A Secure Cloud Computing Based Framework for Big Data Information Management of Smart Grid

Abstract

Smart grid is a technological innovation that improves efficiency, reliability, economics, and sustainability of electricity services. It plays a crucial role in modern energy infrastructure. The main challenges of smart grids, however, are how to manage different types of front-end intelligent devices such as power assets and smart meters efficiently; and how to process a huge amount of data received from these devices. Cloud computing, a technology that provides computational resources on demands, is a good candidate to address these challenges since it has several good properties such as energy saving, cost saving, agility, scalability and flexibility. In this paper, we propose a secure cloud computing based framework for big data information management in smart grids, which we call "Smart-Frame." The main idea of our framework is to build a hierarchical structure of cloud computing centers to provide different types of computing services for information management and big data analysis. In addition to this structural framework, we present a security solution based on identity-based encryption, signature and proxy re-encryption to address critical security issues of the proposed framework.

Federated Cloud Analytics Frameworks in Next Generation Transport Oriented Smart Cities (TOSCs) - Applications, Challenges and Future Directions

“…To ensure real-time processing, analytics and decision making, the utilities demand efficient synchronization infrastructure. As estimation discovers, the transactions of merely two million smart metering populations generate more than 20GB of data every day [10]. Trends reflect that the vast scale roll out of smart transport system leveraged with Advance Metering Infrastructures (AMI), smart grid, smart charging stations and the innate smart xEVs is still in its infancy.…”

“…However, connecting such varying data sources directly to cloud data centers is inefficient and commercially impractical. The major issues with traditional centralized cloud models are associated with latency, network bandwidth, communication overheads, security and reliability [10].…”

Plug-in Electric Vehicle to Cloud Data Analytics for Charging Management

“…The prime ideology on which the model is established is remote accessibility and remote management. Plenty of claims and proposals are found in the literatures which are working independently in diverse domains such as security in information management of smart grids [4], smart grid dynamic energy management (DEM) [8], agent based simulation of electric vehicles fleet charging strategies [9] and many more. Fig.…”

“…The heterogeneous data generated from these devices roots the use of efficient data management techniques to deliver a consistent, reliable and real time operation of the massive vehicle fleet [3]. Cloud computing is an emerging approach, that is envisaged to provide a flexible, secure and cost effective platform for storage, as well as execution of the computing resources thereby offering a robust architecture destined to have a reliable and real time operation of engaged utilities [4]. Coupling the utilities with the cloud services ensure a naïve user to gain an anytime and anywhere access to the network as well as shared resources through smart applications at his disposal [5], [6].…”

“…as shown in Fig.1 But congregating these smart members into a single dais and further administering them is a bewildering task as galactic volume of data is generated in the course of installation of the framework that employs such entities. As estimation discovers, the transactions of only two million smart metering populations generate more than 20 GB of data every day [4], the real-time usage data size could certainly manifold. Trends reveal that the vast scale deployment of smart transport system leveraged with Advance Metering Infrastructures (AMI), smart grid, smart charging stations as well as intelligent xEVs is still in its infancy as the state of art management strategies break down to supervise such elements.…”