2,890 research outputs found
When Mobile Blockchain Meets Edge Computing
Blockchain, as the backbone technology of the current popular Bitcoin digital
currency, has become a promising decentralized data management framework.
Although blockchain has been widely adopted in many applications, e.g.,
finance, healthcare, and logistics, its application in mobile services is still
limited. This is due to the fact that blockchain users need to solve preset
proof-of-work puzzles to add new data, i.e., a block, to the blockchain.
Solving the proof-of-work, however, consumes substantial resources in terms of
CPU time and energy, which is not suitable for resource-limited mobile devices.
To facilitate blockchain applications in future mobile Internet of Things
systems, multiple access mobile edge computing appears to be an auspicious
solution to solve the proof-of-work puzzles for mobile users. We first
introduce a novel concept of edge computing for mobile blockchain. Then, we
introduce an economic approach for edge computing resource management.
Moreover, a prototype of mobile edge computing enabled blockchain systems is
presented with experimental results to justify the proposed concept.Comment: Accepted by IEEE Communications Magazin
On M2M Micropayments : A Case Study of Electric Autonomous Vehicles
The proliferation of electric vehicles has spurred the research interest in
technologies associated with it, for instance, batteries, and charging
mechanisms. Moreover, the recent advancements in autonomous cars also encourage
the enabling technologies to integrate and provide holistic applications. To
this end, one key requirement for electric vehicles is to have an efficient,
secure, and scalable infrastructure and framework for charging, billing, and
auditing. However, the current manual charging systems for EVs may not be
applicable to the autonomous cars that demand new, automatic, secure,
efficient, and scalable billing and auditing mechanism. Owing to the
distributed systems such as blockchain technology, in this paper, we propose a
new charging and billing mechanism for electric vehicles that charge their
batteries in a charging-on-the-move fashion. To meet the requirements of
billing in electric vehicles, we leverage distributed ledger technology (DLT),
a distributed peer-to-peer technology for micro-transactions. Our
proof-of-concept implementation of the billing framework demonstrates the
feasibility of such system in electric vehicles. It is also worth noting that
the solution can easily be extended to the electric autonomous cars (EACs)
Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches
Peer-to-peer (P2P) energy trading has emerged as a next-generation energy
management mechanism for the smart grid that enables each prosumer of the
network to participate in energy trading with one another and the grid. This
poses a significant challenge in terms of modeling the decision-making process
of each participant with conflicting interest and motivating prosumers to
participate in energy trading and to cooperate, if necessary, for achieving
different energy management goals. Therefore, such decision-making process
needs to be built on solid mathematical and signal processing tools that can
ensure an efficient operation of the smart grid. This paper provides an
overview of the use of game theoretic approaches for P2P energy trading as a
feasible and effective means of energy management. As such, we discuss various
games and auction theoretic approaches by following a systematic classification
to provide information on the importance of game theory for smart energy
research. Then, the paper focuses on the P2P energy trading describing its key
features and giving an introduction to an existing P2P testbed. Further, the
paper zooms into the detail of some specific game and auction theoretic models
that have recently been used in P2P energy trading and discusses some important
finding of these schemes.Comment: 38 pages, single column, double spac
Embedded Trusted Monitoring and Management Modules for Smart Solar Panels
This paper investigates developing a prototype of smart solar panels. This architecture consists of a panel monitoring module and the central management unit. The monitoring module is to be embedded inside each PV panel making it secure to transfer the trusted data via Wi-Fi to the central Management unit (which can accommodate an array of PV panels in an installation). This module is required for data storage and provides the ability to upload secure data to the cloud. This platform presents the ability to securely manage large numbers of rooftop solar panels in a distributed ledger by implementing block chain algorithm. For achieving this purpose, Module 400 is envisaged to be turned into a Blockchain node as it provides the infrastructure to implement this technology
Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems
Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions
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