scholarly journals A Novel Loom for Alacrity of Protected Lawsuit dealings using Cloud Computing Environment

Author(s):  
B.V. Subba Rao ◽  
J. Rajendra Prasad ◽  
D. Kavitha ◽  
J. Sirisha ◽  
K. Swaroopa Rani

This paper suggest a well-organized information system for facilitate the litigation procedures Information System courts. The purpose is to decrease the duration of processing cases in courts. The aspiration is to save the time and effort of judges and lawyer. In addition, we make use of the advantages of electronic systems and reducing traffic especially in developed countries. Advanced Encryption Standard is used to encrypt all the manipulated data for each case. All read document are encrypted to attain secure information system Litigation process. This is because the big data for all cases will be stored on cloud environment.

Author(s):  
B.V. Subba Rao ◽  
J. Rajendra Prasad ◽  
D. Kavitha ◽  
J. Sirisha ◽  
K. Swaroopa Rani

This paper suggest a well-organized information system for facilitate the litigation procedures Information System courts. The purpose is to decrease the duration of processing cases in courts. The aspiration is to save the time and effort of judges and lawyer. In addition, we make use of the advantages of electronic systems and reducing traffic especially in developed countries. Advanced Encryption Standard is used to encrypt all the manipulated data for each case. All read document are encrypted to attain secure information system Litigation process. This is because the big data for all cases will be stored on cloud environment.


Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.


Author(s):  
Lavanya S. ◽  
Susila N. ◽  
Venkatachalam K.

In recent times, the cloud has become a leading technology demanding its functionality in every business. According to research firm IDC and Gartner study, nearly one-third of the worldwide enterprise application market will be SaaS-based by 2018, driving annual SaaS revenue to $50.8 billion, from $22.6 billion in 2013. Downtime is treated as the primary drawback which may affect great deals in businesses. The service unavailability leads to a major disruption affecting the business environment. Hence, utmost care should be taken to scale the availability of services. As cloud computing has plenty of uncertainty with respect to network bandwidth and resources accessibility, delegating the computing resources as services should be scheduled accordingly. This chapter proposes a study on cloud of clouds and its impact on a business enterprise. It is also decided to propose a suitable scheduling algorithm to the cloud of cloud environment so as to trim the downtime problem faced by the cloud computing environment.


2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling controller for the optimal use of cloud resources.


Cloud ecosystem basically offers Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and Software as a Service (SaaS). This paper describes the testing process employed for testing the C-DAC cloud SuMegha. Though new tools for the testing cloud are emerging into the market, there are aspects which are suited for manual testing and some which can be speeded up using automated testing tools. This paper brings out the techniques best suited to test different features of Cloud computing environment. It offers a comparison of several tools which enhance the testing process at each level. The authors also try to bring out (recommend) broad guidelines to follow while setting up a cloud environment to reduce the number of bugs in the system


2015 ◽  
Vol 37 ◽  
pp. 427
Author(s):  
Minoo Soltanshahi ◽  
Aliakbar Niknafs

Cloud computing is the latest distributed technology providing a rich environment of dynamically shared resources through virtualization, which can fulfill the requirements of users by allocating resources to programs. Any program in a cloud environment is delivered by workflows which are a series of interlinked tasks to accomplish a goal. One of the most important tasks in cloud computing is correct mapping of tasks onto resources. It is essential to schedule processes in distributed systems such as cloud, since it leaves a tremendous impact on the system performance. This is done by scheduling algorithms. Therefore, it is crucial to present and adopt an efficient algorithm in the cloud environment. This article attempted to examine the parameters effective in the efficiency of scheduling algorithms including deadline, cost constraint, balanced loading, power consumption and fault tolerance. Additionally, the performances of several algorithms were briefly discussed.


Cloud environment basically offers Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS). Here we describe the testing process employed for performance testing. Though new tools for testing cloud are emerging into the market, there are aspects which are suited for manual testing and some which can be speeded up using automatic testing tools. This paper brings out the techniques best suited to test different features of Cloud computing environment. The authors also try to bring out (recommend) broad guidelines to follow while setting up a cloud environment to reduce the number of bugs in the system.


2019 ◽  
Vol 9 (1) ◽  
pp. 279-291 ◽  
Author(s):  
Proshikshya Mukherjee ◽  
Prasant Kumar Pattnaik ◽  
Tanmaya Swain ◽  
Amlan Datta

AbstractThis Paper focuses on multi-criteria decision making techniques (MCDMs), especially analytical networking process (ANP) algorithm to design a model in order to minimize the task scheduling cost during implementation using a queuing model in a cloud environment and also deals with minimization of the waiting time of the task. The simulated results of the algorithm give better outcomes as compared to other existing algorithms by 15 percent.


Author(s):  
R.G. Alakbarov ◽  
◽  
M.A. Hashimov ◽  

The paper deals with the migration of SCADA (Supervisory Control and Data Acquisition) systems widely used in the monitoring and management of the oil and gas industry to the cloud computing environment. There arise various problems in data collection, transmission, and processing because of traditional SCADA systems being very expensive, inflexible, and complicated scalability. The transferring of the SCADA system's applications to the cloud environment reduces costs and improves scalability. The purchase of hardware and software is carried out at a lower cost than its installation and maintenance. In the article, the usage of cloud-based SCADA systems has been proposed for easy, safe, reliable and quick collection and processing of data from facilities installed in the oil and gas industry.


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