TY - GEN
T1 - Suppressing redundancy in wireless sensor network traffic
AU - Abe, Rey
AU - Honiden, Shinichi
PY - 2010/8/13
Y1 - 2010/8/13
N2 - Redundancy suppression is a network traffic compression technique that, by caching recurring transmission contents at receiving nodes, avoids repeatedly sending duplicate data. Existing implementations require abundant memory both to analyze recent traffic for redundancy and to maintain the cache. Wireless sensor nodes at the same time cannot provide such resources due to hardware constraints. The diversity of protocols and traffic patterns in sensor networks furthermore makes the frequencies and proportions of redundancy in traffic unpredictable. The common practice of narrowing down search parameters based on characteristics of representative packet traces when dissecting data for redundancy thus becomes inappropriate. Such difficulties made us devise a novel protocol that conducts a probabilistic traffic analysis to identify and cache only the subset of redundant transfers that yields most traffic savings. We verified this approach to perform close enough to a solution built on exhaustive analysis and unconstrained caching to be practicable.
AB - Redundancy suppression is a network traffic compression technique that, by caching recurring transmission contents at receiving nodes, avoids repeatedly sending duplicate data. Existing implementations require abundant memory both to analyze recent traffic for redundancy and to maintain the cache. Wireless sensor nodes at the same time cannot provide such resources due to hardware constraints. The diversity of protocols and traffic patterns in sensor networks furthermore makes the frequencies and proportions of redundancy in traffic unpredictable. The common practice of narrowing down search parameters based on characteristics of representative packet traces when dissecting data for redundancy thus becomes inappropriate. Such difficulties made us devise a novel protocol that conducts a probabilistic traffic analysis to identify and cache only the subset of redundant transfers that yields most traffic savings. We verified this approach to perform close enough to a solution built on exhaustive analysis and unconstrained caching to be practicable.
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U2 - 10.1007/978-3-642-13651-1_14
DO - 10.1007/978-3-642-13651-1_14
M3 - Conference contribution
AN - SCOPUS:77955410181
SN - 3642136508
SN - 9783642136504
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 187
EP - 200
BT - Distributed Computing in Sensor Systems - 6th IEEE International Conference, DCOSS 2010, Proceedings
T2 - 6th IEEE International Conference on Distributed Computing in Sensor Systems, DCOSS 2010
Y2 - 21 June 2010 through 23 June 2010
ER -