Cuckoo Optimization Algorithm Based Job Scheduling Using Cloud and Fog Computing in Smart Grid

2018 ◽  
pp. 34-46 ◽  
Author(s):  
Saqib Nazir ◽  
Sundas Shafiq ◽  
Zafar Iqbal ◽  
Muhammad Zeeshan ◽  
Subhan Tariq ◽  
...  
Keyword(s):  
Smart Grid ◽  
Optimization Algorithm ◽  
Job Scheduling ◽  
Fog Computing ◽  
Cuckoo Optimization Algorithm

scholarly journals IoT Workflow Scheduling Using Intelligent Arithmetic Optimization Algorithm in Fog Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Mohamed Abd Elaziz ◽  
Laith Abualigah ◽  
Rehab Ali Ibrahim ◽  
Ibrahim Attiya
Keyword(s):  
Task Scheduling ◽  
Optimization Algorithm ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Fog Computing ◽  
Local Optimum ◽  
Energy Aware ◽  
Marine Predators ◽  
Computational Overhead ◽  
Iot Devices

Instead of the cloud, the Internet of things (IoT) activities are offloaded into fog computing to boost the quality of services (QoSs) needed by many applications. However, the availability of continuous computing resources on fog computing servers is one of the restrictions for IoT applications since transmitting the large amount of data generated using IoT devices would create network traffic and cause an increase in computational overhead. Therefore, task scheduling is the main problem that needs to be solved efficiently. This study proposes an energy-aware model using an enhanced arithmetic optimization algorithm (AOA) method called AOAM, which addresses fog computing’s job scheduling problem to maximize users’ QoSs by maximizing the makespan measure. In the proposed AOAM, we enhanced the conventional AOA searchability using the marine predators algorithm (MPA) search operators to address the diversity of the used solutions and local optimum problems. The proposed AOAM is validated using several parameters, including various clients, data centers, hosts, virtual machines, tasks, and standard evaluation measures, including the energy and makespan. The obtained results are compared with other state-of-the-art methods; it showed that AOAM is promising and solved task scheduling effectively compared with the other comparative methods.

scholarly journals Digital Certificate Verification Scheme for Smart Grid using Fog Computing (FONICA)

2021 ◽  
Vol 13 (5) ◽  
pp. 2549
Author(s):  
Shahid Mahmood ◽  
Moneeb Gohar ◽  
Jin-Ghoo Choi ◽  
Seok-Joo Koh ◽  
Hani Alquhayz ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Efficient ◽  
Fog Computing ◽  
Security Threats ◽  
Certification Authority ◽  
Certificate Revocation ◽  
Grid Networks ◽  
Digital Certificates ◽  
Attack Surface ◽  
Energy Network

Smart Grid (SG) infrastructure is an energy network connected with computer networks for communication over the internet and intranets. The revolution of SGs has also introduced new avenues of security threats. Although Digital Certificates provide countermeasures, however, one of the issues that exist, is how to efficiently distribute certificate revocation information among Edge devices. The conventional mechanisms, including certificate revocation list (CRL) and online certificate status protocol (OCSP), are subjected to some limitations in energy efficient environments like SG infrastructure. To address the aforementioned challenges, this paper proposes a scheme incorporating the advantages and strengths of the fog computing. The fog node can be used for this purpose with much better resources closer to the edge. Keeping the resources closer to the edge strengthen the security aspect of smart grid networks. Similarly, a fog node can act as an intermediate Certification Authority (CA) (i.e., Fog Node as an Intermediate Certification Authority (FONICA)). Further, the proposed scheme has reduced storage, communication, processing overhead, and latency for certificate verification at edge devices. Furthermore, the proposed scheme reduces the attack surface, even if the attacker becomes a part of the network.

scholarly journals A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid

Energies ◽  
2017 ◽  
Vol 10 (3) ◽  
pp. 319 ◽  
Author(s):  
Nadeem Javaid ◽  
Sakeena Javaid ◽  
Wadood Abdul ◽  
Imran Ahmed ◽  
Ahmad Almogren ◽  
...  
Keyword(s):  
Smart Grid ◽  
Optimization Algorithm ◽  
Demand Side Management ◽  
Heuristic Optimization ◽  
Demand Side

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

2021 ◽  
pp. 0734242X2110039
Author(s):  
Elham Shadkam
Keyword(s):  
Waste Management ◽  
Network Design ◽  
Optimization Algorithm ◽  
Reverse Logistics ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Fixed Costs ◽  
Logistics System ◽  
Cuckoo Optimization Algorithm ◽  
Proposed Model

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

Visualization Service Model for Job Scheduling

2011 ◽  
Vol 282-283 ◽  
pp. 683-686
Author(s):  
Yong Ling Yu ◽  
Tao Guan ◽  
Jin Fa Shi
Keyword(s):  
Enterprise Resource Planning ◽  
Optimization Algorithm ◽  
Optimization Model ◽  
Job Scheduling ◽  
Resource Planning ◽  
Information Services ◽  
Production Data ◽  
Service Model ◽  
New Approach ◽  
Manufacturing Information

With the expansion of manufacturing information services, visualization service in enterprise resource planning has recently become a hot topic. In this paper, we propose a new approach for job scheduling visualization service and a model of visualization service constructed from the share of production data and job scheduling information. Moreover, the optimization model of visualization service is given. At last, we discuss the optimization algorithm for this model.

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