An Efficient Renewable Energy-Based Scheduling Algorithm for Cloud Computing

2020 ◽  
pp. 81-97
Author(s):  
Sanjib Kumar Nayak ◽  
Sanjaya Kumar Panda ◽  
Satyabrata Das ◽  
Sohan Kumar Pande
Keyword(s):  
Cloud Computing ◽  
Renewable Energy ◽  
Scheduling Algorithm

AN EXTENDED MIN-MIN SCHEDULING ALGORITHM IN CLOUD COMPUTING

2018 ◽  
Vol 5 (2) ◽  
pp. 20
Author(s):  
MAIPAN-UKU J. Y. ◽  
MISHRA A. ◽  
A. ABDULGANIYU ◽  
ABDULKADIR A. ◽  
◽  
...  
Keyword(s):  
Cloud Computing ◽  
Scheduling Algorithm

Load Balancing Scheduling Algorithm in Cloud Computing System with Cloud Pricing Comparative Study

2017 ◽  
Vol 26 (1) ◽  
pp. 129-152 ◽  
Author(s):  
Elhossiny Ibrahim ◽  
Nirmeen A. El-Bahnasawy ◽  
Fatma A. Omara
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Comparative Study ◽  
Scheduling Algorithm ◽  
Computing System ◽  
Cloud Computing System

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

scholarly journals On the Design of Efficient Hierarchic Architecture for Software Defined Vehicular Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1400
Author(s):  
Muhammad Adnan ◽  
Jawaid Iqbal ◽  
Abdul Waheed ◽  
Noor Ul Amin ◽  
Mahdi Zareei ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Traffic Management ◽  
Vehicular Networks ◽  
Scheduling Algorithm ◽  
Main Research ◽  
First Come First Serve ◽  
Computing Framework ◽  
Simulation Results

Modern vehicles are equipped with various sensors, onboard units, and devices such as Application Unit (AU) that support routing and communication. In VANETs, traffic management and Quality of Service (QoS) are the main research dimensions to be considered while designing VANETs architectures. To cope with the issues of QoS faced by the VANETs, we design an efficient SDN-based architecture where we focus on the QoS of VANETs. In this paper, QoS is achieved by a priority-based scheduling algorithm in which we prioritize traffic flow messages in the safety queue and non-safety queue. In the safety queue, the messages are prioritized based on deadline and size using the New Deadline and Size of data method (NDS) with constrained location and deadline. In contrast, the non-safety queue is prioritized based on First Come First Serve (FCFS) method. For the simulation of our proposed scheduling algorithm, we use a well-known cloud computing framework CloudSim toolkit. The simulation results of safety messages show better performance than non-safety messages in terms of execution time.

scholarly journals Minimizing Energy Consumption Scheduling Algorithm of Workflows With Cost Budget Constraint on Heterogeneous Cloud Computing Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 205099-205110
Author(s):  
Longxin Zhang ◽  
Lan Wang ◽  
Zhicheng Wen ◽  
Mansheng Xiao ◽  
Junfeng Man
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Scheduling Algorithm ◽  
Budget Constraint ◽  
Computing Systems ◽  
Heterogeneous Cloud
Sign in / Sign up

Export Citation Format

Share Document