Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/99358
Title: On selective tuning in unreliable wireless channels
Authors: Tan, K.-L. 
Ooi, B.C. 
Keywords: Access time
Selective tuning
Tuning time
Unreliable wireless channels
Wireless computing
Issue Date: Nov-1998
Citation: Tan, K.-L.,Ooi, B.C. (1998-11). On selective tuning in unreliable wireless channels. Data and Knowledge Engineering 28 (2) : 209-231. ScholarBank@NUS Repository.
Abstract: In a wireless computing environment, the server disseminates information by periodically broadcasting data on 'air', while clients 'catch' their desired data on the fly. To minimize energy consumption, these data are usually multiplexed with indexes to facilitate selective tuning. However, most of the existing mechanisms are designed with an inherent assumption that the wireless channel is reliable. But, the signals transmitted are prone to path loss, fading, interference and time dispersion. Because of these impairments, clients may receive 'corrupted' data or miss their data. The resultant effect is that clients may have to wait for the next and even subsequent broadcast cycles to receive their data correctly. This increases the access time and tuning time of data retrieval significantly. In this paper, we propose three selective tuning mechanisms for unreliable wireless channels that can effectively keep the access time low without incurring excessive tuning time. These schemes are variations of three existing schemes - tree-based, hash-based and flexible schemes. The basic idea is to continue the search process within the existing broadcast, rather than restarting the search process from the next broadcast during an access failure. We conducted an extensive simulation study to evaluate the effectiveness of these schemes. Our results demonstrate that these schemes can keep the tuning and access time low in unreliable channels. Comparatively, none of the schemes outperform each other in all cases. © 1998 Elsevier Science B.V. All rights reserved.
Source Title: Data and Knowledge Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/99358
ISSN: 0169023X
Appears in Collections:Staff Publications

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