2,498 research outputs found
An analysis of software aging in cloud environment
Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps
Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges
Artificial General Intelligence (AGI), possessing the capacity to comprehend,
learn, and execute tasks with human cognitive abilities, engenders significant
anticipation and intrigue across scientific, commercial, and societal arenas.
This fascination extends particularly to the Internet of Things (IoT), a
landscape characterized by the interconnection of countless devices, sensors,
and systems, collectively gathering and sharing data to enable intelligent
decision-making and automation. This research embarks on an exploration of the
opportunities and challenges towards achieving AGI in the context of the IoT.
Specifically, it starts by outlining the fundamental principles of IoT and the
critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it
delves into AGI fundamentals, culminating in the formulation of a conceptual
framework for AGI's seamless integration within IoT. The application spectrum
for AGI-infused IoT is broad, encompassing domains ranging from smart grids,
residential environments, manufacturing, and transportation to environmental
monitoring, agriculture, healthcare, and education. However, adapting AGI to
resource-constrained IoT settings necessitates dedicated research efforts.
Furthermore, the paper addresses constraints imposed by limited computing
resources, intricacies associated with large-scale IoT communication, as well
as the critical concerns pertaining to security and privacy
AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0
The advancements in human-centered artificial intelligence (HCAI) systems for Industry 5.0 is a new phase of industrialization that places the worker at the center of the production process and uses new technologies to increase prosperity beyond jobs and growth. HCAI presents new objectives that were unreachable by either humans or machines alone, but this also comes with a new set of challenges. Our proposed method accomplishes this through the knowlEdge architecture, which enables human operators to implement AI solutions using a zero-touch framework. It relies on containerized AI model training and execution, supported by a robust data pipeline and rounded off with human feedback and evaluation interfaces. The result is a platform built from a number of components, spanning all major areas of the AI lifecycle. We outline both the architectural concepts and implementation guidelines and explain how they advance HCAI systems and Industry 5.0. In this article, we address the problems we encountered while implementing the ideas within the edge-to-cloud continuum. Further improvements to our approach may enhance the use of AI in Industry 5.0 and strengthen trust in AI systems
Modelling of the Electric Vehicle Charging Infrastructure as Cyber Physical Power Systems: A Review on Components, Standards, Vulnerabilities and Attacks
The increasing number of electric vehicles (EVs) has led to the growing need
to establish EV charging infrastructures (EVCIs) with fast charging
capabilities to reduce congestion at the EV charging stations (EVCS) and also
provide alternative solutions for EV owners without residential charging
facilities. The EV charging stations are broadly classified based on i) where
the charging equipment is located - on-board and off-board charging stations,
and ii) the type of current and power levels - AC and DC charging stations. The
DC charging stations are further classified into fast and extreme fast charging
stations. This article focuses mainly on several components that model the EVCI
as a cyberphysical system (CPS)
False Data Injection Attacks in Smart Grids: State of the Art and Way Forward
In the recent years cyberattacks to smart grids are becoming more frequent
Among the many malicious activities that can be launched against smart grids
False Data Injection FDI attacks have raised significant concerns from both
academia and industry FDI attacks can affect the internal state estimation
processcritical for smart grid monitoring and controlthus being able to bypass
conventional Bad Data Detection BDD methods Hence prompt detection and precise
localization of FDI attacks is becomming of paramount importance to ensure
smart grids security and safety Several papers recently started to study and
analyze this topic from different perspectives and address existing challenges
Datadriven techniques and mathematical modelings are the major ingredients of
the proposed approaches The primary objective of this work is to provide a
systematic review and insights into FDI attacks joint detection and
localization approaches considering that other surveys mainly concentrated on
the detection aspects without detailed coverage of localization aspects For
this purpose we select and inspect more than forty major research contributions
while conducting a detailed analysis of their methodology and objectives in
relation to the FDI attacks detection and localization We provide our key
findings of the identified papers according to different criteria such as
employed FDI attacks localization techniques utilized evaluation scenarios
investigated FDI attack types application scenarios adopted methodologies and
the use of additional data Finally we discuss open issues and future research
direction
Wind turbine drivetrains:State-of-the-art technologies and future development trends
This paper presents the state-of-the-art technologies and development trends of wind turbine drivetrains – the system that converts kinetic energy of the wind to electrical energy – in different stages of their life cycle: design, manufacturing, installation, operation, lifetime extension, decommissioning and recycling. Offshore development and digitalization are also a focal point in this study. Drivetrain in this context includes the whole power conversion system: main bearing, shafts, gearbox, generator and power converter. The main aim of this article is to review the drivetrain technology development as well as to identify future challenges and research gaps. The main challenges in drivetrain research identified in this paper include drivetrain dynamic responses in large or floating turbines, aerodynamic and farm control effects, use of rare-earth material in generators, improving reliability through prognostics, and use of advances in digitalization. These challenges illustrate the multidisciplinary aspect of wind turbine drivetrains, which emphasizes the need for more interdisciplinary research and collaboration
Smart Urban Water Networks
This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems
What Ukraine Taught NATO about Hybrid Warfare
Russia’s invasion of Ukraine in 2022 forced the United States and its NATO partners to be confronted with the impact of hybrid warfare far beyond the battlefield. Targeting Europe’s energy security, Russia’s malign influence campaigns and malicious cyber intrusions are affecting global gas prices, driving up food costs, disrupting supply chains and grids, and testing US and Allied military mobility. This study examines how hybrid warfare is being used by NATO’s adversaries, what vulnerabilities in energy security exist across the Alliance, and what mitigation strategies are available to the member states.
Cyberattacks targeting the renewable energy landscape during Europe’s green transition are increasing, making it urgent that new tools are developed to protect these emerging technologies. No less significant are the cyber and information operations targeting energy security in Eastern Europe as it seeks to become independent from Russia. Economic coercion is being used against Western and Central Europe to stop gas from flowing. China’s malign investments in Southern and Mediterranean Europe are enabling Beijing to control several NATO member states’ critical energy infrastructure at a critical moment in the global balance of power. What Ukraine Taught NATO about Hybrid Warfare will be an important reference for NATO officials and US installations operating in the European theater.https://press.armywarcollege.edu/monographs/1952/thumbnail.jp
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