Verification and validation techniques for streaming big data analytics in internet of things environment

IET Networks ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 155-163 ◽  
Author(s):  
Aparna Kumari ◽  
Sudeep Tanwar ◽  
Sudhanshu Tyagi ◽  
Neeraj Kumar
Author(s):  
Sornalakshmi Krishnan ◽  
Kayalvizhi Jayavel

In this chapter, a discussion on the integration of distributed streaming Big Data Analytics with the Internet of Things is presented. The chapter begins with the introduction of these two technologies by discussing their features and characteristics. Discussion on how the integration of these two technologies benefit in efficient processing of IoT device generated sensor data follows next. Such data centric processing of IoT data powered by cloud, services and other enablers will be the architecture of most of the realtime systems involving sensors and real-time monitoring and actuation. The Volume, Variety and Velocity of sensor generated data make it a Big Data scenario. In addition, the data is real time and requires decisions or actuations immediately. This chapter discusses how IoT data can be processed using distributed, scalable stream processing systems. The chapter is concluded with future directions of such real time Big Data Analytics in IoT.


2022 ◽  
pp. 722-757
Author(s):  
Sornalakshmi Krishnan ◽  
Kayalvizhi Jayavel

In this chapter, a discussion on the integration of distributed streaming Big Data Analytics with the Internet of Things is presented. The chapter begins with the introduction of these two technologies by discussing their features and characteristics. Discussion on how the integration of these two technologies benefit in efficient processing of IoT device generated sensor data follows next. Such data centric processing of IoT data powered by cloud, services and other enablers will be the architecture of most of the realtime systems involving sensors and real-time monitoring and actuation. The Volume, Variety and Velocity of sensor generated data make it a Big Data scenario. In addition, the data is real time and requires decisions or actuations immediately. This chapter discusses how IoT data can be processed using distributed, scalable stream processing systems. The chapter is concluded with future directions of such real time Big Data Analytics in IoT.


Author(s):  
Zhihan Lv ◽  
Ranran Lou ◽  
Jinhua Li ◽  
Amit Kumar Singh ◽  
Houbing Song

2018 ◽  
Vol 1018 ◽  
pp. 012013 ◽  
Author(s):  
Waleed Noori Hussein ◽  
L.M. Kamarudin ◽  
Haider N. Hussain ◽  
A. Zakaria ◽  
R Badlishah Ahmed ◽  
...  

2021 ◽  
Vol 83 (4) ◽  
pp. 100-111
Author(s):  
Ahmad Anwar Zainuddin ◽  

Internet of Things (IoT) is an up-and-coming technology that has a wide variety of applications. It empowers physical objects to be organized in a specialized framework to grow its convenience in terms of ease and time utilization. It is to convert the thought of bridging the crevice between the physical world and the machine world. It is also being use in the wide range of the technology in this current situation. One of its applications is to monitor and store data over time from numerous devices allows for easy analysis of the dataset. This analysis can then be the basis of decisions made on the same. In this study, the concept, architecture, and relationship of IoT and Big Data are described. Next, several use cases in IoT and big data in the research methodology are studied. The opportunities and open challenges which including the future directions are described. Furthermore, by proposing a new architecture for big data analytics in the Internet of Things, this paper adds value. Overall, the various types of big IoT data analytics, their methods, and associated big data mining technologies are discussed.


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