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Abstract and Figures

Edge Computing (EC) is an emerging technology that has made it possible to process the large volume of data generated by devices connected to the Internet, through the Internet of objects (IO). The article provides an introduction to EC and its definition. The integration of EC in those contexts would imply an optimisation of the processes that are normally executed in a cloud computing environment, bringing considerable advantages. The main contribution of EC is a better pre-processing of the data collected through devices before they are sent to a central server or the cloud.
An Edge Computing Tutorial
INÉS SITTÓN-CANDANEDO1* and JUAN MANUEL CORCHADO1,2,3,4
1BISITE Research Group, University of Salamanca, Salamanca, Spain.
2Air Institute, IoT Digital Innovation Hub, Salamanca, Spain.
3Department of Electronics, Information and Communication, Faculty of Engineering,
Osaka Institute of Technology, Osaka, Japan.
4Pusat Komputeran dan Informatik, Universiti Malaysia Kelantan, Kelantan, Malaysian.
Abstract
Edge Computing (EC) is an emerging technology that has made it
possible to process the large volume of data generated by devices
connected to the Internet, through the Internet of objects (IO). The
article provides an introduction to EC and its definition. The integration
of EC in those contexts would imply an optimisation of the processes
that are normally executed in a cloud computing environment, bringing
considerable advantages. The main contribution of EC is a better pre-
processing of the data collected through devices, before they are sent
to a central server or the cloud.
CONTACT Inés Sittón-Candanedo isittonc@usal.es BISITE Research Group, University of Salamanca, Salamanca, Spain.
© 2019 The Author(s). Published by Oriental Scientific Publishing Company
This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY).
Doi: http://dx.doi.org/10.13005/ojcst12.02.02
Article History
Received: 03 May 2019
Accepted: 22 May 2019
Keywords
Cloud Computing;
Edge Computing (EC);
Industry 4.0;
Internet of Things;
Reference Architecture.
Oriental Journal of Computer Science and Technology
www.computerscijournal.org
ISSN: 0974-6471, Vol. 12, No. (2) 2019, Pg. 34-38
Edge Computing
The Internet of Things is a network or an interconn-
ection of devices, sensors, or actuators that share
information through a unified protocol. The devices
use ubiquitous sensing, data analysis, information
representation and the same framework to achieve
this. A standard IoT network consists mainly of radio
frequency identification devices (RFID) and Wireless
Sensor Networks (WSN). This type of IoT network
have an important number of challenges that are
difficult to overcome in smart scenarios, such as:
logistic, home, city, Industry 4.0 or finance-realted
challenges.1-3
Until very recently, cloud computing was considered
the traditional approach to meeting the requirements
of the Internet of Things.1,4 Cloud computing is
defined as a model that allows for ubiquitous,
convenient, on-demand access to a shared set of
configuration computing resources (e.g., networks,
servers, storage, applications and services) that can
be quickly provisioned and released with minimal
35
SITTÓN-CANDANEDO & CORCHADO, Orient. J. Comp. Sci. & Technol., Vol. 12(2) 34-38 (2019)
interaction between the management center and
the service provider.5,6 The approach of using
cloud computing as a centralized server, generally
geographically distant, increases the frequency of
communications between the peripheral devices
used by users (tablets, computers, wristbands or
smartphones) becoming a limitation for applications
that require a real-time response.
This challenge has given rise to Edge Computing
(EC) as an emerging technology that allows
applications to run on network nodes.7 In EC, the
nodes can be centralized, distributed (core) or at the
end of the network, in this last case they are called
"edges", allowing for a more distributed processing
of all the information generated by the peripheral
devices. The widespread interest in this technology is
due to its association with the Internet of Things (IoT)
and its disruption in diferent scenarios, as a result
of the number of devices that can be connected
to the Internet, generating data and requiring
organizations to improve their productivity through
the administration and analysis of these data.8
Consequently, lines of research have emerged to
address edge computing, its challenges, oportunities
and application scenarios. EC is defined by several
authors as a set of devices, sensors, computer
resources and computers that produce and collect
data that are then sent to cloud centers. They
approach the concept of edge computing in terms of
its architecture, challenges, software technologies,
benefits and capabilities.9-11 Some of the most
commonly used edge computing concepts are
presented as follow:
Edge Computing is a technology that allows to
perform computation at the network edge so
that computing happens near data sources.
In Edge Computing, the end device not only
consumes data but also produces data.12
Edge Computing is a new paradigm in
which substantial computing and storage
resources, also referred to as cloudlets, micro
datacentres or fog nodes, are placed at the
Internet’s edge in close proximity of mobile
devices or sensors.13
Edge computing, refers to the enabling
technologies that allow for computation to
be performed at the network edge so that
computing happens near data sources. It
works on both downstream data on behalf of
cloud services and upstream data on behalf
of IoT services.14
In authors opinion, the most precise definition of
Edge Computing is that established by the Edge
Computing Consortium: Edge Computing is a
distributed open platform at the network edge,
close to the things or data sources, integrating the
capabilities of networks, storage, and applications.
By delivering edge intelligence services, Edge
Table 1: Difference between Edge and Cloud Computing16
Edge Cloud
Advantages · Real time response. · Scalable.
· Low Latency. · Big Data processing.
· Edge can work without · Unlimited storage capacity.
cloud and improve data security.
· The EC distributed structure
reduces: network traffic, storage
and bandwith cost.
Disadvantages · Storage capacity is limited · Response time is slow.
· EC needs proprietary networks. · High latency.
· IoT devices have a high · Cloud does not have an
power consumption. offline mode.
· Difficult to maintain the security of data.
· High costs of data storage and transmission.
36
SITTÓN-CANDANEDO & CORCHADO, Orient. J. Comp. Sci. & Technol., Vol. 12(2) 34-38 (2019)
Computing meets the key requirements of digitisation
for agile connectivity, real-time services, data
optimisation, application intelligence, security and
privacy protection.15 This definition establishes what
organizations currently demand: "platforms capable
of processing data in a secure and private manner,
providing answers to users in real time".
IoT applications and services must be able to support
heterogeneous devices that generate large volumes
of events and data. This feature makes it difficult
to find the development specifications that would
take advantage of all IoT potential. Considering
these concepts, Edge Computing increases IoT
performance with its distributed structure, likewise
network traffic can be significantly minimized; latency
transmission between the edge node the cloud and
end users can be improved; and therefore the real-
time response of IoT applications compared to cloud
and fog computing.
Table 1 resumes the main differences between EC
and Cloud Computing, dispite with all the advantages
mentioned above, it is important to clarify that the
process of increasing the processing or computing
capabilities of IoT devices located at the edge of the
network, using EC, does not replace the functions
performed by Cloud services. In this regard, is
important to note that cloud and edge computing
are very different technologies which complement
each other making it possible to deploy resources
with ubiquitous accessibility. However, even when
working together, they face the challenges of
mobility, scalability, reliability, security, privacy or
limited energy.
Figure 1 shows an edge computing ecosystem,
based on the work of W. Yu, F. Liang, X. He, Hatcher,
W G., Lu, C., Lin, J., Yang, X. (2017).16 It supports
how these two technologies complement each other
by integrating to more efficiently manage this flow
of information. In this sense, the devices need to
be managed and the data collected needs to be
analyzed and this requires a coordination of the
cloud with the network.
The Figure 1 components are described as follows:
Devices and sensors: responsibles to
generate and collect data. This group of
devices interact directly with the end user
(sensors, smartphones, tablets, smart
bracelets or laptops) and although some offer
services and answer in real time, most of
them have a limited capacity. Therefore, they
need to send requests to equipment located
on the Edge infrastructure.
Edge infrastructure: there are distributed data
centers to provide realtime data processing,
data visualization, analitycs, filtering,
optimizacion. They being located closer to
Fig. 1: Edge and Cloud Computing16
37
SITTÓN-CANDANEDO & CORCHADO, Orient. J. Comp. Sci. & Technol., Vol. 12(2) 34-38 (2019)
end users, they process, cache storage, and
perform calculations for a large volume of
data. With this capability, the edge reduces
data flow and costs of using cloud services,
as well as reducing end-user response time
and latency.
Cloud: It offers a greater density of compute,
storage, networking resources. Cloud servers
host applications for automatic learning, big
data analysis and business intelligence.
Finally, edge computing is a new paradigm that
promises to provide the required computing and
storage resources with a decrease in delays due to
its "proximity" to end users or devices. This tutorial
included a state of the art in the field of EC with the
objective of guiding readers towards current trends,
challenges and future research opportunities in the
area of edge computing.
Conclusion
This work is an edge computing state of the art
review, which is a disruptive technology driven by
the development of the Internet of Things and the
devices of our environment permanently connected
to the Internet. IoT devices generate data in real time
and constantly. The growing number of sensors,
connected machines, geographic heterogeneity for
data storage, requests for real-time response have
given rise to Edge Computing. The main advantages
of edge computing as following: real-time analysis of
data at the level of local devices and edge nodes and
not necessarily in the cloud; reduction of operating
costs, traffic and data transfer between the Edge and
the cloud; increase the performance of applications
for IoT scenarios by reducing network latency; and
finally allows integration with Blockchain technology
for security. As future lines of research, the authors
propose the design of an edge computing reference
architecture for IoT scenarios.
Acknowledgments
This research has been partially supported by
the project “Intelligent and sustainable mobility
supported by multi-agent systems and edge
computing” (Id. RTI2018-095390-B-C32). Inés
Sittón-Candanedo has been supported by
IFARHU – SENACYT scholarship program
(Government of Panama).
Conflict of Interest
We dont have conflict of interest including any
financial, personal or other relationships with other
people or organizations that can influence in our
work.
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... CC has provided an efficient and cost-effective way to store and process the data in a centralized cloud repository. However, the centralized storage structure is not able to keep up with the increasing demand for the real-time processing of data [9][10][11]. To address this increasing demand for minimizing the latency, edge computing can provide potential solutions by providing processing capabilities at the "edge of the network", thus minimizing the overhead caused by the speed of the data transformation and latencies [12][13][14]. ...
... In the EC architecture, we assist a part of the processing and storage resources to be at the edges, near sensors or mobile devices, allowing for "agile-connectivity," "real-time services," "data optimization," "security," and "privacy." Real-time response, low latency, reduction of network traffic, storage, energy consumption, and bandwidth cost are some of the advantages that can be pointed out to the EC paradigm [10]. The need to adopt a different paradigm from cloud computing to current and future IoT solutions is mainly due to three reasons: ...
... This can facilitate a near-real-time decision-making and delivery of the services. In addition, as the data captured by the sensors are handled on the edge only, a very short distance has to be travelled for the data to reach the edge nodes, which makes it faster, energy efficient, and cost-effective with very few chances of data losses [9][10][11][17][18][19][20]39]. ...
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