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| Title | Ai And Blockchain Assisted Framework For Offloading And Resource Allocation In Fog Computing |
|---|---|
| ID_Doc | 6891 |
| Authors | Aknan M.; Singh M.P.; Arya R. |
| Year | 2023 |
| Published | Journal of Grid Computing, 21, 4 |
| DOI | http://dx.doi.org/10.1007/s10723-023-09694-7 |
| Abstract | The role of Internet of Things (IoT) applications has increased tremendously in several areas like healthcare, agriculture, academia, industries, transportation, smart cities, etc. to make human life better. The number of IoT devices is increasing exponentially, and generating huge amounts of data that IoT nodes cannot handle. The centralized cloud architecture can process this enormous IoT data but fails to offer quality of service (QoS) due to high transmission latency, network congestion, and bandwidth. The fog paradigm has evolved that bring computing resources at the network edge for offering services to latency-sensitive IoT applications. Still, offloading decision, heterogeneous fog network, diverse workload, security issues, energy consumption, and expected QoS is significant challenges in this area. Hence, we have proposed a Blockchain-enabled Intelligent framework to tackle the mentioned issues and allocate the optimal resources for upcoming IoT requests in a collaborative cloud fog environment. The proposed framework is integrated with an Artificial Intelligence (AI) based meta-heuristic algorithm that has a high convergence rate, and the capability to take the offloading decision at run time, leading to improved results quality. Blockchain technology secures IoT applications and their data from modern attacks. The experimental results of the proposed framework exhibit significant improvement by up to 20% in execution time and cost and up to 18% in energy consumption over other meta-heuristic approaches under similar experimental environments. © 2023, The Author(s), under exclusive licence to Springer Nature B.V. |
| Author Keywords | BAT algorithm; Cloud computing; Fog computing; Internet of Things; Offloading decision |
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