView with all the previously described tools -those used for visualization and those reviewed for Mobile OLAP -we stress the fact that our prototype is the only one that supports the full cycle, starting from a formal and rigorous theory background depicted in CPM itself, and reaching a full fledged implementation covering both worlds, the traditional desktop environments, and the mobile devices. All the other paradigms are departmental in the sense that the they tamper only portions of the big picture, this being either the information visualization area (VisDB [Keim & Kriegel, 1994]; HD-Eye [Hinneburg et al, 2002]; Polaris [Stolte & Hanrahan, 2000]), or specific approaches and implementations for mobile devices (Hand-OLAP [Cuzzocrea et al, 2003]) or simply middleware, like MOCHA (Rodriguez-Martinez & Rossopoulos, 2000), or, finally, a framework for a wireless OLAP model (Sharaf & Chrysanthis, 2002, Sharaf & Chrysanthis, 2002a.…”

Middleware support for multicast-based data dissemination: a working reality

“…We proposed two new, heuristic scheduling algorithms that use this derivation dependency to both maximize the aggregated data sharing between clients and reduce the broadcast length compared to the already existing techniques. The first algorithm, called Summary Tables On-Demand Broadcast Scheduler STOBS [50], is based on the RxW algorithm [1] and the second one, called Subsumption-Based Scheduler (SBS) [51], is based on the Longest Total Stretch First (LTSF) algorithm [1]. Further, they differ on the used criterion for aggregate requests.…”