Visible to the public A security aware scheduling in fog computing by hyper heuristic algorithm

TitleA security aware scheduling in fog computing by hyper heuristic algorithm
Publication TypeConference Paper
Year of Publication2017
AuthorsRahbari, D., Kabirzadeh, S., Nickray, M.
Conference Name2017 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS)
Keywordsauthentication parameter, authorisation, average energy consumption, cloud computing, computational overhead, confidentiality parameter, CPU utilization, data integrity, data mining, data mining technique, edge computing, Fog Computing, fog devices, heterogeneous distributed environment, heuristic algorithm, Heuristic algorithms, hyper heuristic algorithm, integrity parameter, Internet of Things, job scheduling, latency, Processor scheduling, pubcrawl, Resiliency, resource allocation, Scalability, scheduling, security, security aware scheduling, Security Heuristics, security of data, security overhead, sensor nodes, Task Analysis
Abstract

Fog computing provides a new architecture for the implementation of the Internet of Things (IoT), which can connect sensor nodes to the cloud using the edge of the network. This structure has improved the latency and energy consumption in the cloud. In this heterogeneous and distributed environment, resource allocation is very important. Hence, scheduling will be a challenge to increase productivity and allocate resources appropriately to the tasks. Programs that run in this environment should be protected from intruders. We consider three parameters as authentication, integrity, and confidentiality to maintain security in fog devices. These parameters have time and computational overhead. In the proposed approach, we schedule the modules for the run in fog devices by heuristic algorithms based on data mining technique. The objective function is included CPU utilization, bandwidth, and security overhead. We compare the proposed algorithm with several heuristic algorithms. The results show that our proposed algorithm improved the average energy consumption of 63.27%, cost 44.71% relative to the PSO, ACO, SA algorithms.

URLhttps://ieeexplore.ieee.org/document/8311595
DOI10.1109/ICSPIS.2017.8311595
Citation Keyrahbari_security_2017