Integration of Cloud Computing with Internet of
Things: Challenges and Open Issues
Abstract— The Internet of Things (IoT) is becoming the next
Internet-related revolution. It allows billions of devices to be
connected and communicate with each other to share
information that improves the quality of our daily lives. On the
other hand, Cloud Computing provides on-demand, convenient
and scalable network access which makes it possible to share
computing resources; indeed, this, in turn, enables dynamic data
integration from various data sources. There are many issues
standing in the way of the successful implementation of both
Cloud and IoT. The integration of Cloud Computing with the
IoT is the most effective way on which to overcome these issues.
The vast number of resources available on the Cloud can be
extremely beneficial for the IoT, while the Cloud can gain more
publicity to improve its limitations with real world objects in a
more dynamic and distributed manner. This paper provides an
overview of the integration of the Cloud into the IoT by
highlighting the integration benefits and implementation
challenges. Discussion will also focus on the architecture of the
resultant Cloud-based IoT paradigm and its new applications
scenarios. Finally, open issues and future research directions are
also suggested.
Keywords— Cloud Computing, Internet of Things, Cloud based
IoT, Integration.
I. INTRODUCTION
It is important to explore the common features of the
technologies involved in the field of computing. Indeed, this is
certainly the case with Cloud Computing and the Internet of
Things (IoT) – two paradigms which share many common
features. The integration of these numerous concepts may
facilitate and improve these technologies. Cloud computing has
altered the way in which technologies can be accessed,
managed and delivered. It is widely agreed that Cloud
computing can be used for utility services in the future [1].
Although many consider Cloud computing to be a new
technology, it has, in actual fact, been involved in and
encompassed various technologies such as grid, utility
computing virtualisation, networking and software services [2],
[3]. Cloud computing provides services which make it possible
to share computing resources across the Internet. As such, it is
not surprising that the origins of Cloud technologies lie in grid,
utility computing virtualisation, networking and software
services, as well as distributed computing, and parallel
computing [4]. On the other hand, the IoT can be considered
both a dynamic and global networked infrastructure that
manages self-configuring objects in a highly intelligent way.
The IoT is moving towards a phase where all items around us
will be connected to the Internet and will have the ability to
interact with minimum human effort [5]. The IoT normally
includes a number of objects with limited storage and
computing capacity [6]. It could well be said that Cloud
computing and the IoT will be the future of the Internet and
next-generation technologies. However, Cloud services are
dependent on service providers which are extremely
interoperable, while IoT technologies are based on diversity
rather than interoperability [6].
This paper provides an overview of the integration of
Cloud Computing into the IoT; this involves an examination of
the benefits resulting from the integration process and the
implementation challenges encountered. Open issues and
research directions are also discussed. The remainder of the
paper is organised as follows: Section II provides the basic
concepts of Cloud computing, IoT, and Cloud-based IoT;
Section III discusses the benefits of integrating the IoT into the
Cloud; Could-based IoT Architecture is presented in section
IV; Section V illustrates different Cloud-based IoT applications
scenarios. Following this, the challenges facing Cloud-based
IoT integration and open research directions are discussed in
Section VI and Section VII respectively, before Section VIII
concludes the paper.
II. B
ASIC CONCEPTS
This section reviews the basic concepts of Cloud
Computing, the IoT, and Cloud-based IoT.
A. Cloud Computing
There exist a number of proposed definitions for Cloud
computing, although the most widely agreed upon seems be
that put forth by the National Institute of Standards and
Technology (NIST). Indeed, the NIST has defined Cloud
computing as "a model for enabling ubiquitous, convenient,
on-demand network access to a shared pool of configurable
computing resources (e.g., networks, servers, storage,
applications, and services) that can be rapidly provisioned and
released with minimal management effort or service provider
interaction" [7].
Hany F. Atlam
1, 2
, Ahmed Alenezi
1
, Abdulrahman Alharthi
1
, Robert J. Walters
1
, and Gary B. Wills
1
1
Electronic and Computer Science Dept., University of Southampton, Southampton, UK
2
Computer Science and Engineering Dept., Faculty of Electronic Engineering, Menoufia University, Menoufia, Egypt
{hfa1g15, aa4e15, aaa2g14, rjw5, gbw}@soton.ac.uk
2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom)
and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
978-1-5386-3066-2/17 $31.00 © 2017 IEEE
DOI 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.105
670
As stated in this definition, Cloud computing comprises
four types of deployment models, three different service
models, and five essential characteristics.
Cloud computing deployment models are most commonly
classified as belonging to the public Cloud, where resources
are made available to consumers over the Internet. Public
Clouds are generally owned by a profitable organisation (e.g.
Amazon EC2) [8]. Conversely, the infrastructure of a private
Cloud is commonly provided by a single organisation to serve
the particular purposes of its users [7]. The private Cloud offers
a secure environment and a higher level of control (Microsoft
Private Cloud). Hybrid Clouds are a mixture of private and
public Clouds. This choice is provided for consumers as it
makes it possible to overcome some of the limitations of each
model [9]. In contrast, a community Cloud is a Cloud
infrastructure which is delivered to a group of users by a
number of organisations which share the same need [10].
In order to allow consumers to choose the service that suits
them, services in Cloud computing are provided at three
different levels, namely: the Software as a Service (SaaS)
model, where software is delivered through the Internet to
users (e.g. GoogleApps) [2]; the Platform as a Service (PaaS)
model, which offers a higher level of integrated environment
that can build, test, and deploy specific software (e.g.
Microsoft Azure) [11]; and finally, with the Infrastructure as a
Service (IaaS) model, infrastructure such as storage, hardware
and servers are delivered as a service (e.g. Amazon Web
Services) [7].
B. Internet of Things
The IoT represents a modern approach where boundaries
between real and digital domains are progressively eliminated
by consistently changing every physical device to a smart
alternative ready to provide smart services. All things in the
IoT (smart devices, sensors, etc.) have their own identity. They
are combined to form the communication network and will
become actively participating objects [6]. These objects
include not only daily usable electronic devices, but also things
like food, clothing, materials, parts, and subassemblies;
commodities and luxury items; monuments and landmarks; and
various forms of commerce and culture [7]. In addition, these
objects are able to create requests and alter their states. Thus,
all IoT devices can be monitored, tracked and counted, which
significantly decreases waste, loss, and cost [8].
The concept of the IoT was first mentioned by Kevin
Ashton in 1999 [9], [10], when he stated that “The Internet of
Things has the potential to change the world, just as the
Internet did. Maybe even more so”. Later, the IoT was formally
presented by the International Telecommunication Union
(ITU) in 2005 [11]. A great many definitions of the IoT have
been put forth by numerous organisations and researchers.
According to the ITU (2012), the IoT is “a global
infrastructure for the Information Society, enabling advanced
services by interconnecting (physical and virtual) things based
on, existing and evolving, interoperable information and
communication technologies” [12]. The IoT introduces a
variety of opportunities and applications. However, it faces
many challenges which could potentially hinder its successful
implementation, such as data storage, heterogeneous resource-
constrained, scalability, Things, variable geospatial
deployment, and energy efficiency [13].
C. Cloud-Based Internet of Things
The IoT and Cloud computing are both rapidly developing
services, and have their own unique characteristics. On the one
hand, the IoT approach is based on smart devices which
intercommunicate in a global network and dynamic
infrastructure. It enables ubiquitous computing scenarios. The
IoT is typically characterised by widely-distributed devices
with limited processing capabilities and storage. These devices
encounter issues regarding performance, reliability, privacy,
and security [14]. On the other hand, Cloud computing
comprises a massive network with unlimited storage
capabilities and computation power. Furthermore, it provides a
flexible, robust environment which allows for dynamic data
integration from various data sources [8]. Cloud computing has
partially resolved most of the IoT issues. Indeed, the IoT and
Cloud are two comparatively challenging technologies, and are
being combined in order to change the current and future
environment of internetworking services [6].
The Cloud-based Internet of Things is a platform which
allows for the smart usage of applications, information, and
infrastructure in a cost-effective way. While the IoT and Cloud
computing are different from each other, their features are
almost complementary, as shown in TABLE 1. This
complementarity is the primary reason why many researchers
have proposed their integration [14].
TABLE
1.
COMPARISON OF THE
I
O
T
WITH
C
LOUD COMPUTING
Items IoT Cloud Computing
Characteristics IoT is pervasive (things
are everywhere).
These are real world
objects.
Cloud is ubiquitous
(resources are available
from everywhere).
These are virtual resources.
Processing
capabilities
Limited computational
capabilities.
Virtually unlimited
computational capabilities.
Storage
capabilities
Limited storage or no
storage capabilities.
Unlimited storage
capabilities.
Connectivity It uses the Internet as a
point of convergence.
It uses the Internet for
service delivery.
Big data It is a source of big data. It is a means by which to
manage big data.
III. BENEFITS OF INTEGRATING IOT WITH CLOUD
Since the IoT suffers from limited capabilities in terms of
processing power and storage, it must also contend with issues
such as performance, security, privacy, reliability. The
integration of the IoT into the Cloud is certainly the best way to
overcome most of these issues. The Cloud can even benefit
from the IoT by expanding its limits with real world objects in
a more dynamic and distributed way, and providing new
services for billions of devices in different real life scenarios
[6], [14]. In addition, the Cloud provides simplicity of use and
reduces the cost of the usage of applications and services for
end-users. The Cloud also simplifies the flow of the IoT data
gathering and processing, and provides quick, low-cost
installation and integration for complex data processing and
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deployment [15]. The benefits of integrating IoT into Cloud are
discussed in this section as follows.
1. Communication
Application and data sharing are two significant features of
the Cloud-based IoT paradigm. Ubiquitous applications can be
transmitted through the IoT, whilst automation can be utilised
to facilitate low-cost data distribution and collection. The
Cloud is an effective and economical solution which can be
used to connect, manage, and track anything by using built-in
apps and customised portals [7]. The availability of fast
systems facilitates dynamic monitoring and remote objects
control, as well as data real-time access. It is worth declaring
that, although the Cloud can greatly develop and facilitate the
IoT interconnection, it still has weaknesses in certain areas.
Thus, practical restrictions can appear when an enormous
amount of data needs to be transferred from the Internet to the
Cloud [7], [16].
2. Storage
As the IoT can be used on billions of devices, it comprises
a huge number of information sources, which generate an
enormous amount of semi-structured or non-structured data
[17]. This is known as Big Data, and has three characteristics
[4]: variety (e.g. data types), velocity (e.g. data generation
frequency), and volume (e.g. data size). The Cloud is
considered to be one of the most cost-effective and suitable
solutions when it comes to dealing with the enormous amount
of data created by the IoT. Moreover, it produces new chances
for data integration, aggregation, and sharing with third parties
[18].
3. Processing capabilities
IoT devices are characterised by limited processing
capabilities which prevent on-site and complex data
processing. Instead, gathered data is transferred to nodes that
have high capabilities; indeed, it is here that aggregation and
processing are accomplished. However, achieving scalability
remains a challenge without an appropriate underlying
infrastructure. Offering a solution, the Cloud provides
unlimited virtual processing capabilities and an on-demand
usage model [18]. Predictive algorithms and data-driven
decisions making can be integrated into the IoT in order to
increase revenue and reduce risks at a lower cost [6].
4. Scope
With billions of users communicating with one another
together and a variety of information being collected, the world
is quickly moving towards the Internet of Everything (IoE)
realm - a network of networks with billions of things that
generate new chances and risks [18]. The Cloud-based IoT
approach provides new applications and services based on the
expansion of the Cloud through the IoT objects, which in turn
allows the Cloud to work with a number of new real world
scenarios, and leads to the emergence of new services [22].
5. New abilities
The IoT is characterised by the heterogeneity of its devices,
protocols, and technologies. Hence, reliability, scalability,
interoperability, security, availability and efficiency can be
very hard to achieve. Integrating IoT into the Cloud resolves
most of these issues [6]. It provides other features such as ease-
of-use and ease-of-access, with low deployment costs [19],
[22].
6. New Models
Cloud-based IoT integration empowers new scenarios for
smart objects, applications, and services [11], [20]. Some of the
new models are listed as follows:
• SaaS (Sensing as a Service) [11], which allows access
to sensor data;
• EaaS (Ethernet as a Service) [23], the main role of
which is to provide ubiquitous connectivity to control
remote devices;
• SAaaS (Sensing and Actuation as a Service) [11],
which provides control logics automatically.
• IPMaaS (Identity and Policy Management as a Service)
[23], which provides access to policy and identity
management.
• DBaaS (Database as a Service) [23], which provides
ubiquitous database management;
• SEaaS (Sensor Event as a Service) [11], which
dispatches messaging services that are generated by
sensor events;
• SenaaS (Sensor as a Service) [23], which provides
management for remote sensors;
• DaaS (Data as a Service) [23], which provides
ubiquitous access to any type of data.
IV. C
LOUD-BASED IOT ARCHITECTURE
According to a number of previous studies, the well-known
IoT architecture is typically divided into three different layers:
application, perception and network layer. Most assume that
the network layer is the Cloud layer, which realises the Cloud-
based IoT architecture, as depicted in Fig. 1.
Fig. 1. Cloud-based IoT architecture [1].
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The perception layer is used to identify objects and gather
data, which is collected from the surrounding environment. In
contrast, the main objective of the network layer is to transfer
the collected data to the Internet/Cloud. Finally, the application
layer provides the interface to different services [20].
V. C
LOUD-BASED IOT APPLICATIONS
The Cloud-based IoT approach has introduced a number of
applications and smart services, which have affected end users’
daily lives. TABLE 2 presents a brief discussion of certain
applications which have been improved by the Cloud-based
IoT paradigm [4], [24 – 27].
TABLE
2.
C
LOUD
-
BASED
I
O
T
APPLICATIONS
Application
Field
Description
Healthcare
Cloud-based IoT has brought many benefits and
opportunities to the field of healthcare. It can
clearly develop and improve healthcare services
and keep the field innovative (e.g. intelligent
drug/medicine control, hospital management).
Smart Cities
A middleware for future smart cities can be
provided through the IoT, attaining data from
sensing infrastructure, IoT technologies and placing
information in a consistent manner. This will lead
to the generation of services that can communicate
with the surrounding environments (e.g. Smart
streetlights, Bigbelly, ShotSpotte).
Smart Homes
A large number of Cloud-based IoT applications
have enabled the automation of home activities,
where the adoption of various embedded devices
and Cloud computing has empowered the
automation of in-house activities (e.g. home
security control, smart metering, energy saving).
Video
surveillance
By embracing Cloud-based IoT, intelligent video
surveillance will make it possible to manage, store
and process video content from video sensors
easily and efficiently; this will also make it possible
to extract information from scenes automatically. It
has become one of the supreme tools for many
security-related applications (e.g. Wireless CCTV
Cameras, Movement detection system).
Automotive and
Smart Mobility
The integration of Cloud computing into The
Global Positioning System (GPS) and other
transportation technologies represents a promising
opportunity to solve many of the existing
challenges (e.g. traffic state prediction &
notification, remote vehicles).
Smart energy and
smart grid
Cloud computing and the IoT can work together
effectively to provide consumers with smart
management of energy consumption (e.g. smart
meters, smart appliances, renewable energy
resources).
Smart logistics
It allows for, and eases, the automated management
of goods flow between producers and consumers,
while simultaneously enabling the tracking of
goods in transit (e.g. logistics industry, tracking
shipments).
Environmental
monitoring
By combining the Cloud with the IoT, a high-speed
information system can be provided which will link
the entity that monitors wide-area environments
and sensors that have been properly deployed in the
area (e.g. pollution source monitoring, water
quality monitoring, air quality monitoring).
VI. CHALLENGES FACING CLOUD-BASED IOT INTEGRATION
There are many challenges which could potentially prevent
the successful integration of the Cloud-based IoT paradigm.
These challenges include:
1. Security and privacy.
Cloud-based IoT makes it possible to transport data from
the real world to the Cloud. Indeed, one particularly important
issues which has not yet been resolved is how to provide
appropriate authorisation rules and policies while ensuring that
only authorised users have access to the sensitive data; this is
crucial when it comes to preserving users’ privacy, and
particularly when data integrity must be guaranteed [18]. In
addition, when critical IoT applications move into the Cloud,
issues arise because of the lack of trust in the service provider,
information regarding service level agreements (SLAs), and
the physical location of data [25], [27]. Sensitive information
leakage can also occur due to the multi-tenancy. Moreover,
public key cryptography cannot be applied to all layers because
of the processing power constraints imposed by IoT objects
[18]. New challenges also require specific attention; for
example, the distributed system is exposed to number of
possible attacks, such as SQL injection, session riding, cross-
site scripting, and side-channel. Moreover, important
vulnerabilities, including session hijacking and virtual machine
escape are also problematic [18], [29].
2. Heterogeneity
One particularly important challenge faced by the Cloud-
based IoT approach is related to the extensive heterogeneity of
devices, platforms, operating systems, and services that exist
and might be used for new or developed applications. Cloud
platforms suffer from heterogeneity issues; for instance, Cloud
services generally come with proprietary interfaces, thus
allowing for resource integration based on specific providers
[18]. In addition, the heterogeneity challenge can be
exacerbated when end-users adopt multi-Cloud approaches,
and thus services will depend on multiple providers to improve
application performance and resilience [30].
3. Big data
With many predicting that Big Data will reach 50 billion
IoT devices by 2020, it is important to pay more attention to
the transportation, access, storage and processing of the
enormous amount of data which will be produced. Indeed,
given recent technological developments, it is clear that the IoT
will be one of the core sources of big data, and that the Cloud
can facilitate the storage of this data for a long period of time,
in addition to subjecting it to complex analysis [4]. Handling
the huge amount of data produced is a significant issue, as the
application’s whole performance is heavily reliant on the
properties of this data management service. Finding a perfect
data management solution which will allow the Cloud to
manage massive amounts of data is still a big issue [31].
Furthermore, data integrity is a vital element, not only because
of its effect on the service’s quality, but also because of
security and privacy issues, the majority of which relate to
outsourced data [18].
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4. Performance
Transferring the huge amount of data created from IoT
devices to the Cloud requires high bandwidth. As a result, the
key issue is obtaining adequate network performance in order
to transfer data to Cloud environments; indeed, this is because
broadband growth is not keeping pace with storage and
computation evolution [18]. In a number of scenarios, services
and data provision should be achieved with high reactivity
[29]. This is because timeliness might be affected by
unpredictable matters and real-time applications are very
sensitive to performance efficiency [18].
5. Legal aspects
Legal aspects have been very significant in recent research
concerning certain applications. For instance, service providers
must adapt to various international regulations. On the other
hand, users should give donations in order to contribute to data
collection [32].
6. Monitoring
Monitoring is a primary action in Cloud Computing when it
comes to performance, managing resources, capacity planning,
security, SLAs, and for troubleshooting. As a result, the Cloud-
based IoT approach inherits the same monitoring demands
from the Cloud, although there are still some related challenges
that are impacted by velocity, volume, and variety
characteristics of the IoT [4], [31].
7. Large scale
The Cloud-based IoT paradigm makes it possible to design
new applications that aim to integrate and analyse data coming
from the real world into IoT objects. This requires interacting
with billions of devices which are distributed throughout many
areas [28]. The large scale of the resulting systems raises many
new issues that are difficult to overcome. For instance,
achieving computational capability and storage capacity
requirements is becoming difficult. Moreover, the monitoring
process has made the distribution of the IoT devices more
difficult, as IoT devices have to face connectivity issues and
latency dynamics [18].
VII. O
PEN ISSUES AND RESEARCH DIRECTIONS
This section will address some of the open issues and future
research directions related to Cloud-based IoT, and which still
require more research efforts. These issues include:
1. Standardisation
Many studies have highlighted the issues of lack of
standards, which is considered critical in relation to the Cloud-
based IoT paradigm [18]. Although a number of proposed
standardisations have been put forth by the scientific society
for the deployment of IoT and Cloud approaches, it is obvious
that architectures, standard protocols, and APIs are required to
allow for interconnection between heterogeneous smart things
and the generation of new services, which make up the Cloud-
based IoT paradigm [4], [6], [18].
2. Fog Computing
Fog computing is a model which extends Cloud computing
services to the edge of the network. Similar to the Cloud, Fog
supply communicates application services to users. Fog can
essentially be considered an extension of Cloud Computing
which acts as an intermediate between the edge of the network
and the Cloud; indeed, it works with latency-sensitive
applications that require other nodes to satisfy their delay
requirements [6]. Although storage, computing, and
networking are the main resources of both Fog and the Cloud,
the Fog has certain features, such as location awareness and
edge location, that provide geographical distribution, and low
latency; moreover, there are a large nodes; this is in contrast
with the Cloud, which is supported for real-time interaction
and mobility [4], [6].
3. Cloud Capabilities
As in any networked environment, security is considered to
be one of the main issues of the Cloud-based IoT paradigm.
There are more chances of attacks on both the IoT and the
Cloud side. In the IoT context, data integrity, confidentiality
and authenticity can be guaranteed by encryption. However,
insider attacks cannot be resolved and it is also hard to use the
IoT on devices with limited capabilities [4], [18].
4. SLA enforcement
Cloud-based IoT users need created data to be conveyed
and processed based on application-dependent limitations,
which can be tough in some cases. Ensuring a specific Quality
of Service (QoS) level regarding Cloud resources by depending
on a single provider raises many issues. Thus, multiple Cloud
providers may be required to avoid SLA violations. However,
dynamically choosing the most appropriate mixture of Cloud
providers still represents an open issue due to time, costs, and
heterogeneity of QoS management support [18], [31].
5. Big data
In the previous section, we discussed Big Data as a critical
challenge that is tightly coupled with the Cloud-based IoT
paradigm. Although a number of contributions have been
proposed, Big Data is still considered a critical open issue, and
one in need of more research. The Cloud-based IoT approach
involves the management and processing of huge amounts of
data stemming from various locations and from heterogeneous
sources; indeed, in the Cloud-based IoT, many applications
need complicated tasks to be performed in real-time [18], [28].
6. Energy efficiency
Recent Cloud-based IoT applications include frequent data
that is transmitted from IoT objects to the Cloud, which
quickly consumes the node energy. Thus, generating efficient
energy when it comes to data processing and transmission
remains a significant open issue [4]. Several directions have
been suggested to overcome this issue, such as compression
technologies, efficient data transmission; and data caching
techniques for reusing collected data with time-insensitive
application [18], [31].
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![Fig. 1. Cloud-based IoT architecture [1].](/figures/fig-1-cloud-based-iot-architecture-1-tihzynw7.webp)
