DDMan: A Management System for Distributed Software Development in Cloud Computing Environments

Cloud computing is becoming very common in recent years and is growing rapidly due to its attractive benefits and features such as resource pooling, accessibility, availability, scalability, reliability, cost saving, security, flexibility, on-demand services, pay-per-use services, use from anywhere, quality of service, resilience, etc. With this rapid growth of cloud computing, there may exist too many users that require services or need to execute their tasks simultaneously by resources provided by service providers. To get these services with the best performance, and minimum cost, response time, makespan, effective use of resources, etc. an intelligent and efficient task scheduling technique is required and considered as one of the main and essential issues in the cloud computing environment. It is necessary for allocating tasks to the proper cloud resources and optimizing the overall system performance. To this end, researchers put huge efforts to develop several classes of scheduling algorithms to be suitable for the various computing environments and to satisfy the needs of the various types of individuals and organizations. This research article provides a classification of proposed scheduling strategies and developed algorithms in cloud computing environment along with the evaluation of their performance. A comparison of the performance of these algorithms with existing ones is also given. Additionally, the future research work in the reviewed articles (if available) is also pointed out. This research work includes a review of 88 task scheduling algorithms in cloud computing environment distributed over the seven scheduling classes suggested in this study. Each article deals with a novel scheduling technique and the performance improvement it introduces compared with previously existing task scheduling algorithms. Keywords: Cloud computing, Task scheduling, Load balancing, Makespan, Energy-aware, Turnaround time, Response time, Cost of task, QoS, Multi-objective. DOI: 10.7176/IKM/12-5-03 Publication date: September 30 th 2022

Resources are provided mainly in the form of services in cloud computing. In the distribute environment of cloud computing, how to find the needed services efficiently and accurately is the most urgent problem in cloud computing. In cloud computing, services are the intermediary of cloud platform, services are connected by lots of service providers and requesters and construct the complex heterogeneous network. The traditional recommendation systems only consider the functional and non-functional requirements of services but ignore the links between providers and requesters of service, which result to the service position is not accurate. Focus on the problems, this study intends to model the relationship of the cloud services participants with the format of heterogeneous information network, which intend to mine the hidden relationships between services participants in the cloud computing environment. In theoretical research, we proposed a cloud service heterogeneous network extraction and automatic maintenance model, proposed a new service recommendation system based on heterogeneous service network ranking and clustering.

 Abstract—Cloud computing is an emerging technology that is still unclear to many security problems. Ensuring the security ofstored data in cloud servers is one of the most challenging issues in such environments. Accordingly, this schema presents a Hybrid Encryption algorithm that is based on RSA Small-e and Efficient RSA (HE-RSA) for improving the reliability in cloud computing environments. The main aim of this project is to use the cryptography concepts in cloud computing communications and to increase the security of encrypted data in cloud servers with the least consumption of time and cost at the both of encryption and decryption processes.In the proposed model, the number of key generation exponents has been increased in comparison to the original RSA. Moreover,a dual encryption process has been applied in this algorithm to prevent common attacks against RSA algorithm. In addition, this schema also presents the comparison between HE-RSA and original RSA in terms of security and performance. For this purpose, Key Generation, Encryption and Decryption Time in Original RSA and HE-RSA have been compared according to the different size of exponents. Moreover, some of the common attacks against RSA algorithm have been analysed to detect the resistance of the proposed algorithm against possible attacks. Finally, the effects of using HE-RSA on cloud computing environments have been reviewed in more depth and details.

This project establishes a Chinese wall security policy model in the environment of cloud computing. In 1988 Brewer and Nash proposed a very nice commercial security policy in British financial world. Though the policy was well accepted, but the model was incorrect. A decade later, Dr. Lin provided a model in 2003 that meets Brewer & Nash’s Policy. One of the important components in Cloud computing is data center. In order for any company to store data in the center, a trustable security policy model is a must; Chinese wall security policy model will provide this assurance. The heart of the Chinese Wall Security Policy Model is the concept of Conflict of Interest (COI). The concept can be modeled by an anti-reflexive, symmetric and transitive binary relation. In this project, by extending Dr. Lin’s Model, we explore the security issues in the environment of cloud computing and develop a small system of the Chinese Wall Security Model.

Privacy-preserving multi-party logistic regression in cloud computing

With the rapid development of computers and the Internet, information technology has brought about great changes to our educational field. At present the ubiquitous “cloud service” has brought education into “the cloud era”. Cloud computing has found more applications in our English teaching. Integrating the technology of “cloud computing” with the theory of “multimodal discourse analysis”, this paper researches how to carry out multimodal English teaching in the cloud computing environment.

In China, with the continuous advance of cloud computing technologies such as virtualization technology and big data processing technology, small and medium-sized enterprises are constantly updating and improving their management information system. In recent years, computer network technology and information technology have been gradually applied to enterprise management. With the development of enterprises, a large number of heterogeneous software services deployed on different servers are accumulated in enterprises. Cloud computing can not only reduce the cost of informatization construction of small and medium-sized enterprises, strengthen the integration of information resources, promote resource sharing, but also promote enterprise management and service innovation. In view of the development of social economy and the advance of the industry, if the enterprise wants to be better based on the market, it must realize the scientific management mode, and constantly improve the efficiency and quality of work. Through the cloud computing model, this paper introduces the system construction of the management information system for small and medium-sized enterprises in the cloud computing environment and the implementation scheme of enterprises in the cloud computing environment.

The cloud computing is an Internet-based resource sharing system in which virtualized resources are provided over the Internet. Cloud computing refers to a class of systems and applications that employ distributed resources for use in various applications; these computing resources are utilized over a network to facilitate the execution of tasks. However, cloud computing resources are heterogeneous and dynamic, connecting a broad range of resources. Thus, there are a large numbers of application and data center in the cloud computing environment. Therefore, the security issues of authentication and communication in application services and data center need to be considered in the cloud computing environment.

In this paper, we conduct research on the library development prospects and challenges under the environment of big data and cloud computing. Increasingly nervous and public li braries are facing funding, resources construction pace slow or stagnant difficult situation, readers to the library cause in the new times challenge. Big data era has quietly come, for the knowledge storage, use and development as own duty, the library, how to improve the ability of handling large amounts of growth literature is urgent. Our methodology solves the issues well which will be meaningful.

In order to improve the task scheduling strategy, a method based on genetic algorithm in cloud computing environment was proposed. First, the independent task scheduling algorithm and associated task scheduling algorithm commonly used in cloud computing are studied and compared, respectively, and their application characteristics, advantages, and disadvantages are analyzed in detail. Second, an independent task scheduling strategy based on multipopulation genetic algorithm is proposed for independent task scheduling in cloud environment, considering the scheduling time, scheduling cost, and system resource utilization of task set. The implementation steps of the algorithm are given in detail. Finally, the simulation experiment is carried out on Cloud Sim platform. The experimental results show that computing resource M is 10, subtask N is 2000, population size S is 80, and ETC matrix and RCU array are randomly generated by the system. As the number of iterations increases, the scheduling scheme formed by MCGA and CGA is more obvious and close to the subtask execution cost optimization. Finally, the optimized scheme is basically formed. However, the scheduling scheme formed by TGA has no obvious optimization effect on the subtask execution cost. It is proved that the algorithm proposed in this paper can effectively optimize the task scheduling efficiency and improve the utilization of cloud computing resources at the same time, providing a feasible idea and method for task scheduling in the cloud computing environment.

Cloud computing technology and services has become an important issue in the recent years. Cloud Computing needs lot of attention, time and innovative concepts for the technology to mature over a period of time. Many organizations show interest in adopting cloud computing technology and services because of its socio economic and time factor. Cloud computing is nothing but virtual centralization of different computers where the software and memory space is provided by the vendor and the data is managed by them. This leaves the client/customer unaware of where the process is running or where the data is stored. Security of the data is highly dependent on the vendor who has to provide an assurance to the customer on security issues by making service level agreements. This paper focus on security issues, requirements for providing a secured data in cloud computing environment by giving a standard service oriented cloud computing Architecture and management tools that can be used by the organizations for authentication, confidentiality and integrity. Thus providing secured data access and transfer.

Arc4nix: A cross-platform geospatial analytical library for cluster and cloud computing

Virtualization is very important factor to reduce cost of data warehouse deployment. It can reduce cost as well as tremendous pressure of managing devices, storage servers, application models and man power. In current era, data warehouse is very effective concept that can make huge impact in organizational decision support system. Unlike database systems, data warehouse systems take large amount of time and cost to deploy and develop in-house system for an organization. This is the reason that people now think about cloud computing as a solution of the problem instead of implementing their own data warehouse system. This paper is about, how cloud computing environment can be established as an alternative of data warehouse system. It will also throw some light about better environment choice for the organizational need. Organizational data warehouse and EC2 (Elastic Cloud Computing) are discussed with different parameters like ROI, security, scalability, robustness of data, maintenance of system etc. Paper will help in comparative analysis of both the systems.

INTRODUCTION: Cloud services are becoming increasingly important as advanced technology changes. In these kinds of cases, the volume of work on the corresponding server in public real-time data virtualized environment can vary based on the user’s needs. Cloud computing is the most recent technology that provides on-demand access to computer resources without the user’s direct interference. Consequently, cloud-based businesses must be scalable to succeed.OBJECTIVES: The purpose of this research work is to describe a new virtual cluster architecture that allows cloud applications to scale dynamically within the virtualization of cloud computing scale Using auto-scaling, resources can be dynamically adjusted to meet multiple demands. METHODS: An auto-scaling algorithm based on the current implementation sessions will be initiated for automated provisioning and balancing of virtualized resources. The suggested methodology also considers the cost of energy.RESULTS: The proposed research work has shown that the suggested technique can handle sudden load demands while maintaining higher resource usage and lowering energy costs efficiently.CONCLUSION: Auto-scaling features are available in measures in order groups, allowing you to automatically add or remove instances from a managed instance group based on changes in load. This research work provides an analysis of auto-scaling mechanisms in cloud services that can be used to find the most efficient and optimal solution in practice and to manage cloud services efficiently.

Managing Cloud Computing Environment: Gaining Customer Trust with Security and Ethical Management