scholarly journals Makespan Optimisation in Cloudlet Scheduling with Improved DQN Algorithm in Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amine Chraibi ◽  
Said Ben Alla ◽  
Abdellah Ezzati
Keyword(s):  
Execution Time ◽  
Work Performance ◽  
Virtual Machines ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Cloud Infrastructure ◽  
Reward Function ◽  
Cloud Service Providers ◽  
Cloudlet Scheduling

Despite increased cloud service providers following advanced cloud infrastructure management, substantial execution time is lost due to minimal server usage. Given the importance of reducing total execution time (makespan) for cloud service providers (as a vital metric) during sustaining Quality-of-Service (QoS), this study established an enhanced scheduling algorithm for minimal cloudlet scheduling (CS) makespan with the deep Q-network (DQN) algorithm under MCS-DQN. A novel reward function was recommended to enhance the DQN model convergence. Additionally, an open-source simulator (CloudSim) was employed to assess the suggested work performance. Resultantly, the recommended MCS-DQN scheduler revealed optimal outcomes to minimise the makespan metric and other counterparts (task waiting period, resource usage of virtual machines, and the extent of incongruence against the algorithms).

scholarly journals Allocation of Cloudlets using Solution of Job Assignment Problem

2019 ◽  
Vol 8 (9S4) ◽  
pp. 20-25
Keyword(s):  
Cloud Computing ◽  
Execution Time ◽  
Assignment Problem ◽  
Virtual Machines ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Job Assignment ◽  
Total Execution Time ◽  
First Come First Serve

Resource allocation policies play a key role in determining the performance of cloud. Service providers in cloud computing have to provide services to many users simultaneously. So the job of allocating cloudlets to appropriate virtual machines is becoming one of the challenging issues of cloud computing. Many algorithms have been proposed to allocate cloudlets to the virtual machines. Here in our paper, we have represented cloudlet allocation problem as job assignment problem and we have proposed Hungarian algorithm based solution for allocating cloudlets to virtual machines. The main objective is to minimize total execution time of cloudlets. Proposed algorithm is implemented in Cloudsim-3.03 simulator. We have done comparative analysis of the simulation results of proposed algorithm with the existing First Come First Serve (FCFS) scheduling policy and Min-Min scheduling algorithm. Proposed algorithm performs better than the above mentioned algorithms in terms of total execution time and makespan time (finishing time of last cloudlet)

scholarly journals AUTO-SCALING AND ADJUSTMENT PLATFORM FOR CLOUD-BASED SYSTEMS

2017 ◽  
Vol 2 ◽  
pp. 52 ◽  
Author(s):  
Jānis Kampars ◽  
Krišjānis Pinka
Keyword(s):  
Real Time ◽  
Performance Metrics ◽  
Virtual Machines ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Infrastructure ◽  
Time Data ◽  
Cloud Service Providers ◽  
Auto Scaling

For customers of cloud-computing platforms it is important to minimize the infrastructure footprint and associated costs while providing required levels of Quality of Service (QoS) and Quality of Experience (QoE) dictated by the Service Level Agreement (SLA). To assist with that cloud service providers are offering: (1) horizontal resource scaling through provisioning and destruction of virtual machines and containers, (2) vertical scaling through changing the capacity of individual cloud nodes. Existing scaling solutions mostly concentrate on low-level metrics like CPU load and memory consumption which doesn’t always correlate with the level of SLA conformity. Such technical measures should be preprocessed and viewed from a higher level of abstraction. Application level metrics should also be considered when deciding upon scaling the cloud-based solution. Existing scaling platforms are mostly proprietary technologies owned by cloud service providers themselves or by third parties and offered as Software as a Service. Enterprise applications could span infrastructures of multiple public and private clouds, dictating that the auto-scaling solution should not be isolated inside a single cloud infrastructure. The goal of this paper is to address the challenges above by presenting the architecture of Auto-scaling and Adjustment Platform for Cloud-based Systems (ASAPCS). It is based on open-source technologies and supports integration of various low and high level performance metrics, providing higher levels of abstraction for design of scaling algorithms. ASAPCS can be used with any cloud service provider and guarantees that move from one cloud platform to another will not result in complete redesign of the scaling algorithm. ASAPCS itself is horizontally scalable and can process large amounts of real-time data which is particularly important for applications developed following the microservices architectural style. ASAPCS approaches the scaling problem in a nonstandard way by considering real-time adjustments of the application logic to be part of the scalability strategy if it can result in performance improvements.

scholarly journals АНАЛИЗ ПОДХОДОВ К ОБЕСПЕЧЕНИЮ БЕЗОПАСНОСТИ ОБЛАЧНЫХ СЕРВИСОВ

2020 ◽  
pp. 70-82
Author(s):  
Вячеслав Вікторович Фролов
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Geographical Location ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Infrastructure ◽  
Critical System ◽  
Cloud Service Providers ◽  
Safety And Reliability ◽  
Cloud Resources

The article is devoted to the analysis of modern approaches that ensure the security of cloud services. Since cloud computing is one of the fastest growing areas among information technology, it is extremely important to ensure the safety and reliability of processes occurring in the clouds and to secure the interaction between the client and the provider of cloud services. Given that fears about data loss and their compromise are one of the main reasons that some companies do not transfer their calculations to the clouds. The object of research and analysis of this work are cloud services, which are provided by various cloud service providers. The aim of the study of this work is to compare existing approaches that provide information security for cloud services, as well as offer a new approach based on the principle of diversity. There are many approaches that ensure their safety, using both traditional and cloud-specific. The multi-cloud approach is one of the most promising strategies for improving reliability by reserving cloud resources on the servers of various cloud service providers. It is shown that it is necessary to use diversity to ensure the reliability and safety of critical system components. The principle of diversity is to use a unique version of each resource thanks to a special combination of a cloud computing provider, the geographical location of data centers, cloud service presentation models, and cloud infrastructure deployment models. The differences between cloud providers and which combination of services are preferable to others in terms of productivity are discussed in detail. In addition, best practices for securing cloud resources are reviewed. As a result, this paper concludes that there is a problem of insufficient security and reliability of cloud computing and how to reduce threats in order to avoid a common cause failure and, as a result, loss of confidential data or system downtime using diversity of cloud services.

scholarly journals Selection of optimal data placement using cloud infrastructure

2021 ◽  
pp. 34-42
Author(s):  
Vladimir Meikshan ◽  
◽  
Natalia Teslya ◽  
Keyword(s):  
Mathematical Model ◽  
Data Storage ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Information Storage ◽  
Cloud Infrastructure ◽  
Digital Ecosystem ◽  
Cloud Service Providers ◽  
The Cost

Benefits of using cloud technology are obvious, their application is expanding, as a result, it determines the steady growth of demand. Cloud computing has acquired particular relevance for large companies connected with Internet services, retailing, logistics that generate large volume of business and other information. The use of cloud technologies allows organizing the joint consumption of resources, solving the problems of storing and transferring significant amounts of data. Russian consumer cooperation refers to large territory distributed organizations actively forming their own digital ecosystem. The issue of data storing and processing for consumer coo-peration organizations is very relevant. At the same time, the prices of cloud service providers are significantly different and require solving the problem of minimizing the cost of storing and transferring significant amounts of data. The application of the linear programming method is considered to select the optimal data storage scheme for several cloud service providers having different technical and economic parameters of the package (maximum amount of storage, cost of allocated resources). Mathematical model includes the equation of costs for data storing and transferring and restrictions on the amount of storage, the amount of data and its safety. Software tool that allows to perform numerical calculations is selected Microsoft Excel in combination with the "search for solutions" add-on. In accordance with the mathematical model, the conditions for minimizing the amount of cloud storage costs and the necessary restrictions are established. Initial data are set for three data forming centers, storages of certain size for five cloud service providers and nominal price for information storage and transmission. Calculations of expenses are performed in several variants: without optimization, with the solution of the optimization problem, with price increase by cloud service providers. Results of the calculations confirm the necessity to solve the problem of minimizing the cost of cloud services for corporate clients. The presented model can be expanded for any cost conditions as well as for different areas of cloud applications.

A New Conception of Load Balancing in Cloud Computing Using Tasks Classification Levels

2018 ◽  
Vol 8 (4) ◽  
pp. 118-133 ◽  
Author(s):  
Fahim Youssef ◽  
Ben Lahmar El Habib ◽  
Rahhali Hamza ◽  
Labriji El Houssine ◽  
Eddaoui Ahmed ◽  
...  
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Execution Time ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Providers ◽  
Cloud Service ◽  
Mathematical Functions ◽  
Worst Case ◽  
Cloud Users

Cloud users can have access to the service based on “pay as you go.” The daily increase of cloud users may decrease the performance, the availability and the profitability of the material and software resources used in cloud service. These challenges were solved by several load balancing algorithms between the virtual machines of the data centers. In order to determine a new load balancing improvement; this article's discussions will be divided into two research axes. The first, the pre-classification of tasks depending on whether their characteristics are accomplished or not (Notion of Levels). This new technique relies on the modeling of tasks classification based on an ascending order using techniques that calculate the worst-case execution time (WCET). The second, the authors choose distributed datacenters between quasi-similar virtual machines and the modeling of relationship between virtual machines using the pre-scheduling levels is included in the data center in terms of standard mathematical functions that controls this relationship. The key point of the improvement, is considering the current load of the virtual machine of a data center and the pre-estimation of the execution time of a task before any allocation. This contribution allows cloud service providers to improve the performance, availability and maximize the use of virtual machines workload in their data centers.

scholarly journals Hybrid task scheduling algorithm for high availability in cloud

2018 ◽  
Vol 7 (2.8) ◽  
pp. 455
Author(s):  
Snehaa K ◽  
Sivasankari S
Keyword(s):  
Service Providers ◽  
Learning Algorithm ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
High Availability ◽  
The Other ◽  
Machine Learning Algorithm ◽  
Task Scheduling Algorithm ◽  
Cloud Service Providers ◽  
Load Balancer

Today, wherever we go we will find one thing or the other that is running in cloud. It has become an essential component in our everyday life. Many cloud service providers have been extensively working on improving the performance of the service provided. Highavailability in cloud is a place where various cloud service providers are extensively researching. High availability in cloud can vary depending on the scenario it is considered under. In our case we are going to see this in the form of response time for the request to get processed and how we can improve it. We are proposing an algorithm which will ensure the above and also provide an efficient model for analysing the same. We will also be configuring Reinforcement machine learning algorithm for training the load balancer and the server to process the request faster in a short duration of time.

scholarly journals A Novel Cryptosystem for Files Stored in Cloud using NTRU Encryption Algorithm

2020 ◽  
Vol 9 (1) ◽  
pp. 2127-2130
Keyword(s):  
Service Provider ◽  
Service Providers ◽  
Computational Cost ◽  
Cloud Service ◽  
Encryption Algorithm ◽  
Advanced Encryption Standard ◽  
Cloud Infrastructure ◽  
Computationally Efficient ◽  
Cloud Service Provider ◽  
Cloud Service Providers

The cloud refers to a set of services and infrastructure that are accessed via the internet. the cloud infrastructure is shared by many users each one performing different tasks. in order to prevent data leakage in the cloud the Cloud Service Provider should employ an Encryption Algorithm to protect the data of the users. Since the cloud service providers and large amount of data the Encryption Algorithm should be very efficient in terms of computational cost and time. Current Cloud service providers you son of the following algorithms to encrypt and decrypt the data Advanced encryption standard(AES), Rivest–Shamir–Adleman (RSA) and elliptic curve cryptography(ECC).The encryption for cloud should be chosen such that it is computationally efficient for the Cloud Service Provider and also meets the security requirement of the user

scholarly journals An Efficient Resource Scheduling Framework for Infrastructure Performance Enhancement in Cloud Environment

2019 ◽  
Vol 8 (4) ◽  
pp. 7283-7287
Keyword(s):  
Performance Enhancement ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Infrastructure ◽  
Cloud Service Providers ◽  
Efficient Resource ◽  
Infrastructure Performance ◽  
Cloud Users ◽  
Level Performance

On-demand cloud services must be provided to customers at any time by ways of cloud service providers due to cloud demand. It is obligatory for cloud service providers to lessen large volumes of data, thereby it can reduce costs for maintaining large storage systems.Infrastructure level performance is an important problem which directly affects the overall working of cloud computing environment. The objective of our framework is enhancing the performance of cloud infrastructure. Proposed approach demonstrates high effective in cloud performance enhancement, as it displays enhancement in both the service providers as well as for cloud users.

scholarly journals User Behavior and Trust Evaluation in Cloud Computing

10.29007/q5bd ◽  
2019 ◽  
Author(s):  
Maryam Alruwaythi ◽  
Krishna Kambhampaty ◽  
Kendall E. Nygard
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
User Behavior ◽  
User Authentication ◽  
Critical Role ◽  
Cloud Service ◽  
Cloud Infrastructure ◽  
Resource Needs ◽  
Cloud Service Providers ◽  
Trust Models

Cloud computing helps organizations to dynamically increase the resource needs as and when needed, without the need to purchase them. Security is a basic concern in cloud computing, and threats can occur both internally and externally. Users can access the cloud infrastructure for software, operating system and network infrastructure provided by the Cloud Service Providers (CSP). Evaluating the user behavior in the cloud computing infrastructure is becoming more and more important for both Cloud Users (CSs) as well as Cloud Service Providers The CSPs must ensure the safety of users accessing the cloud. Since user authentication alone is not enough to ensure the safety of users, user behavior trust plays a critical role in ensuring the authenticity of the user as well as safety. In this paper, we present the importance of user behavior in modeling trust, associated evaluation principles and comparison between different trust models.

scholarly journals Micro Service Based System for Cost Based Selection of Cloud Provider Services

2020 ◽  
Vol 8 (5) ◽  
pp. 985-991
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Daily Basis ◽  
Cloud Services ◽  
Cloud Provider ◽  
Cloud Infrastructure ◽  
Cloud Service Providers ◽  
Architectural Framework ◽  
The Cost ◽  
Cloud Applications

The increase in the amount of data generated on a daily basis coupled with the need to store and manage this data has encouraged the organizations to adopt cloud computing. In order to ensure better availability and reliability of their data as well as resources, most of the organizations make use of one or more cloud service providers .But the use of cloud resources puts forth some challenges as well. One of the challenges is its detailed monitoring. As the number of services utilized by the cloud consumers goes on increasing, the number of logs and metrics generated by them also scales rapidly.The dynamic nature of cloud infrastructure and the variety of services offered by several cloud vendors demands a sophisticated mechanism to calculate and analyze the cost of using different services. The billing reports by the cloud service providers deliver statistics about the usage of resources and the costs associated with them. It contains large amount of data which needs to be processed in order to gain useful information. In this paper, we propose a micro service based architectural framework which gathers the data from two different cloud service providers. This data is not only stored but processed to generate reports to enable optimal use of cloud infrastructure. The use of microservices framework provides benefits and is a preferred framework for the development of cloud applications. The main aim of this work is to provide an integrated mechanism to enable the comparison of cost for using similar cloud services.

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