Articles
Pages
Products
Research Papers
Blogs
Search Engines
Events
Webinar, Seminar, Live Classes

Research Papers by Category

A Scalable Search Engine for Mass Storage Smart Objects

This paper presents a new embedded search engine designed for smart objects. Such devices are generally equipped with extremely low RAM and large Flash storage capacity. To tackle these conflicting hardware constraints, conventional search engines privilege either insertion or query scalability but cannot meet both requirements at the same time. Moreover, very few solutions support document deletions and updates in this context. In this paper, we introduce three design principles, namely WriteOnce Partitioning, Linear Pipelining and Background Linear Merging, and show how they can be combined to produce an embedded search engine reconciling high insert/delete/update rate and query scalability. We have implemented our search engine on a development board having a hardware configuration representative for smart objects and have conducted extensive experiments using two representative datasets. The experimental results demonstrate the scalability of the approach and its superiority compared to state of the art methods.

Download PDF

Get Exclusive Research Tips in Your Inbox

Receive Great tips via email, enter your email to Subscribe.
Please wait

airs logo

AIRS is the world's leading community for the Internet Research Specialist and provide a Unified Platform that delivers, Education, Training and Certification for Online Research.

Subscribe to AIRS Newsletter

Receive Great tips via email, enter your email to Subscribe.
Please wait

Follow Us on Social Media