A set of simplified scheduling constraints for underwater acoustic MAC scheduling


Share/Save/Bookmark

Kleunen, Wouter van and Meratnia, Nirvana and Havinga, Paul J.M. (2010) A set of simplified scheduling constraints for underwater acoustic MAC scheduling. In: 3rd International Workshop on Underwater Networks, WUnderNet 2011, 22-25 March 2011, Singapore (pp. pp. 902-907).

[img] PDF
Restricted to UT campus only
: Request a copy
285kB
Abstract:Abstract—The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water have significant impacts on throughput, energy consumption, and reliability. Although the conflict scenarios and required scheduling constraints for deriving a collision-free schedule have been identified in the past,
applying them in a scheduling algorithm is by no means easy. In this paper, we derive a set of simplified scheduling constraints and propose two scheduling algorithms with relatively low complexity for both known and unknown orders of transmissions. Our experimental results show that scheduling without slots is on
average 22% better than scheduling with slots for large packet sizes, while for small packet sizes scheduling without slots is about 40% better. We also compare our ”smallest delay first” heuristic algorithm with the ”highest transmission load first” heuristic of ST-MAC [1] and show that our heuristic algorithm performs on average 13% better.
Item Type:Conference or Workshop Item
Additional information:This work is supported by the SeaSTAR project funded by the Dutch Technology Foundation (STW).
Copyright:© 2010 IEEE
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:http://purl.utwente.nl/publications/74783
Official URL:http://dx.doi.org/10.1109/WAINA.2011.25
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page

Metis ID: 277538