scholarly journals A Novel Probabilistic Strategy for Delay Corrected Allocation in Shared Resource Systems

2017 ◽  
Vol 17 (2) ◽  
pp. 83-96
Author(s):  
G. Arun Kumar ◽  
Aravind Sundaresan ◽  
Snehanshu Saha ◽  
Bidisha Goswami ◽  
Shakti Mishra
Keyword(s):  
Resource Allocation ◽  
Learning Strategy ◽  
Service Providers ◽  
A Priori ◽  
Peak Load ◽  
Service Level Agreement ◽  
Service Level ◽  
Cloud Provider ◽  
Average Delay ◽  
Priori Information

Abstract Cloud computing offers scalable services to the user where computing resources are owned by a cloud provider. The resources are offered to clients on pay-per-use basis. However, since multiple clients share the cloud’s resources, they could potentially interfere with each others’ task during peak load instances. The environment changes every instant of time with a new set of job requests demanding resource while another set of jobs relieving another set of resources. A major challenge among the service providers is to maintain a balance without compromising Service Level Agreement (SLA). In case of peak load, when each client strives for a particular resource in minimal time, the resource allocation problem becomes more challenging. The important issue is to fulfil the SLA criterion without delaying the resource allocation. The paper proposes a n-player game-based Machine learning strategy that would forecast outcome using a priori information available and measure/estimate existing parameters such as utilization and delay in an optimal load-balanced paradigm. The simulation validates the conclusion of the theorem by showing that average delay is low and stays in that range as the number of job requests increase. In future, we shall extend this work to multi-resource, multi-user environment.

scholarly journals Resource Allocation Techniques in Cloud Computing: A Review and Future Directions

2020 ◽  
Vol 26 (6) ◽  
pp. 40-51
Author(s):  
Muhammad Faraz Manzoor ◽  
Adnan Abid ◽  
Muhammad Shoaib Farooq ◽  
Naeem A. Azam ◽  
Uzma Farooq
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Literature Review ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Process Data ◽  
Future Directions ◽  
Computing Model ◽  
Structured Literature Review

Cloud computing has become a very important computing model to process data and execute computationally concentrated applications in pay-per-use method. Resource allocation is a process in which the resources are allocated to consumers by cloud providers based on their flexible requirements. As the data is expanding every day, allocating resources efficiently according to the consumer demand has also become very important, keeping Service Level Agreement (SLA) between service providers and consumers in prospect. This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. In the light of the uniqueness of the models and techniques, the main aim of the resource allocation is to limit the overhead/expenses associated with it. This research aims to present a comprehensive, structured literature review on different aspects of resource allocation in cloud computing, including strategic, target resources, optimization, scheduling and power. More than 50 articles, between year 2007 and 2019, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and they are reviewed under clearly defined objectives. It presents a topical taxonomy of resource allocation dimensions, and articles under each category are discussed and analysed. Lastly, salient future directions in this area are discussed.

Review on Mapping of Tasks to Resources in Cloud Computing

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Resource Allocation ◽  
Service Providers ◽  
Service Level Agreement ◽  
Scheduling Algorithms ◽  
Service Level ◽  
Storage Network ◽  
Use Factors ◽  
Cloud Users ◽  
Cloud Resources

Resource allocation and scheduling algorithms are the two essential factors that determine the satisfaction of cloud users. The major cloud resources involved here are servers, storage, network, databases, software and so on based on requirements of customers. In the competitive scenario, each service provider tries to use factors like optimal configuration of resources, pricing, Quality of Service (QoS) parameters and Service Level Agreement (SLA) in order to benefit cloud users and service providers. Since, many researchers have proposed different scheduling algorithms and resource allocation strategies, it becomes a cumbersome task to conclude which ones really benefit customers and service providers. Hence, this paper analyses and presents the most relevant considerations that would help the cloud researchers in achieving their goals in terms of mapping of tasks to cloud resources.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

A Novel QoS Aware Shortest Path Algorithm for VSDN

2017 ◽  
Vol 6 (1) ◽  
pp. 1-14
Author(s):  
Amandeep Kaur Sandhu ◽  
Jyoteesh Malhotra
Keyword(s):  
Energy Consumption ◽  
Shortest Path ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Software Defined Networks ◽  
Shortest Path Algorithm ◽  
Internet Service ◽  
Decrease Energy Consumption

This article describes how a rapid increase in usage of internet has emerged from last few years. This high usage of internet has occurred due to increase in popularity of multimedia applications. However, there is no guarantee of Quality of Service to the users. To fulfill the desired requirements, Internet Service Providers (ISPs) establish a service level agreement (SLA) with clients including specific parameters like bandwidth, reliability, cost, power consumption, etc. ISPs make maximum SLAs and decrease energy consumption to raise their profit. As a result, users do not get the desired services for which they pay. Virtual Software Defined Networks are flexible and manageable networks which can be used to achieve these goals. This article presents shortest path algorithm which improves the matrices like energy consumption, bandwidth usage, successful allocation of nodes in the network using VSDN approach. The results show a 40% increase in the performance of proposed algorithms with a respect to existing algorithms.

Broker-based optimization of SLA negotiations in cloud computing

2021 ◽  
Vol 17 (2) ◽  
pp. 179-195
Author(s):  
Priyanka Bharti ◽  
Rajeev Ranjan ◽  
Bhanu Prasad
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Service Level Agreement ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Environment ◽  
Negotiation Strategies ◽  
Sla Negotiation ◽  
Conflicting Interests ◽  
The Impact

Cloud computing provisions and allocates resources, in advance or real-time, to dynamic applications planned for execution. This is a challenging task as the Cloud-Service-Providers (CSPs) may not have sufficient resources at all times to satisfy the resource requests of the Cloud-Service-Users (CSUs). Further, the CSPs and CSUs have conflicting interests and may have different utilities. Service-Level-Agreement (SLA) negotiations among CSPs and CSUs can address these limitations. User Agents (UAs) negotiate for resources on behalf of the CSUs and help reduce the overall costs for the CSUs and enhance the resource utilization for the CSPs. This research proposes a broker-based mediation framework to optimize the SLA negotiation strategies between UAs and CSPs in Cloud environment. The impact of the proposed framework on utility, negotiation time, and request satisfaction are evaluated. The empirical results show that these strategies favor cooperative negotiation and achieve significantly higher utilities, higher satisfaction, and faster negotiation speed for all the entities involved in the negotiation.

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
Author(s):  
Suvendu Chandan Nayak ◽  
Sasmita Parida ◽  
Chitaranjan Tripathy ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Utilization ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Different Types ◽  
Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

ODACE SLA

2010 ◽  
Vol 1 (3) ◽  
pp. 1-20 ◽  
Author(s):  
Kaouthar Fakhfakh ◽  
Tarak Chaari ◽  
Said Tazi ◽  
Mohamed Jmaiel ◽  
Khalil Drira
Keyword(s):  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Second Step ◽  
Technical Knowledge ◽  
Complex Task ◽  
Semantic Matching ◽  
The Third ◽  
Draft Version ◽  
Fourth Step

The establishment of Service Level Agreements between service providers and clients remains a complex task regarding the uninterrupted growth of the IT market. In fact, it is important to ensure a clear and fair establishment of these SLAs especially when providers and clients do not share the same technical knowledge. To address this problem, the authors started modeling client intentions and provider offers using ontologies. These models helped them in establishing and implementing a complete semantic matching approach containing four main steps. The first step consists of generating correspondences between the client and the provider terms by assigning certainties for their equivalence. The second step corrects and refines these certainties. In the third step, the authors evaluate the matching results using inference rules, and in the fourth step, a draft version of a Service Level Agreement is automatically generated in case of compatibility.

SLA Monitoring of Presence-Enabled Services

2011 ◽  
pp. 307-322
Author(s):  
Tapati Bandopadhyay ◽  
Pradeep Kumar
Keyword(s):  
Service Providers ◽  
Instant Messaging ◽  
Service Level Agreement ◽  
Service Level ◽  
Application Framework ◽  
End User ◽  
New Approach ◽  
Clear Guideline ◽  
Evaluation Measurement ◽  
Monitoring Service

The concept of presence was initially associated with an instant messaging service, allowing an end user to recognize the presence of a peer online to send or receive messages. Now the technology has grown up to include various services like monitoring performance of any type of end user device, and services are accessible from anywhere, any time. The need for enhanced value remains the driving force behind these services, for example, Voice over Internet Protocol (VoIP) services, which is drawing tremendous research interest in services performance evaluation, measurement, benchmarking, and monitoring. Monitoring service level parameters happens to be one of the most interesting application-oriented research issues because various service consumers at the customer companies/end users’ level are finding it very difficult to design and monitor an effective SLA (Service Level Agreement) with the presence-enabled service providers. This chapter focuses on to these specific issues and presents a new approach of SLA monitoring through Data Envelopment Analysis (DEA). This extreme point approach actually can work much better in the context of SLA monitoring than general central-tendency-based statistical tools, a fact which has been corroborated by similar application examples of DEA presented in this chapter and has therefore it acts as the primary motivation to propose this new approach. Towards this end, this chapter first builds up the context of presence-enabled services (Day, Rosenburg, & Sugano, 2000), its SLA and SLA parameters, and the monitoring requirements. Then it explains the basics of DEA and its application in various other engineering and services context. Ultimately, a DEA application framework for monitoring an SLA of presence-enabled services is proposed which can serve as a clear guideline for the customers of presence-enabled services, not only for SLA monitoring but also at various other stages of implementing presence-enabled services frameworks. This approach exploits the definitive suitability of the application of DEA methods to presence-enabled service monitoring problems, and can be easily implemented by the industry practitioners.

scholarly journals A Novel Energy Efficient Resource Management System in Cloud Computing Environment.

2018 ◽  
Vol 7 (4.19) ◽  
pp. 1030
Author(s):  
S. K. Sonkar ◽  
M. U.Kharat
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Resource Management ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Service Providers ◽  
Optimization Techniques ◽  
Cloud Provider ◽  
Efficient Resource ◽  
Machine Allocation

Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization.  For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.  

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