scholarly journals An Efficient Resource Scheduling Strategy for V2X Microservice Deployment in Edge Servers

2020 ◽  
Vol 12 (10) ◽  
pp. 172
Author(s):  
Yanjun Shi ◽  
Yijia Guo ◽  
Lingling Lv ◽  
Keshuai Zhang
Keyword(s):  
Resource Utilization ◽  
Resource Scheduling ◽  
Mutation Process ◽  
Migration Strategy ◽  
Scheduling Strategy ◽  
Efficient Resource ◽  
Fast Development ◽  
Objective Model ◽  
Crossover And Mutation

The fast development of connected vehicles with support for various V2X (vehicle-to-everything) applications carries high demand for quality of edge services, which concerns microservice deployment and edge computing. We herein propose an efficient resource scheduling strategy to containerize microservice deployment for better performance. Firstly, we quantify three crucial factors (resource utilization, resource utilization balancing, and microservice dependencies) in resource scheduling. Then, we propose a multi-objective model to achieve equilibrium in these factors and a multiple fitness genetic algorithm (MFGA) for the balance between resource utilization, resource utilization balancing, and calling distance, where a container dynamic migration strategy in the crossover and mutation process of the algorithm is provided. The simulated results from Container-CloudSim showed the effectiveness of our MFGA.

Resource Scheduling Method Based on the Tenants' Requirements of QoS

2012 ◽  
Vol 546-547 ◽  
pp. 1158-1163
Author(s):  
Ting Wei Chen ◽  
Ji Hong Wu
Keyword(s):  
Quality Of Service ◽  
Resource Scheduling ◽  
Software As A Service ◽  
Shared Resources ◽  
Service Levels ◽  
Scheduling Strategy ◽  
Scheduling Method

Multi-tenancy technology in SaaS (Software as a Service), the basis of the shared resources on how to meet quality of service requirements of different tenants, is a major problem faced by the resource scheduling. Solve the problem, proposed a resource scheduling method based on the tenants' requirements of QoS: resources classified by types of resources QoS value of the keywords the two indexes to the formation of the three resource pool structure, in order to improve the speed of resource scheduling; division of tenants rating to determine the order of execution of the request, types of resources required, the division of tenants request for the sub-request, according to the sub-requested quality of service levels ,respectively, using different resource scheduling strategy, the isolation of different quality of service requirements of tenants. The experiments show that the method can achieve the tenants' quality of service requirements, and has a higher efficiency.

scholarly journals Design of a Fault Tolerant Strategy for Resource Scheduling in Cloud Environment

2019 ◽  
Vol 9 (1) ◽  
pp. 5121-5128
Keyword(s):  
Cloud Computing ◽  
Failure Rate ◽  
Virtual Machines ◽  
Fault Tolerant ◽  
Previous History ◽  
Resource Scheduling ◽  
Efficient Manner ◽  
Computing Power ◽  
Efficient Resource

Cloud computing supports the technological need of the industry supporting many other technologies. Also, the demand for computing power and storage by recent technologies is reasonably growing in a drastic way. Cloud computing, serving for these technologies are to be developed with advancements that lead to performance improvement both in support to the technologies like block-chain and big data. The allocation of cloud resources is an important strategy to be followed in a wiser manner to incorporate the needs of extra ordinary computing power. In this paper, an efficient resource allocation strategy (FTVMA) is introduced that involves the creation of effective virtual machines (VMs) and performs VM allocation in an efficient manner by considering the failure rates, previous history of failure of VM, execution efficiency as a part of effective scheduling. There exist many reasons for cloudlet failure in VMs. Some of them are overloading of VMs and non-availability of VMs. The introduced FTVMA algorithm considers the failure rate of the physical machine, load of virtual machines and the cost priority of the tasks in order to achieve Quality of Service (QoS) and Quality of Experience (QoE) of the user. The FTVMA methodology proposed in this paper works better for computation intensive VMs and is tested using CloudSim environment. The QoS metrics used to measure the performance of the proposed algorithm are Makespan and VM Utilization. The metric to measure QoE are Priority Miss Rate and Failure Rate. The proposed algorithm shows its improvement in terms of the QoS and QoE metrics. The results obtained are compared with the existing resource scheduling algorithms and it is inferred that the proposed algorithm performs better in terms of QoS and QoE.

scholarly journals The Efficient Resource Scheduling Strategy in Cloud: A Metaheuristic Approach

2021 ◽  
Vol 1099 (1) ◽  
pp. 012027
Author(s):  
Shilpa Maheshwari ◽  
Savita Shiwani ◽  
Surendra Singh Choudhary
Keyword(s):  
Resource Scheduling ◽  
Scheduling Strategy ◽  
Efficient Resource

Joint Access Control Based on Access Ratio and Resource Utilization for High-Speed Railway Communications

Frequenz ◽  
2015 ◽  
Vol 69 (5-6) ◽  
Author(s):  
Yuzhe Zhou ◽  
Bo Ai
Keyword(s):  
Quality Of Service ◽  
Access Control ◽  
Resource Utilization ◽  
High Speed ◽  
High Speed Railway ◽  
Broadband Wireless ◽  
Control Scheme ◽  
Fast Development ◽  
Optimal Resource

AbstractThe fast development of high-speed rails makes people’s life more and more convenient. However, provisioning of quality of service of multimedia applications for users on the high-speed train is a critical task for wireless communications. Therefore, new solutions are desirable to be found to address this kind of problem. Current researches mainly focus on providing seamless broadband wireless access for high-speed mobile terminals. In this paper, an algorithm to calculate the optimal resource reservation fraction of handovers is proposed. A joint access control scheme for high-speed railway communication handover scenario is proposed. Metrics of access ratio and resource utilization ratio are considered jointly in the analysis and the performance evaluation. Simulation results show that the proposed algorithm and the scheme improve quality of service compared with other conventional schemes.

Research on Scheduling Model in Dynamic Environment Based on Computational Economy

2015 ◽  
Vol 713-715 ◽  
pp. 1868-1871 ◽  
Author(s):  
Li Jun Duan
Keyword(s):  
Dynamic Behavior ◽  
Dynamic Environment ◽  
Resource Scheduling ◽  
Evaluation Function ◽  
Scheduling Strategy ◽  
Model Based ◽  
Scheduling Model ◽  
Two Factors ◽  
Efficient Resource

Efficient resource scheduling in dynamic environment reveals several challenges due to its high heterogeneity, dynamic behavior, and space shared utilization. In order to address this issue, a scheduling model based on computational economy was proposed in this paper. Firstly, the problem of resource scheduling was analyzed, and the essence of resource scheduling was concluded. Secondly, a scheduling strategy based on computational economy was presented. It applied the principles of economics and broker technology in its resource scheduling process. The strategy of the model synthetically considered two factors: execution cost and total complete time. An evaluation function driven by user’s needs was also built based on the two factors. Finally, the scheduling strategy was simulated. The result shows that the model can adjust the relation between price and time based on computational economy efficiently. It indicates that the model is an effective approach for resource scheduling.

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