Title

Energy-Efficient Algorithms for Data Retrieval from Indexed Parallel Broadcast Channels

Abstract

The advances in mobile device and wireless communication techniques have enabled anywhere, anytime information access. Information being accessed, whether structured or unstructured, can be classified into three categories: private data, shared data, and public data. Private and shared data are usually accessed through on-demand-based services, where user request is pushed to the server(s) and response to the request is generated and passed to the user (i.e., two way communication). Public data, on the other hand, can be most effectively disseminated using broadcasting technique (i.e., one way communication). In broadcasting, server(s) generates the broadcast contents and disseminate it through the air channel. The mobile user in search of public data, tunes to the air channel and pulls the desired information. The characteristics of mobile device and limitations of wireless communication technology pose challenges on broadcasting strategy as well as data retrieval algorithms. To reduce the access time and power consumption, major research issues include indexing techniques and data organization on air channel, broadcasting over single and parallel channel(s), data distribution and replication strategy, conflict resolution, and data retrieval methods This article is intended to articulate these challenges, propose several solutions, and through comprehensive simulation demonstrate the validity of the proposed solutions.

Department(s)

Computer Science

Second Department

Electrical and Computer Engineering

Keywords and Phrases

Broadcasting; Energy Efficiency; Energy Management; Information Retrieval; Mobile Devices; Query Processing; Wireless Telecommunication Systems; Algorithm/Protocol Design And Analysis; Energy Efficient Algorithms; Parallel Broadcast Channel; Retrieval Models; Simulation Demonstrate; Two Way Communications; Wireless Communication Techniques; Wireless Communication Technology; Ubiquitous Computing

International Standard Serial Number (ISSN)

2210-5379

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Elsevier, All rights reserved.

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