Open AccessAdaptive dual prediction scheme based on sensing context similarity for wireless sensor networks
Author(s) -
Heo Taewook,
Kim Hyunhak,
Ko JeongGil,
Doh Yoonmee,
Park JongJun,
Jun Jongarm,
Choi Hoon
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.0165
Subject(s) - wireless sensor network , dual (grammatical number) , scheme (mathematics) , computer science , context (archaeology) , similarity (geometry) , wireless , artificial intelligence , electronic engineering , data mining , computer network , telecommunications , engineering , mathematics , geography , art , mathematical analysis , literature , archaeology , image (mathematics)
A novel adaptive dual‐prediction scheme is introduced for minimising the data communication load for wireless sensor networks as a way to maximise the lifetime of resource‐limited sensor nodes. Specifically, the proposed scheme exposes the fact that when sensing context prediction is used at both the sink node and the sensor nodes, the amount of data that need to be transmitted can be minimised. Furthermore, the transmission data quantity is reduced even more by exploiting the spatial correlation among different sensor nodes. On using this adaptive dual prediction scheme, the evaluations show that the amount of data transmissions can be compressed by as much as 20% against a basic dual prediction scheme, suggesting that the lifetime of sensor nodes can increase significantly in practical systems.