The fast-paced development of power systems necessitates smart grids to facilitate real-time control and monitoring with bidirectional communication and electricity flows. Future smart grids are expected to have reliable, efficient, secured, and cost-effective power management with the implementation of distributed architecture. To focus on these requirements, we provide a comprehensive survey on different cloud computing applications for the smart grid architecture, in three different areas— energy management , information management , and security . In these areas, the utility of cloud computing applications is discussed, while giving directions on future opportunities for the development of the smart grid. We also highlight different challenges existing in the conventional smart grid (without cloud application) that can be overcome using cloud. In this survey, we present a synthesized overview of the current state of research on smart grid development. We also identify the current research problems in the areas of cloud-based energy management, information management, and security in smart grid.

Cloud Computing Applications for Smart Grid: A Survey

Fog computing (FC) and Internet of Everything (IoE) are two emerging technological paradigms that, to date, have been considered standing-alone. However, because of their complementary features, we expect that their integration can foster a number of computing and network-intensive pervasive applications under the incoming realm of the future Internet. Motivated by this consideration, the goal of this position paper is fivefold. First, we review the technological attributes and platforms proposed in the current literature for the standing-alone FC and IoE paradigms. Second, by leveraging some use cases as illustrative examples, we point out that the integration of the FC and IoE paradigms may give rise to opportunities for new applications in the realms of the IoE, Smart City, Industry 4.0, and Big Data Streaming, while introducing new open issues. Third, we propose a novel technological paradigm, the Fog of Everything (FoE) paradigm, that integrates FC and IoE and then we detail the main building blocks and services of the corresponding technological platform and protocol stack. Fourth, as a proof-of-concept, we present the simulated energy-delay performance of a small-scale FoE prototype, namely, the V-FoE prototype. Afterward, we compare the obtained performance with the corresponding one of a benchmark technological platform, e.g., the V-D2D one. It exploits only device-to-device links to establish inter-thing “ad hoc” communication. Last, we point out the position of the proposed FoE paradigm over a spectrum of seemingly related recent research projects.

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Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study

A cloud computing framework on demand side management game in smart energy hubs

For over forty years, relational databases have been the leading model for data storage, retrieval and management. However, due to increasing needs for scalability and performance, alternative systems have emerged, namely NoSQL technology. The rising interest in NoSQL technology, as well as the growth in the number of use case scenarios, over the last few years resulted in an increasing number of evaluations and comparisons among competing NoSQL technologies. While most research work mostly focuses on performance evaluation using standard benchmarks, it is important to notice that the architecture of real world systems is not only driven by performance requirements, but has to comprehensively include many other quality attribute requirements. Software quality attributes form the basis from which software engineers and architects develop software and make design decisions. Yet, there has been no quality attribute focused survey or classification of NoSQL databases where databases are compared with regards to their suitability for quality attributes common on the design of enterprise systems. To fill this gap, and aid software engineers and architects, in this article, we survey and create a concise and up-to-date comparison of NoSQL engines, identifying their most beneficial use case scenarios from the software engineer point of view and the quality attributes that each of them is most suited to.

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Choosing the right NoSQL database for the job: a quality attribute evaluation

Building energy management systems (BEMSs) monitor and control the heating ventilation and air conditioning (HVAC) of buildings in addition to many other building systems and utilities. Wireless sensor networks (WSNs) have become the integral part of BEMS at the initial implementation phase or latter when retro fitting is required to upgrade older buildings. WSN enabled BEMS, however, have several challenges which are managing data, controllers, actuators, intelligence, and power usage of wireless components (which might be battery powered). The wireless sensor nodes have limited processing power and memory for embedding intelligence in the sensor nodes. In this paper, we present a random neural network (RNN)-based smart controller on a Internet of Things (IoT) platform integrated with cloud processing for training the RNN which has been implemented and tested in an environment chamber. The IoT platform is modular and not limited to but has several sensors for measuring temperature, humidity, inlet air coming from the HVAC duct and PIR. The smart RNN controller has three main components: 1) base station; 2) sensor nodes; and 3) the cloud with embedded intelligence on each component for different tasks. This IoT platform is integrated with cloud processing for training the RNN. The RNN-based occupancy estimator is embedded in sensor node which estimates the number of occupants inside the room and sends this information to the base station. The base station is embedded with RNN models to control the HVAC on the basis of setpoints for heating and cooling. The HVAC of the environment chamber consumes 27.12% less energy with smart controller as compared to simple rule-based controllers. The occupancy estimation time is reduced by our proposed hybrid algorithm for occupancy estimation that combines RNN-based occupancy estimator with door sensor node (equipped with PIR and magnetic reed switch). The results show that accuracy of hybrid RNN occupancy estimator is 88%.

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Design and Implementation of a Cloud Enabled Random Neural Network-Based Decentralized Smart Controller With Intelligent Sensor Nodes for HVAC

This paper plays a role for electricity providers, who are actively developing digital meters and power management systems, and develops an energy management system by using service-oriented architecture. In addition to a power management system, the policy has changed from the traditional way in Taiwan by using energy-saving appliances. Therefore, the solution is to design devices that are more intelligent and energy saving at the same time. Moreover, computers can control the mechanism of the smart devices. The system uses a service-oriented architecture approach to construct services and utilize common virtualization technologies on cloud infrastructure. This work also applies distributed storage technologies to store and distribute data in order to make sure the system can meet massive loads of demands for services. Finally, we not only show provided services and hardware control in the implementation but also conduct performance tests of the distributed database.

Implementation of Smart Power Management and Service System on Cloud Computing

Currently, most health care systems used among divisions in medical centers still adopt the Excel file format for a variety of scales statistics, such as the clinical self-care ability scale for Functional Independence Measure. Although people can further analyze Excel files using other statistical analysis software, such as SAS, SPSS, and STATA, they cannot effectively share the archived data in Excel among divisions. We propose to do format conversion on these data and store them in a database. As the collection of Excel files cannot be shared with ease, we plan to use HBase, a non-relational database, to further integrate data. The purpose of this paper is to construct complete import tools and solutions based on HBase to facilitate easy access of data in HBase. Besides, a visual interface is also used to manage HBase to implement user friendly client connection tools for the HBase database.

Implementation of Data Transform Method into NoSQL Database for Healthcare Data

Cloud Services have been regarded as the significant trend of technical industries and applications after Web Services. The framework of cloud services contains the infrastructure, OS, virtual machines, platform, cloud web application services, and cloud devices. Due to the improvement of global network bandwidth over the past few years, people began to mutually share video files with larger space, in addition to the popularity of cloud computing and storage, video websites become fairly popular. The goal of this paper is to build video services on cloud IaaS environment, which integrates KVM and Open Nebula open sources to provide a cloud virtual environment for end users. This paper realizes video services that are easy for users to understand, access, and operate with it on cloud.

On Construction of Cloud IaaS Using KVM and Open Nebula for Video Services

In recent years, Cloud Computing and Virtualization has become one of the most popular computer science fields. Cloud Computing is enabled by the existing parallel and distributed technology, which provides computing, storage and software services to users. This paper focuses on the cloud storage virtualization technology to achieve high-availability services. We have designed and implemented a medical imaging system with a distributed file system. The technology of Distributed Replicated Block Device has been utilized to mirror an entire disk image. The experimental results show that the high reliability data storage clustering and fault tolerance capabilities can be achieved.

Wen-Hung Hsu

Papers

Implementation of Smart Power Management and Service System on Cloud Computing

Implementation of Data Transform Method into NoSQL Database for Healthcare Data

On Construction of Cloud IaaS Using KVM and Open Nebula for Video Services

A medical image file accessing system with virtualization fault tolerance on cloud