Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/75267
Title: Cross-layer adaptive end-to-end delay control for asynchronous duty-cycle wireless sensor networks
Authors: Shi, P
Wang, Y
Li, K
Chan, ATS 
Keywords: Asynchronous duty-cycle
Cross-layer
End-to-end delay
Single-hop delay model
Wireless sensor networks
Issue Date: 2014
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2014, v. 8351 LNCS, p. 520-531 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Most sensor networks require application-specific network-wide performance guarantees, suggesting the need for adaptive parameters and flexible network optimization. Since sleep scheduling degrades the end-to-end delay performance in asynchronous duty-cycle wireless sensor networks, we propose a Cross-Layer Adaptive Duty Cycle (CLA-DC) control by dynamically adjusting the sleep interval to achieve the desired end-to-end delay guarantees. CLA-DC extracts information from the application, routing, data link and MAC layers to estimate the single-hop transmission delays along a multi-hop path that affect the end-to-end delay requirement. Experimental results verify the availability of the single-hop delay mode for end-to-end delay guarantees in CLA-DC, and prove that CLA-DC outperforms Simple-DC on meeting the end-to-end delay requirements by adopting cross-layer design approach, especially when the number of flows increases.
Description: Joint International Conference on Pervasive Computing and Web Society, ICPCA/SWS 2013, Vina del Mar, 5-7 December 2013
URI: http://hdl.handle.net/10397/75267
ISBN: 9783319092645
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-09265-2_53
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

4
Citations as of May 9, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.