Simulation of Cloud Computing

Organizations worldwide commonly utilize cloud infrastructure to manage large volumes of data, making the optimization of storage crucial for enhancing cloud performance. One effective optimization technique is data deduplication, which identifies duplicate objects and ensures that only one copy of unique data is stored in the cloud. While several deduplication schemes currently exist, there is a pressing need to improve efficiency in cloud storage through innovative approaches. In this paper, we propose a new system model designed to facilitate an efficient deduplication process. Our algorithm, called deduplication in cloud infrastructure (DCI), offers a systematic and effective method for handling deduplication challenges related to redundant data storage. DCI focuses on hash generation, metadata comparison, and pointer-based deduplication, providing a comprehensive strategy for optimizing cloud storage resources and minimizing duplication. This ultimately enhances both the efficiency and cost-effectiveness of cloudbased data management. A simulation study using CloudSim and the Hadoop distributed file system (HDFS) simulator demonstrates that the proposed deduplication method is effective. Experimental results show that our algorithm outperforms many existing solutions, achieving the highest deduplication ratio of 6.7 and saving 85.09% of storage space due to its efficient deduplication approach. The proposed system can be used in cloud infrastructures for efficiency.

Cloud computing has become known as an extensive vision of function computing pattern that makes available dependable and durable communications for consumers to remotely store data and personal information, and utilize on require applications and services. In the present scenario, many human beings and associations moderate the trouble of local data storage space and decrease the preservation expenditure by outsourcing data to the cloud users.

Cloud computing has become known as an extensive vision of function computing pattern that makes available dependable and durable communications for consumers to remotely store data and personal information, and utilize on require applications and services. In the present scenario, many human beings and associations moderate the trouble of local data storage space and decrease the preservation expenditure by outsourcing data to the cloud users.

Cloud Computing is a new paradigm which allows individuals and organizations to purchase resources like compute, storage, networking etc as a utility with minimum human intervention. According to recent surveys more than half of the large to medium size organizations have already migrated to the cloud. Despite of providing resources as a utility and its wide spread acceptance in the IT community, cloud computing is still at its prime and poses many challenges like automated service provisioning, virtual machine migration, server consolidation, energy management, traffic analysis, data security, software frameworks which needs considerable amount of research to stabilize. Conducting research on live cloud environments for individuals or small institutions is very difficult due to the costs involved in setting up a cloud. This paper presents various cloud simulators which were developed over the years that are a cost effective way of conducting cloud research tasks. This paper compares almost 17 cloud simulators based on diverse criteria and the result and explanations are presented which enables new researchers to choose a suitable cloud simulator.

The purpose of this research is to empirically examine the effect of third party auditor and quality service to cloud storage and user trust. This research is causal quantitative and use partial least square and path analysis. The research object is corporation users of cloud computing storage in listed corporation in Indonesia Stock Exchange. The sample size is 368 corporations and the results of the research are as follow: third party auditor has positive effect on both cloud storage security and cloud user trust. Quality of service has positive effect on both cloud storage security and cloud user trust. Cloud storage security has positive effect on cloud user trust.

Cloud computing is an established technology to provide computing resources on demand that currently faces several challenges. Main challenges include management of shared resources, energy consumption, load balancing, resource provisioning and allocation, and fulfilment of service level agreements (SLAs). Due to its inherent complexity, cloud simulation is largely used to experiment new models and algorithms. This work presents CloudSim Plus, an open source simulation framework that pursues conformance to software engineering principles and object-oriented design in order to provide an extensible, modular and accurate tool. Based on the CloudSim framework, it aims to improve several engineering aspects, such as maintainability, reusability and extensibility. This work shows the benefits of CloudSim Plus, its particular features, how it ensures more accuracy, extension facility and usage simplicity.

The purpose of this research is to empirically examine the effect of third party auditor and quality service to cloud storage and user trust. This research is causal quantitative and use partial least square and path analysis. The research object is corporation users of cloud computing storage in listed corporation in Indonesia Stock Exchange. The sample size is 368 corporations and the results of the research are as follow: third party auditor has positive effect on both cloud storage security and cloud user trust. Quality of service has positive effect on both cloud storage security and cloud user trust. Cloud storage security has positive effect on cloud user trust.

The purpose of this research is to empirically examine the effect of third party auditor and quality service to cloud storage and user trust. This research is causal quantitative and use partial least square and path analysis. The research object is corporation users of cloud computing storage in listed corporation in Indonesia Stock Exchange. The sample size is 368 corporations and the results of the research are as follow: third party auditor has positive effect on both cloud storage security and cloud user trust. Quality of service has positive effect on both cloud storage security and cloud user trust. Cloud storage security has positive effect on cloud user trust.

Cloud computing is an established technology to provide computing resources on demand that currently faces several challenges. Main challenges include management of shared resources, energy consumption, load balancing, resource provisioning and allocation, and fulfilment of service level agreements (SLAs). Due to its inherent complexity, cloud simulation is largely used to experiment new models and algorithms. This work presents CloudSim Plus, an open source simulation framework that pursues conformance to software engineering principles and object-oriented design in order to provide an extensible, modular and accurate tool. Based on the CloudSim framework, it aims to improve several engineering aspects, such as maintainability, reusability and extensibility. This work shows the benefits of CloudSim Plus, its particular features, how it ensures more accuracy, extension facility and usage simplicity.

Cloud Computing is largely used utility for computing, where users can store their data into the cloud and access data from cloud as when they required so user can enjoy quality services from a computing resources. By data outsourcing, users can get free from the burden of data storage and data maintenance. Enabling public auditing for cloud data storage security is of critical importance so that users can restore to an external audit party to check the integrity of outsourced data when needed. To maintain this data efficiently, there is a necessity of data recovery services. First it help the users to collect information in the form of multimedia form from any remote location in the absence of network connectivity and second to recovery the files on data loss or if the server gets failed due to any reason.

Nowadays the fast growth and evolution on technologies such as cloud computing, mobile computing and geographic information systems (GIS) inherently exhibit spatiotemporal phenomena. These technologies have created opportunities for business implementation that utilize advanced mapping, mobile field-based applications and location aware systems. The capability to process and handle a big volume of data using cloud computing and to access location information via mobile have made GIS technology utilizes more widely. In this paper, we introduce a new mobile GIS cloud computing architecture that increase the efficiency of processing by decreasing the transmission time for data this is based on decreasing the size of transmitted data. The mobile geographic patrolling system based on cloud GIS has great significance for the development of gas pipeline patrolling. We propose pipeline patrolling prototype system which utilizes such technology.

Cloud computing has maintained popularity and attraction in the ICT industry. Many business organizations have embraced the benefits that it offers and many more are still working towards cloud computing. One of the many concerns many organizations and individuals have about cloud computing from its inception is how to test the services and opportunities offered by cloud computing. This concern is as a result of the cost of running experiments on real cloud system and the fact that real infrastructure limits experiments within the size of the infrastructure, thereby making it really difficult to reproduce test. The alternative solution to this concern is the use of cloud simulation tools which offer a cloud environment to test cloud services in a repeated and controlled manner at no cost. Many cloud simulation tools have been developed since the inception of cloud computing. These tools have their strengths and weakness in modelling and simulating cloud system. This paper reviews some simulation tools and compares them in terms of their underlying framework, programming language, GUI, availability, cost modelling, energy modelling, simulation time, federation policy and communication model.

Storing and sharing of data in hybrid cloud is most commonly used but it poses many challenges of maintaining the secrecy of the data and anonymity of the user signing the data from the malicious users during public auditing. In literature many mechanisms have been introduced that works in achieving these challenges. ORUTA (One Ring to Rule Them All) is one such mechanism that works on privacy preserving public auditing. But ORUTA does not focus on dynamicity, traceability, freshness property and it mainly concentrates on static group. It also provides only partial auditing.The system proposed in this paper aims at fulfilling dynamicity, preserving identity of user and privacy of data. It also provides complete public auditability in hybrid cloud. The privacy of data and identity of the user signing the data is kept confidential and it is also safeguarded from adversaries internal and external to the group. This is achieved by using the Tri Degree Coalition (TDC) Architecture and Vi...

Hundreds of thousands of servers from data centers are operated to provide users with pay-as-yougo infrastructure as a service, platform as a service, and software as a service. Many different types of virtual machine (VM) instances hosted on these servers oftentimes need to efficiently communicate with data movement under current bandwidth capacity. This motivates providers to seek for a bandwidth scheduler to satisfy objectives, namely assuring the minimum bandwidth per VM for the guaranteed deadline and eliminating network congestion as much as possible. Based on some rigorous mathematical models, we formulated a cloud-based bandwidth scheduling algorithm which enables dynamic and fair bandwidth management by categorizing the total bandwidth into several categories and adjusting the allocated bandwidth limit per VM for both upstream and downstream traffics in real time. The simulation showed that paradigm was able to utilize the total assigned bandwidth more efficiently compared ...

Hundreds of thousands of servers from data centers are operated to provide users with pay-as-yougo infrastructure as a service, platform as a service, and software as a service. Many different types of virtual machine (VM) instances hosted on these servers oftentimes need to efficiently communicate with data movement under current bandwidth capacity. This motivates providers to seek for a bandwidth scheduler to satisfy objectives, namely assuring the minimum bandwidth per VM for the guaranteed deadline and eliminating network congestion as much as possible. Based on some rigorous mathematical models, we formulated a cloud-based bandwidth scheduling algorithm which enables dynamic and fair bandwidth management by categorizing the total bandwidth into several categories and adjusting the allocated bandwidth limit per VM for both upstream and downstream traffics in real time. The simulation showed that paradigm was able to utilize the total assigned bandwidth more efficiently compared to algorithms such as bandwidth efficiency persistence proportional sharing (PPS), PPS, and PS at the network level.

It has been widely observed that the concept of cloud computing is become one of major theory in the world of IT industry. It involves storing the user's data to be able to use the applications and services that the clouds introduce. There is a significant numbers of risks can be occurred. One of these risks that can attack the cloud computing is the integrity of the data stored in the cloud [2]. In order to overcome the threat of integrity of the data, the user must be able to use the assistance of a Third Party Auditor (TPA). The TPA has an experience that clouds users does not have, and checks over the integrity that is difficult for the users to check. The user can handout the integrity checking mission to the TPA, in such a way that the TPA will not be able to manipulate with the client data with one way or another [5]. In this paper, we will introduce a model for the integrity checking over the cloud computing with the support of the TPA using digital signature technique. The proposed model result was shown efficiently with a number of situations that performed by unauthorized attackers. The checking done over two parts the CSP and TPA, without giving any secure data that void the integrity definition and without uploading any secure data to the cloud.

Cloud computing is new technology with its ease of access and a variety of applications. If offers various types of services to the user, such as software as a service, platform as a service and hardware as a service or infrastructure as a service. The deployment of real cloud for commercial use is quite expensive. Therefore, various kinds of simulators such as CloudSim, GroudSim, CDOSim, GreenCloud are available in the market for cloud environment. In this paper, we have done a study and analysis of various simulators available for cloud computing.

Web services is become major issue in distributed data mining. In the literature we can found a number of proposals of privacy preserving which can be divided into two major categories that is trusted third party and multiparty based privacy protocols. In case of the trusted third party privacy protocol models the conventional asymmetric cryptographic based techniques or algorithms will be used and in case of the multi party based protocols data perturbed technique can be used to ensure no other party to understand original data. In order to improve security features by combining strengths of both the above said models in this work, we propose to use data perturbed techniques in third party privacy preserving protocol to conduct the secure web service. In order to perform web service we propose third party protocol for secure computations. Our results shown that although the data are disguised and decentralized, our method can still achieve literally high accuracy.

Cloud storage is one of popular cloud service model that stores data on the Internet through thecloud computing provider who manages and provides Storage as a service to the end users. Incloud storage huge amount of data will becomes duplicated due to the multiple uploads from thedifferent users for the same data. The cloud servers want to reduce the volume of data stored bythe client which has the similar content and the client wants to maintain the integrity of the data uploaded to the cloud storage. To achieve this there are several models defined using the deduplication and integrity auditing delegation techniques. This project work is to show an implementation of the combining the deduplication algorithm with the data integrity auditing algorithm to achieve the goals of removing the duplication of data and providing the integrity of data to the client. The data considered will be in encryptedformand thehash data isusedto verifythe correctness ofthe data. The proposed algorithm will satisfy the fundamental security requirements and provides an userinterface for the client and the server admin to present the proper management of the data storedon cloud storage. The project work is implemented using the java language on Google drivestorage.

The article SOLID Principles in Software Architecture and Introduction to RESM concept in OOP gives an outlook of the SOLID principles and to the concepts of Reusability, Extensibility, Simplicity and Maintainability (RESM) in Object Oriented Programming.

This paper studies the delay-optimal virtual machine (VM) scheduling problem in cloud computing systems, which have a constant amount of infrastructure resources such as CPU, memory and storage in the resource pool. The cloud computing system provides VMs as services to users. Cloud users request various types of VMs randomly over time and the requested VM-hosting durations vary vastly. A multi-level queue scheduling algorithm partitions the ready queue into several separate queues. The processes are permanently assigned to one queue, generally based on some property of the process, such as memory size, process priority or process type. Each queue has its own scheduling algorithm. Similarly, a process that waits too long in a lower-priority queue may be moved to a higher-priority queue. Multi-level queue scheduling is performed via the use of the Particle Swarm Optimization algorithm (MQPSO). It checks both Shortest-Job-First (SJF) buffering and Min-Min Best Fit (MMBF) scheduling algorithms, i.e., SJF-MMBF, is proposed to determine the solutions. Another scheme that combines the SJF buffering and Extreme Learning Machine (ELM)-based scheduling algorithms, i.e., SJF- ELM, is further proposed to avoid the potential of job starva¬tion in SJF-MMBF. In addition, there must be scheduling among the queues, which is commonly implemented as fixed-priority preemptive scheduling. The simulation results also illustrate that SJF- ELM is optimal in a heavy-loaded and highly dynamic environment and it is efficient in provisioning the average job hosting rate.

The main aim of this paper is to study the role of E-marketing in sales enhancement in Jordan. A questionnaire was adopted from previous studies and distributed among managers, assistant or deputy director, and head of division at (LG) Levant company in Jordan. The sample of the study consisted 108 respondents. SPSS software was used to analyze the data. The study concluded a number of results achieved (LG) Levant company in Jordan (= 0.05 α) for electronic marketing in its dimensions (Facebook, Twitter, mobile applications) on the activation of sales with indicators (purchase percentage, repeat purchase) in Jordan. The researchers also recommended the need to work to achieve success. And the need to develop the concept of solving the problem of sales in (LG) Levant company in Jordan.

Cloud computing is an established technology to provide computing resources on demand that currently faces several challenges. Main challenges include management of shared resources, energy consumption, load balancing, resource provisioning and allocation, and fulfilment of service level agreements (SLAs). Due to its inherent complexity, cloud simulation is largely used to experiment new models and algorithms. This work presents CloudSim Plus, an open source simulation framework that pursues conformance to software engineering principles and object-oriented design in order to provide an extensible, modular and accurate tool. Based on the CloudSim framework, it aims to improve several engineering aspects, such as maintainability, reusability and extensibility. This work shows the benefits of CloudSim Plus, its particular features, how it ensures more accuracy, extension facility and usage simplicity.

Cloud computing is an on demand service in which shared resources, information, software and other devices are provided according to the clients requirement at specific time. In such a scenario, resource scheduling algorithms play an important role where the aim is to schedule applications effectively so as to reduce the turnaround time and improve resource utilization. The problem of this paper is how to dynamically allocate the submitted jobs to the available resources in order to complete the tasks within a minimum turnaround time as well as utilizing cloud resources effectively. The objective of this paper is to propose new scheduling algorithm on cloud computing environment using Shortest Remaining Job First (SRJF) algorithm. The methodology of this paper depends on simulation using cloudsim. The results of this paper revealed that the proposed algorithm (SRJF) performed better than the default scheduling algorithm.

— In Regenerating-code-based cloud storage using Privacy-Preserving public auditing scheme there is no need of data owners for data change, we can change data using proxy and partial keys. Using Third Party Auditor which provide more security and allows the user to know the information about the data stored in the cloud. We elaborate on the correctness of verification with public auditing scheme and regenerating codes have gained Data integrity on cloud data storage.

— Cloud computing a new era opens a new era as it can provide various elastic and scalable IT services in a pay-as-you-go fashion, in which its users can reduce the huge capital investments in their own IT infrastructure. This philosophy is users of cloud storage services no longer physically maintain direct control over their data that makes data security as one of the concern of cloud. The existing research work allows data integrity to be verified without possession of the actual data file. After this when the verification is done by a trusted third party, this verification process is also called data auditing, and this third party is called an auditor. Many results that are related to experimental and theoretical which demonstrate that our scheme can offer not only enhanced security ,flexibility, but also significantly lower overhead for big data applications with a large number of frequent small updates, like a applications in social media and business transactions.

On cloud we can store and share files. In cloud, there is Third Party Auditor (TPA) which performs auditing of shared files. While auditing, it may happen that some data will be visible to TPA, the TPA may misuse it. In this paper, we proposed a system that will assign rights of TPA to the user who shares the file. This will reduce the significance of TPA form the existing system.

There are various initiatives used nowadays to achieve data
centres energy efficient systems, which are covered in this paper. We will introduce ten free software tools and techniques launched by Research Institutions or companies, in order to measure, monitor, simulate or implement energy savings, developed in 2009’-2015’ period. We will compare them by their benefits and limitations. This paper is mainly addressed to researchers of the field in order to give an overview of the alternatives they can choose from to implement experimental studies on the field of energy management computing systems.

Cloud computing and Big Data Analytics stores a large quantity of data, which provides scalable computing
storage, where user does not have any information where his data is stored but user can access the data which
is remotely stored in different data centres all over the world. In this paper we discussed the quality of service
for secured cloud system model. We focused on the role of Third Party Auditor (TPA) and Intelligence based
security system auditing with CIA Triad and AAA security management to protect data in cloud against
exploitations, by providing fault tolerance.  Cloud computing has become prominent of its on-demand network
access and scalability that is pay as you use. We concentrated on privacy preserving public auditing procedures
and algorithms that support regenerating code based data storage which facilitates the auditing scheme that
includes setup, audit and repair. We discussed risks, threats and attacks that prevent the auditor from detecting
the data losses and corruption. We focus on evaluating the performance based on time and computational
complexity using Testing Tools.  We proposed public auditing scheme for regenerating code based data storage.
The mathematical approach for regenerating code and auditing procedures are given and construction of
dynamic data verification system for auditing scheme is generated and proved.

Cloud computing environments facilitate applications by providing virtualized resources that can be provisioned dynamically. Computing resources are delivered by Virtual Machines (VMs). In such a scenario, resource scheduling algorithms play an important role where the aim is to schedule applications effectively so as to reduce the turn-around time and improve resource utilization. The problem of this paper is how to dynamically allocate the submitted jobs to the available resources in order to complete the tasks within a minimum turn-around time as well as utilizing cloud resources effectively. The objective of this paper is to propose new scheduling algorithm on cloud computing environment using Shortest Remaining Job First (SRJF) algorithm. The methodology of this paper  depends on simulation using cloudsim. The results of this paper revealed that the proposed algorithm (SRJF) performed better than the default scheduling algorithm.

Cloud computing is new technology with its ease of access and a variety of applications. If offers various types of services to the user, such as software as a service, platform as a service and hardware as a service or infrastructure as a service. The deployment of real cloud for commercial use is quite expensive. Therefore, various kinds of simulators such as CloudSim, GroudSim, CDOSim, GreenCloud are available in the market for cloud environment. In this paper, we have done a study and analysis of various simulators available for cloud computing.

Cloud computing is one of the emerging technologies with its ease of access and diverse applicability, letting customers attracted to it and thus posing many challenging issues that need to overcome in this field. Since the evolution of cloud computing: Load balancing, power constrains, program offloading, cost modelling and security issues are the popular research topic in this field. Deploying real cloud for testing or for commercial use is very costly. Cloud simulator helps to model various kinds of cloud application by creating Data Centre, Virtual Machine and many Utilities which can be added to configure it, thus making it very easy to analyse. Till now, many cloud simulators have been proposed and also available to use. These simulators are built for specific purpose, and have varying features in each of them. In this paper we presented a comprehensive study of major cloud simulators by highlighting their important features and analysing their pros and cons. we made a comparison among the simulators by considering their important attributes and finally concluded with our future direction.