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)

An architecture for distributed ledger-based M2M auditing for Electric Autonomous Vehicles

Electric Autonomous Vehicles (EAVs) promise to be an effective way to solve transportation issues such as accidents, emissions and congestion, and aim at establishing the foundation of Machine-to-Machine (M2M) economy. For this to be possible, the market should be able to offer appropriate charging services without involving humans. The state-of-the-art mechanisms of charging and billing do not meet this requirement, and often impose service fees for value transactions that may also endanger users and their location privacy. This paper aims at filling this gap and envisions a new charging architecture and a billing framework for EAV which would enable M2M transactions via the use of Distributed Ledger Technology (DLT)

The Usage of Process Metrics to Analyze the Energy Efficiency of the Software Development Process and Product

The InnoMetrics project aims at building and validating a quantitative framework to assess and guide the software development teams using process metrics collected non-invasively throughout the life-cycle of software systems, from the initial concept to the deployment, execution, and maintenance taking into consideration energy concerns, which play a pivotal role in the success of applications and infrastructures. In this paper, we report the early experience we have in its development together with the data of developers' activities that we have obtained so far, including running processes and applications, user actions in browser or IDE, and associated energy consumption

A Machine to Machine framework for the charging of Electric Autonomous Vehicles

Electric Autonomous Vehicles (EAVs) have gained increasing attention of industry, governments and scientific communities concerned about issues related to classic transportation including accidents and casualties, gas emissions and air pollution, intensive traffic and city viability. One of the aspects, however, that prevent a broader adoption of this technology is the need for human interference to charge EAVs, which is still mostly manual and time-consuming. This study approaches such a problem by introducing the Inno-EAV, an open-source charging framework for EAVs that employs machine-to-machine (M2M) distributed communication. The idea behind M2M is to have networked devices that can interact, exchange information and perform actions without any manual assistance of humans. The advantages of the Inno-EAV include the automation of charging processes and the collection of relevant data that can support better decision making in the spheres of energy distribution. In this paper, we present the software design of the framework, the development process, the emphasis on the distributed architecture and the networked communication, and we discuss the back-end database that is used to store information about car owners, cars, and charging stations

Tailored performance dashboards—an evaluation of the state of the art

none3siContext. Tailoring mechanisms allow performance dashboards to vary their appearance as a response to changing requirements (e.g., adapting to multiple users or multiple domains). Objective. We analyze existing research on tailored dashboards and investigate different proposed approaches. Methodology. We performed a systematic literature review. Our search processes yielded a total of 1,764 papers, out of which we screened 1,243 and ultimately used six for data collection. Results. Tailored dashboards, while being introduced almost thirty years ago, did not receive much research attention. However, the area is expanding in recent years and we observed common patterns in novel tailoring mechanisms. Since none of the existing solutions have been running for extended periods of time in real-world scenarios, this lack of empirical data is a likely cause of vaguely described research designs and important practical issues being overlooked. Implications. Based on our findings we propose types of tailoring mechanisms taking into account the timing and nature of recommendations. This classification is grounded in empirical data and serves as a step ahead to a more unifying way of looking at tailoring capabilities in the context of dashboards. Finally, we outline a set of recommendations for future research, as well as a series of steps to follow to make studies more attractive to practitioners.openKruglov, Artem; Strugar, Dragos; Succi, GiancarloKruglov, Artem; Strugar, Dragos; Succi, Giancarl