Energy efficient optimal parent selection based routing protocol for Internet of Things using firefly optimization algorithm

2020 ◽  
Author(s):  
Sankar Sennan ◽  
Ramasubbareddy Somula ◽  
Ashish K. Luhach ◽  
Ganesh Gopal Deverajan ◽  
Waleed Alnumay ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Routing Protocol ◽  
Optimization Algorithm ◽  
Energy Efficient ◽  
Parent Selection ◽  
Firefly Optimization ◽  
Firefly Optimization Algorithm

FA-Based Optimal Strategy of Train’s Energy Saving with Energy Materials

2012 ◽  
Vol 485 ◽  
pp. 93-96 ◽  
Author(s):  
Hui Hu
Keyword(s):  
Mathematical Model ◽  
Energy Saving ◽  
Optimization Algorithm ◽  
Optimal Strategy ◽  
Energy Efficient ◽  
Energy Materials ◽  
Ga Algorithm ◽  
Firefly Optimization ◽  
Simulation Results ◽  
Firefly Optimization Algorithm

According to one energy-efficient mathematical model which usually uses GA algorithm to solve, a new algorithm based on firefly optimization algorithm is applied to solve it. Through calculation for a cited example, simulation results such as speed-position curve are got. Compared with other methods, it demonstrates this new FA-based algorithm has a better performance and can be considered to be put into practical use.

scholarly journals Energy Efficient Composite Metric Based Routing Protocol for Internet of Things

2020 ◽  
Vol 26 (11) ◽  
pp. 1366-1381
Author(s):  
Sathishkumar Natesan ◽  
Rajakumar Krishnan
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Link Quality ◽  
Traffic Load ◽  
Delivery Ratio ◽  
Lossy Networks ◽  
Hop Count ◽  
Battery Discharge

The Routing Protocol for Low Power and Lossy Networks (RPL) is operated by gadgets comprised of many devices of embedded type with limited energy, memory as well as resources that do their process. The improvements in the life of the network and energy conservation are the key challenging features in Low Power and Lossy Networks (LLN). Obviously, the LLN has a key strategic part in routing. The Internet of Things (IoT) device is expected to make the apt choice. In LLN, the poor routing choice leads to traffic congestion, reduction in power as well as packet loss ratio. The task in the proposal analyzes Delay (D), Load (L) and Battery Discharge Index (BDI) pivoted Energy Efficient Composite Metric Routing (EECMR) protocol for LLN. The performance of the work in the proposal is evaluated by the COOJA simulator. It outperforms with respect to Network Lifetime (NL), Delay as well as Packet Delivery Ratio (PDR) contrasted to the routing metrics like Traffic Load (TL), Link Quality (LQ), Residual Energy (RE), RE-Battery Discharge Index (RE-BDI) and Hop Count (HC).

Evaluation of the trust values among human resources in the enterprise cloud using an optimization algorithm and fuzzy logic

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lantian Li ◽  
Bahareh Pahlevanzadeh
Keyword(s):  
Optimization Algorithm ◽  
Heuristic Algorithms ◽  
Human Life ◽  
Cloud Services ◽  
Cloud Provider ◽  
Suggested Approach ◽  
Content Type ◽  
Firefly Optimization ◽  
Security Costs ◽  
Firefly Optimization Algorithm

PurposeCloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.Design/methodology/approachCloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.FindingsThe fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.Practical implicationsThe findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.Originality/valueUsing a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

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