Cloud Servers: Resource Optimization Using Different Energy Saving Techniques

Currently, researchers are working to contribute to the emerging fields of cloud computing, edge computing, and distributed systems. The major area of interest is to examine and understand their performance. The major globally leading companies, such as Google, Amazon, ONLIVE, Giaki, and eBay, are truly concerned about the impact of energy consumption. These cloud computing companies use huge data centers, consisting of virtual computers that are positioned worldwide and necessitate exceptionally high-power costs to preserve. The increased requirement for energy consumption in IT firms has posed many challenges for cloud computing companies pertinent to power expenses. Energy utilization is reliant upon numerous aspects, for example, the service level agreement, techniques for choosing the virtual machine, the applied optimization strategies and policies, and kinds of workload. The present paper tries to provide an answer to challenges related to energy-saving through the assistance of both dynamic voltage and frequency scaling techniques for gaming data centers. Also, to evaluate both the dynamic voltage and frequency scaling techniques compared to non-power-aware and static threshold detection techniques. The findings will facilitate service suppliers in how to encounter the quality of service and experience limitations by fulfilling the service level agreements. For this purpose, the CloudSim platform is applied for the application of a situation in which game traces are employed as a workload for analyzing the procedure. The findings evidenced that an assortment of good quality techniques can benefit gaming servers to conserve energy expenditures and sustain the best quality of service for consumers located universally. The originality of this research presents a prospect to examine which procedure performs good (for example, dynamic, static, or non-power aware). The findings validate that less energy is utilized by applying a dynamic voltage and frequency method along with fewer service level agreement violations, and better quality of service and experience, in contrast with static threshold consolidation or non-power aware technique

Dynamic Task Scheduling in Remote Sensing Data Acquisition from Open-Access Data Using CloudSim

With the rapid development of cloud computing and network technologies, large-scale remote sensing data collection tasks are receiving more interest from individuals and small and medium-sized enterprises. Large-scale remote sensing data collection has its challenges, including less available node resources, short collection time, and lower collection efficiency. Moreover, public remote data sources have restrictions on user settings, such as access to IP, frequency, and bandwidth. In order to satisfy users’ demand for accessing public remote sensing data collection nodes and effectively increase the data collection speed, this paper proposes a TSCD-TSA dynamic task scheduling algorithm that combines the BP neural network prediction algorithm with PSO-based task scheduling algorithms. Comparative experiments were carried out using the proposed task scheduling algorithms on an acquisition task using data from Sentinel2. The experimental results show that the MAX-MAX-PSO dynamic task scheduling algorithm has a smaller fitness value and a faster convergence speed

Cloud Computing in Digital and University Libraries

Libraries may soon be building and managing their own data centers. This model would let libraries maintain more control over the applications and data stores that contain sensitive, private information about patrons. Provisioning and maintenance of infrastructure for Web based digital library present several challenges. In this paper we discuss problems faced with digital library and development efforts to overcome that problem. Infrastructure virtualization and cloud computing are particularly attractive choices which is challenged by both growth in the size of the indexed document collection, new features and most prominently usage. With the purpose of applying Cloud Computing to university library, the paper describes the current status of user service models in university libraries. Then it proposed to improve current user service model with Cloud Computing. This paper explores some of the security issues surrounding data location, mobility and availability

Mobile App Acceleration via Fine-Grain Offloading to the Cloud

Mobile device hardware can limit the sophistication of mobile applications. One strategy for side-stepping these constraints is to opportunistically offload computations to the cloud, where more capable hardware can do the heavy lifting. We propose a platform that accomplishes this via compressive offloading, a novel application of compressive sensing in a distributed shared memory setting. Our prototype gives up to an order-of-magnitude acceleration and 60% longer battery life to the end user of an example handwriting recognition app. We argue that offloading is beneficial to both end users and cloud providers—the former experiences a performance boost and the latter receives a steady stream of small computations to fill periods of under-utilization. Such workloads, originating from ARM-based mobile devices, are especially well-suited for offloading to emerging ARM-based data centers.Engineering and Applied Science

Implementation of Intelligent Green Energy Management System

In this work, we mainly apply the cloud infrastructure (IaaS) and virtualization technology to provide the construction services of a green energy management system. First of all, we used MySQL Cluster database technology to build a data storage system which can solve the challenge of large demand. Digital electricity meter data and environmental information are collected efficiently and quickly in the proposed green energy management system. Next, a virtualized user-interface is provided by graphical presentation to facilitate data analysis. Finally, we control the electricity equipment to reduce Power Usage Effectiveness (PUE) and the overall power consumption target-based on this virtualized user-interface of the data analysis

Information technology governance maturity and technology innovation in higher education: factors in effectiveness

Prior research has explored many facets of innovation, provided models of governance maturity, and analyzed the impact of corporate decision-making on innovation. However, there is little research on IT governance maturity in higher education or on IT innovation in organizations outside of the IT industry. Findings from previous research were ambiguous regarding whether a mature IT governance process helps or hinders innovation. This study fills a gap in existing knowledge by reviewing the literature and examining the interaction of IT governance and information technology innovation at five major U.S. universities. It provides insights into the structures and processes necessary for IT governance to facilitate technology innovation and the factors required for effective IT governance in higher education. Highly effective IT governance processes focused on collaboration and communication were associated with greater integration of radical innovation into institutional processes than effective IT governance processes that focused primarily on the prioritization of large enterprise projects. Incremental technology innovations were pervasive among all schools studied. IT governance was found to be more effective under a delegated model of decision-making authority that empowers IT governance bodies than under a CIO-centric model. The inclusion of a faculty, students and business units in IT governance committees was associated with a stronger innovation culture

IGeneration: A Study in Challenge Based Learning at a Small Private University

Faculty-buy in is an essential component of successful technology integration processes at the Higher Education level. The goal of this case study was to assess the University faculty\u27s role in the utilization of Challenge Based Learning while teaching undergraduate students. Did the University have the faculty\u27s support and buy-in concerning the use of Challenge Based Learning as a campus-wide initiative? The perspectives of 16 full-time University faculty members enrolled in a Challenge Based Learning pilot study were explored at the beginning of the Challenge Based Learning pilot and then and were assessed again upon the completion of the pilot. The findings of the study were in favor of using Challenge Based Learning again