A Feasibility Study of Service Level Agreement Compliance for Start-Ups in Cloud Computing

2020 ◽  
pp. 407-417
Author(s):  
T. Lavanya Suja ◽  
B. Booba
Keyword(s):  
Cloud Computing ◽  
Feasibility Study ◽  
Service Level Agreement ◽  
Service Level ◽  
Start Ups

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.

scholarly journals Multilevel classification of security threats in cloud computing

2017 ◽  
Vol 7 (1.5) ◽  
pp. 253
Author(s):  
N. Srinivasu ◽  
O. Sree Priyanka ◽  
M. Prudhvi ◽  
G. Meghana
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Service Level Agreement ◽  
Service Level ◽  
Security Threats ◽  
Security Threat ◽  
Security Issues ◽  
Network Applications ◽  
Storage Network ◽  
Multilevel Classification

Cloud Security was provided for the services such as storage, network, applications and software through internet. The Security was given at each layer (Saas, Paas, and Iaas), in each layer, there are some security threats which became the major problem in cloud computing. In Saas, the security issues are mainly present in Web Application services and this issue can be overcome by web application scanners and service level agreement(SLA). In Paas, the major problem is Data Transmission. During transmission of data, some data may be lost or modified. The PaaS environment accomplishes proficiency to some extent through duplication of information. The duplication of information makes high accessibility of information for engineers and clients. However, data is never fully deleted instead the pointers to the data are deleted. In order to overcome this problem the techniques that used are encryption[12], data backup. In Iaas the security threat that occurs in is virtualization and the techniques that are used to overcome the threats are Dynamic Security Provisioning(DSC), operational security procedure, for which Cloud Software is available in the market, for e.g. Eucalyptus, Nimbus 6.

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.

Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment

2012 ◽  
Vol 2 (3) ◽  
pp. 86-97
Author(s):  
Veena Goswami ◽  
Sudhansu Shekhar Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Finite Buffer ◽  
Web Browser ◽  
Computing Paradigm ◽  
Computing Services ◽  
Multi Server

Cloud computing is a new computing paradigm in which information and computing services can be accessed from a Web browser by clients. Understanding of the characteristics of computer service performance has become critical for service applications in cloud computing. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services (QoS) is crucial. Based on the Service level agreement, the requests are processed in the cloud centers in different modes. This paper analyzes a finite-buffer multi-server queuing system where client requests have two arrival modes. It is assumed that each arrival mode is serviced by one or more Virtual machines, and both the modes have equal probabilities of receiving service. Various performance measures are obtained and optimal cost policy is presented with numerical results. The genetic algorithm is employed to search the optimal values of various parameters for the system.

scholarly journals Performance-based service-level agreement in cloud computing to optimise penalties and revenue

2020 ◽  
Vol 14 (7) ◽  
pp. 1102-1112 ◽  
Author(s):  
Afzal Badshah ◽  
Anwar Ghani ◽  
Shahaboddin Shamshirband ◽  
Giuseppe Aceto ◽  
Antonio Pescapè
Keyword(s):  
Cloud Computing ◽  
Service Level Agreement ◽  
Service Level

scholarly journals Service Level Agreement Violation Preventive Task Scheduling for Quality of Service Delivery in Cloud Computing Environment

2020 ◽  
Vol 178 ◽  
pp. 375-385
Author(s):  
Ismail Zahraddeen Yakubu ◽  
Zainab Aliyu Musa ◽  
Lele Muhammed ◽  
Badamasi Ja’afaru ◽  
Fatima Shittu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Service Delivery ◽  
Task Scheduling ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment

Dynamic Management of Resources in Cloud Computing

2020 ◽  
Vol 8 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Pradeep Kumar Tiwari ◽  
Sandeep Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Level Agreement ◽  
Service Level ◽  
Poor Quality ◽  
Migration Time ◽  
Load Imbalance ◽  
Management Of Resources ◽  
And Migration

It has already been proven that VMs are over-utilized in the initial stages and are underutilized in the later stages. Due to the random utilization of the CPU, resources are sometimes heavily loaded whereas other resources are idle. Load imbalance causes service level agreement (SLA) violations resulting in poor quality of service (QoS) aided by the imperfect management of resources. An effective load balancing mechanism helps to achieve balanced utilization, which maximizes the throughput, availability, and reliability and reduces the response and migration time. The proposed algorithm can effectively minimize the response and the migration time and maximize reliability, and throughput. This research also helps to understand the load balancing policies and analysis of other research works.

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