58,707 research outputs found
The Next Generation Cloud technologies: A Review On Distributed Cloud, Fog And Edge Computing and Their Opportunities and Challenges
Cloud computing is a 21st-century wonder with applications in nearly every industry imaginable. As a new technology, it has certain shortcomings. There are always attempts for improvements to combat those shortcomings. The next generation cloud technologies is believed to overcome these shortcomings. This research seeks to examine the few next generation cloud technologies, namely, distributed cloud, fog computing, edge computing. The distributed cloud improves worldwide service communications while also allowing for more responsive communications in individual regions. The distributed approach is used by cloud providers to allow lower latency and greater efficiency for cloud services. We find that there are few opportunities in Distributed Cloud such as, Improved security, IoT implementations, Faster content delivery, and cost efficiency. However, it poses some challenges such as data exposure to hackers when transferred from public networks. Fog computing, according to the findings, reduces the amount of time it takes, lowers operational costs, increases the level of security. However, one of the most difficult aspects of fog computing is the substantial reliance on data transit. Several opportunities of edge computing in various areas include Network optimization, Healthcare improvement, and Transportation. The popularity of some of the next generation cloud technologies has been strongly impacted by the growth of the internet of things and the unanticipated surge in data created by IoT-connected devices. It is possible to state that obstacles can be gradually overcome because the benefits of next generation cloud technologies enable solutions that meet a wide range of contemporary company requirements. The adoption of next generation cloud technologies might take some time as businesses consider the benefits and drawbacks, and the transition may be slow
Next Generation Cloud Computing: New Trends and Research Directions
The landscape of cloud computing has significantly changed over the last
decade. Not only have more providers and service offerings crowded the space,
but also cloud infrastructure that was traditionally limited to single provider
data centers is now evolving. In this paper, we firstly discuss the changing
cloud infrastructure and consider the use of infrastructure from multiple
providers and the benefit of decentralising computing away from data centers.
These trends have resulted in the need for a variety of new computing
architectures that will be offered by future cloud infrastructure. These
architectures are anticipated to impact areas, such as connecting people and
devices, data-intensive computing, the service space and self-learning systems.
Finally, we lay out a roadmap of challenges that will need to be addressed for
realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201
A gap analysis of Internet-of-Things platforms
We are experiencing an abundance of Internet-of-Things (IoT) middleware
solutions that provide connectivity for sensors and actuators to the Internet.
To gain a widespread adoption, these middleware solutions, referred to as
platforms, have to meet the expectations of different players in the IoT
ecosystem, including device providers, application developers, and end-users,
among others. In this article, we evaluate a representative sample of these
platforms, both proprietary and open-source, on the basis of their ability to
meet the expectations of different IoT users. The evaluation is thus more
focused on how ready and usable these platforms are for IoT ecosystem players,
rather than on the peculiarities of the underlying technological layers. The
evaluation is carried out as a gap analysis of the current IoT landscape with
respect to (i) the support for heterogeneous sensing and actuating
technologies, (ii) the data ownership and its implications for security and
privacy, (iii) data processing and data sharing capabilities, (iv) the support
offered to application developers, (v) the completeness of an IoT ecosystem,
and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims
to highlight the deficiencies of today's solutions to improve their integration
to tomorrow's ecosystems. In order to strengthen the finding of our analysis,
we conducted a survey among the partners of the Finnish IoT program, counting
over 350 experts, to evaluate the most critical issues for the development of
future IoT platforms. Based on the results of our analysis and our survey, we
conclude this article with a list of recommendations for extending these IoT
platforms in order to fill in the gaps.Comment: 15 pages, 4 figures, 3 tables, Accepted for publication in Computer
Communications, special issue on the Internet of Things: Research challenges
and solution
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