What is it about?

Experts believe that the Internet of Things (IoT) is a new revolution in technology and has brought many advantages for our society. However, there are serious challenges in terms of information security and privacy protection. Smart objects usually do not have malware detection due to resource limitations and their intrusion detection work on a particular network. Low computation power, low bandwidth, low battery, storage, and memory contribute to a resource‐constrained effect on information security and privacy protection in the domain of IoT. The capacity of fog and cloud computing such as efficient computing, data access, network and storage, supporting mobility, location awareness, heterogeneity, scalability, and low latency in secure communication positively influence information security and privacy protection in IoT. This study illustrates the positive effect of fog and cloud computing on the security of IoT systems and presents a decision‐making model based on the object's characteristics such as computational power, storage, memory, energy consumption, bandwidth, packet delivery, hop‐count, etc. This helps an IoT system choose the best nodes for creating the fog that we need in the IoT system. Our experiment shows that the proposed approach has less computational, communicational cost, and more productivity in compare with the situation that we choose the smart objects randomly to create a fog.

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Why is it important?

The presented model and approach is a novel solution to overcome resource constraint in IoT domain.


A real and clear problem statement is important part of a research. Resource constraint has presented as a problem in smart objects in many studies. We have presented a novel approach (fog and cloud computing) to overcome this challenge.

Dr Nader Sohrabi Safa
University of Wolverhampton

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This page is a summary of: An opportunistic resource management model to overcome resource-constraint in the Internet of Things, Concurrency and Computation Practice and Experience, September 2018, Wiley, DOI: 10.1002/cpe.5014.
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