An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

Abstract

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.KEYWORDS cloud, Fog, information security, Internet of Things, privacy, resource INTRODUCTIONThe Internet has provided a backbone for connecting different objects to each other and has changed human life significantly. The ubiquitous things is a new concept that has been created by the interconnection and intercommunication amongst smart objects. 1 We are faced with a huge volume of data in this environment. Network traffic, increasing demands of real time, latency-sensitive applications, resource-constraints (computational power, storage, memory, etc) in actuators, mobility and geo-distribution of smart objects, and heterogeneity that are new challenges in the domain of IoT. 2 These weaknesses directly or indirectly influence information security and privacy violation in IoT systems. 3Resource-constraint in actuators jeopardises secure communication between different smart objects. 4 Messages need to be sent encrypted;they will be decrypted for process in the target. The result of the process should be encrypted and send to the same object or other smart objects.We have latency; this delays not only creates risk for information security, but it may also impact human safety in some applications of IoT, such as smart vehicles. Lightweight cryptography has been presented to overcome this challenge in vehicle-to-vehicle (V2V) communication and in many other secure communications in IoT. 5 Smart objects usually do not have malware detection due to limitation in resources; their intrusion detection only can detect attacks in particular networks (not hybrid). These are examples of common problems in the IoT domain.Cloud...

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