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Multiple layer design for mass data transmission against channel congestion in IoT
Author(s) -
Liu Yang,
Chen Zhikui,
Lv Xiaoning,
Han Feng
Publication year - 2014
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.2399
Subject(s) - computer science , computer network , application layer , data transmission , cloud computing , distributed computing , channel (broadcasting) , data sharing , medicine , alternative medicine , pathology , software deployment , operating system
SUMMARY Internet of Things (IoT) is well studied from many aspects; however, data transmission in a large‐scale constructed IoT network is still an open topic. In this paper, the problems of channel congestion caused by mass data transmission are discussed respectively from different perspectives. Then, a multiple layer solution is proposed, pointing to each layer including data processing architecture, data dimension reduction, data abandon protocol, and spectrum sharing. In the architecture layer, a combined scheme with cloud computing and sea computing is introduced. Context awareness and granular computing is exploited to implement the data dimension reduction. And cognitive protocol is involved with type of service, which drops certain data to guarantee the entire network connectivity. Then, a principal–agent theory based two‐step game model is proposed with the consideration of cooperation and price coefficient, which affect the secondary user's choice and primary user's profit. Some incomplete information is assumed as random variables so that certainty equivalent is introduced in the model. A simple scenario shows how the data dimension reduction works and how simulations for data abandon protocol and spectrum sharing test the two parts, respectively. Copyright © 2012 John Wiley & Sons, Ltd.