Automate Model Transformation From CIM to PIM up to PSM in Model-Driven Architecture

The CIM, PIM, and PSM models are the main levels of the MDA approach. Model transformation is an important step in the MDA process. Indeed, in MDA there are two elementary transformation kinds: CIM to PIM transformation and PIM to PSM transformation. However, most searches propose approaches transforming PIM to PSM, since there are multiple points in common between PIM and PSM. Nevertheless, transforming CIM to PIM is rarely addressed in research because these two levels are mainly different. However, there is not a synthesis work that makes it possible to carry out a model transformation from CIM to PIM towards PSM until obtaining the code. This synthesis methodology allows controlling models transformation from CIM to PIM to PSM, indeed, up to obtaining code according the MDA. This approach makes it possible to limit the intervention of computer scientists in the life cycle of software development. Indeed, this methodology allows modeling only CIM, the business process, and then obtains the source code through successive semi-automatic transformations.

Recent Advances Delivered in Mobile Cloud Computing's Security and Management Challenges

Mobile cloud computing provides an opportunity to restrict the usage of huge hardware infrastructure and to provide access to data, applications, and computational power from every place and in any time with the use of a mobile device. Furthermore, MCC offers a number of possibilities but additionally creates several challenges and issues that need to be addressed as well. Through this work, the authors try to define the most important issues and challenges in the field of MCC technology by illustrating the most significant works related to MCC during recent years. Regarding the huge benefits offered by the MCC technology, the authors try to achieve a more safe and trusted environment for MCC users in order to operate the functions and transfer, edit, and manage data and applications, proposing a new method based on the existing AES encryption algorithm, which is, according to the study, the most relevant encryption algorithm to a cloud environment. Concluding, the authors suggest as a future plan to focus on finding new ways to achieve a better integration MCC with other technologies.

Distributed Algorithms for Finding Meta-Paths of a Large Heterogeneous Information Network on Cloud

Meta-path is an important concept of heterogeneous information networks (HINs). Meta-paths were used in many tasks such as information retrieval, decision making, and product recommendation. Normally meta-paths were proposed by human experts. Recently, works on meta-path discovery have proposed in-memory solutions that fit in one computer. With large HINs, the whole HIN cannot be loaded in the memory. In this chapter, the authors proposed distributed algorithms to discover meta-paths of large HINs on cloud. They develop the distributed algorithms to discover the significant meta-path, maximal significant meta-path, and top-k meta-paths between two vertices of HIN. Calculation of the support of meta-paths or performing breadth first search can be computational costly in very large HINs. Conveniently, the distributed algorithms utilize the GraphFrames library of Apache Spark on cloud computing environment to efficiently query large HINs. The authors conduct the experiments on large DBLP dataset to prove the performance of our algorithms on cloud.

Security Threats and Recent Countermeasures in Cloud Computing

The cloud is an appealing innovation that has driven, in record time, an extraordinary interest. It is right now one of the busiest regions of research in IT, due to its adaptability, vigor, and capacity to altogether lessen the expenses of administrations to clients on the web. Additionally, cloud stores all client information in server farms dispersed the world over. In this manner, security has turned into a foremost worry that anticipates numerous organizations to receive its administrations. Clients should store their information, a few of which are ordinarily secret or individual; in this way, the authors are exceptionally mindful to information honesty and classification amid exchange to a cloud server. This exploration chapter plans to build up an investigation on the different security threats engaged with distributed computing along with their recent countermeasures.

A Computational Approach for Secure Cloud Computing Environments

The recent emergence of cloud computing has drastically altered everyone's perception of infrastructure architectures, software delivery, and development models. Projecting as an evolutionary step, cloud computing encompasses elements from grid computing, utility computing, and autonomic computing into an innovative deployment architecture. Cloud computing systems offer a lot of advantages like pay per use and rapid service provisioned on demand, while it suffers for some concerns specially security. In fact, a number of unchartered risks and challenges have been introduced from this new environment. This chapter explores the security issues in cloud computing systems and shows how to solve these problems using a quantitative security risk assessment model.

Secure Identity-Based Proxy Signature With Computational Diffie-Hellman for Cloud Data Management

This chapter explains a secure smart cloud framework based on identity-based proxy signature (IDBPS) scheme on Computational Diffie-Hellman (CD-H) assumption and AckIBE for data management. The objective of this chapter is to construct a secure hierarchical structure of homogeneous and heterogeneous cloud centers. This structure gives various types of computing services in the support of data analysis and information management. In this, the authors also introduce a security-related solution based on acknowledgment identity-based encryption (AckIBE), an IDBPS on computational Diffie-Hellman assumption, and identity-based proxy re-encryption to face critical security issues of the proposed framework.

Meta-Heuristic and Non-Meta-Heuristic Energy-Efficient Load Balancing Algorithms in Cloud Computing

The number of users of cloud computing services is drastically increasing, thereby increasing the size of data centers across the globe. In virtue of it, the consumption of power and energy is a major concern for system designers and developers. Their goal is now to develop power and energy-efficient products at the same time maintaining the quality and cost of products and services. For managing the power and efficiency, several aspects are taken into consideration in cloud computing paradigm. Load balancing, task scheduling, task migration, resource allocation are some of the techniques, which need to be efficiently employed to minimize the energy consumption. This chapter represents the detailed survey of the existing solutions and approaches for energy-efficient load balancing algorithms used in cloud environments. The research challenges as well as future research directions are also discussed in this chapter.

A Framework Strategy to Overcome Trust Issues on Cloud Computing Adoption in Higher Education

Cloud computing has the potential of adding strategic value to the higher education domain owing to exemplary growth in ubiquitous data and communication services ranging from student access to educational materials to developing teaching and research practices. Despite the wide adoption of CC in HEIs, there is a paucity of research that specifically addresses the issue of trust in cloud adoption in the UK HEI context, as well as identifying smarter and more efficient strategies to overcome the existing CC trust issue in this domain. The authors propose a five-stage strategic roadmap to address the trust issues impacting the uptake of cloud services in UK universities. They conclude that IT and management participation and support are the keys to the success of the strategic framework.

Cloud Computing Adoption

The purpose of this chapter is to develop a cloud computing adoption scale for Indian manufacturing, service, and process industries. The scale development procedure has been followed from the previous studies and is refined further for clear understanding to adopt easily. In the first step, the authors have conducted a qualitative study for item selection. The second step includes pilot testing of 110 responses for measurement scale purification, and finally, they are validating the scale with 660 sample respondents through convergent validity and discriminant validity. The initial result showed very poor threshold values for the items “top management support” and “marketplace establishment,” which have strong literature support. This measurement scale will help managers to evaluate the level of cloud adoption to increase the business performance. The study is a first attempt to develop a validated scale for cloud adoption that can be used in Indian industries.

Security for Cross-Tenant Access Control in Cloud Computing

Cloud computing is becoming a de facto standard for most of the emerging technology solutions. In a typical cloud environment, various tenants purchase the compute, storage resource, and would be sharing the resource with other tenants. Sharing of the resources among various tenants is not popular due to the security concerns. There are few solutions that try to solve the security problem of resource sharing among tenants. Having a trusted mediator between multiple tenants is one of the methods. Few research papers have been written, and this chapter attempts to enhance one of the published solutions: Cross-tenant access control model for cloud computing. Most of the existing research papers explore the theoretical way to solve the problem. This project develops a working prototype and proves how resource sharing can be achieved. This research develops the concept of resource sharing activation, where the resource can be shared with multiple cloud tenant and the deactivation where the shared resources can be removed from the shared resource pool.