Topics In Cloud Computing Research Articles

Cloud-based Cost Effective IIoT Model Towards Industry 5.0

Companies across industries increasingly depend upon cloud computing to manage their Industrial Internet of Things (IIoT) technology. Machines are connected over a network in the IIoT. Cloud computing plays an essential role by connecting people, devices, work processes, and buildings to deliver cloud services in industries. But cloud computing faces a problem with task scheduling, high latency delay, and memory management, affecting the overall cost of industries using cloud services. A major concern in the cloud computing field is task scheduling which is essential for achieving cost-effective execution and improving resource usage. It refers to assigning available resources to user tasks. This problem can be solved effectively by improving task execution and increasing the use of resources. The waiting time between a client’s sent request and a cloud service provider to give a response, known as latency, is another issue in cloud environments. In cloud computing, this delay can be significantly higher. As a result, users of various cloud services may incur increased expenses due to this delay. Finally, among the most significant topics in cloud computing is efficient memory management, which handles integrated data and optimizes memory management algorithms. This paper proposes a cloud model for IIoT, which provides task scheduling, helps reduce latency, and optimizes memory management. This proposed model helps to reduce the cost of using cloud computing in IIoT.

A Secure and Dynamic Fuzzy Multi-Keyword Ranked Search over Encrypted Cloud Data Without Access Pattern Leakage

Recent years, Searchable Encryption (SE) has become one of the hottest topics in cloud computing, because of its flexibility and availability. Most of existing SE schemes focus on the improvement of its efficiency, accuracy, and availability. However, the majority of them leak data access patterns due to their schemes constructions. In this paper, we present a secure symmetric searchable encryption scheme without access pattern leakage, based on Fu’s scheme. By constructing two cloud servers to replace the original server, our scheme protects data users from access pattern leakage.

The Rise of Data Capital

If exploited correctly, data can offer economic advantage, spur innovations, and generate revenue to enterprises. Cloud computing and big data are often intertwined. In fact, big data services is becoming a general phrase, with examples including cloud-based big data analytics and cloud-based big data storage services. This issue looks at various topics in cloud computing, from the emerging cloud of sensors, which builds on the Internet of Things and wireless sensors, to cloud brokering and its challenges when deploying in an enterprise, to a unique method to classify and grade security aspects.

클라우드 컴퓨팅 관련 논문의 서지정보 및 인용정보를 활용한 연구 동향 분석: 사회 네트워크 분석의 활용

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So into cloud computing is highly related to and combined with various relevant computing areas. To seek promising issues and topics in cloud computing, it is necessary to understand the trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among topics in cloud computing related areas, and highlight new potential topics. In addition, we visualize dynamic changes of topics relating to cloud computing using a proposed cloud computing research trend A trend map visualizes positions of topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the trend map. Based on the values of the two dimensions, the two dimensional space of a map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing trend maps make it possible to easily grasp the main trends in cloud computing, and to explain the evolution of topics. According to the results of an analysis of citation relationships, papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing trend maps. Moreover, this study revealed that current in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

Resource Allocation and Scheduling in Cloud Computing: Policy and Algorithm

ABSTRACTCloud computing is a new distributed commercial computing model that aims at providing computational resources or services to users over a network in a low-cost manner. Resource allocation and scheduling (RAS) is the key focus of cloud computing, and its policy and algorithm have a direct effect on cloud performance and cost. This paper presents five major topics in cloud computing, namely locality-aware task scheduling; reliability-aware scheduling; energy-aware RAS; Software as a Service (SaaS) layer RAS; and workflow scheduling. These five topics are then classified into three parts: performance-based RAS; cost-based RAS; and performance- and cost-based RAS. A number of existing RAS policies and algorithms are discussed in detail accordingly with regard to their given parameters. In addition, a comparative analysis of five identified problems with their representative algorithms is performed. Finally, some future research directions of cloud RAS are pointed out.

Summary of the 3rd ACM SIGOPS workshop on large-scale distributed systems and middleware (LADIS 2009)

The 3rd ACM/SIGOPS workshop on Large-Scale Distributed Systems and Middleware (LADIS’09) was held on October 10-11, 2009, in conjunction with the 22nd Symposium on Operating System Principles (SOSP) in Big Sky, Montana. The workshop was dedicated to hot topics in cloud computing. It lasted for one and a half days and featured keynote talks by industry leaders, peer-reviewed position papers from both academia and industry, and late-night break-out sessions fostering further discussion of important topics. LADIS’09 provided a forum for presenting and discussing cutting-edge ideas, and touched upon topics as diverse as distributed computing infrastructure, programming models, data storage, and security and privacy. This report summarizes key themes and conclusions from the workshop.