توضیحات
Abstract
This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection
and wireless communication in Internet of Things (IoT). Wireless sensor networks (WSNs) are the main components of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address
many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper
reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute
their sensing data. Furthermore, we consider the use of some pricing models in machine-to-machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT
INTRODUCTION
to operate and transmit data to other systems without or with minimal human intervention [1]. The development of IoT has brought a great influence to many areas, and there have been many IoT applications implemented to improve the system performance as well as the quality of life such as healthcare, transportation, manufacturing, and so on [2]. Surveys of technologies and applications of IoT were presented in [3]–[6].In IoT systems, a wireless sensor networks (WSNs) is one of the most important components mainly used to collect
data from the environment and transfer such data to the central controllers for further processing. However, different from conventional wireless sensor networks, sensors in IoT are required to be “smarter” [1]. In particular, sensors in IoT can not only perform normal functions, e.g., sensing information from the surrounding environment, but also make optimal decisions without or with minimal human intervention given their constrained resources and the dynamic of the environment for the requested IoT services. In addition, with billion of devices connecting to the Internet, it leads to many challenges in efficiently controlling and managing IoT’s sensors. Consequently, new approaches with higher efficiency and more flexibility to adapt to dynamic IoT networks need to be developed
Year:2016
By:Nguyen Cong Luong, Dinh Thai Hoang, Ping Wang, Dusit Niyato,Dong In Kim, and Zhu Han
File Information:English Language/45 Page/Size :4.4M
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سال :2016
کاری از :Nguyen Cong Luong, Dinh Thai Hoang, Ping Wang, Dusit Niyato,Dong In Kim, and Zhu Han
اطلاعات فایل :زبان انگلیسی /45 صفحه/حجم:4.4M
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