3,078 research outputs found
Special issue on Big Data and digital transformation
[Excerpt] The world we live in is more and more of a digital nature. Nowadays, more than ever, we are witnessing a fundamental trend - technological innovations are continuously appearing and rapidly made available to everyone. These have a huge impact on people, who, for the most, easily adhere to and use them, not only in their personal lives, but also at work. At the enterprise level, easy access to global markets and new ways of working and conducting business becomes possible due to technological innovations, leading to
innovative business models. Similarly, governments, municipalities and public organizations are developing new ways to reach the citizens and interact with them, in manners that were impossible to foresee a
few years ago. All these changes, fueled by the continuous stream of technological innovations, are widely
known as Digital Transformation. [...]- (undefined
A manifesto for future generation cloud computing: research directions for the next decade
The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to address issues such as scalability, elasticity, reliability, security, sustainability, and application models. The proposed manifesto addresses them by identifying the major open challenges in Cloud computing, emerging trends, and impact areas. It then offers research directions for the next decade, thus helping in the realisation of Future Generation Cloud Computing
A Decade of Research in Fog computing: Relevance, Challenges, and Future Directions
Recent developments in the Internet of Things (IoT) and real-time
applications, have led to the unprecedented growth in the connected devices and
their generated data. Traditionally, this sensor data is transferred and
processed at the cloud, and the control signals are sent back to the relevant
actuators, as part of the IoT applications. This cloud-centric IoT model,
resulted in increased latencies and network load, and compromised privacy. To
address these problems, Fog Computing was coined by Cisco in 2012, a decade
ago, which utilizes proximal computational resources for processing the sensor
data. Ever since its proposal, fog computing has attracted significant
attention and the research fraternity focused at addressing different
challenges such as fog frameworks, simulators, resource management, placement
strategies, quality of service aspects, fog economics etc. However, after a
decade of research, we still do not see large-scale deployments of
public/private fog networks, which can be utilized in realizing interesting IoT
applications. In the literature, we only see pilot case studies and small-scale
testbeds, and utilization of simulators for demonstrating scale of the
specified models addressing the respective technical challenges. There are
several reasons for this, and most importantly, fog computing did not present a
clear business case for the companies and participating individuals yet. This
paper summarizes the technical, non-functional and economic challenges, which
have been posing hurdles in adopting fog computing, by consolidating them
across different clusters. The paper also summarizes the relevant academic and
industrial contributions in addressing these challenges and provides future
research directions in realizing real-time fog computing applications, also
considering the emerging trends such as federated learning and quantum
computing.Comment: Accepted for publication at Wiley Software: Practice and Experience
journa
Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordCritical infrastructure systems are vital to underpin
the functioning of a society and economy. Due to ever-increasing
number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data generated and collected,
security and scalability are becoming burning concerns for
critical infrastructures in industry 4.0. The blockchain technology
is essentially a distributed and secure ledger that records all
the transactions into a hierarchically expanding chain of blocks.
Edge computing brings the cloud capabilities closer to the
computation tasks. The convergence of blockchain and edge
computing paradigms can overcome the existing security and
scalability issues. In this paper, we first introduce the IoT/IIoT
critical infrastructure in industry 4.0, and then we briefly present
the blockchain and edge computing paradigms. After that, we
show how the convergence of these two paradigms can enable
secure and scalable critical infrastructures. Then, we provide a
survey on state-of-the-art for security and privacy, and scalability
of IoT/IIoT critical infrastructures. A list of potential research
challenges and open issues in this area is also provided, which
can be used as useful resources to guide future research.Engineering and Physical Sciences Research Council (EPSRC
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