Big Data Challenges in IoT and Cloud: A Comprehensive Analysis

This report delves into the challenges of Big Data (BD) within the context of the Internet of Things (IoT) and cloud computing. It explores the significant advantages BD offers for data collection, integration, and transformation, particularly from IoT devices and databases. The paper identifies key technical and non-technical challenges, with a focus on data analysis, security, and privacy. It examines the relationships between BD, IoT, and cloud, including the roles of SaaS, PaaS, and IaaS. The report investigates data collection techniques, security management, and the importance of fog computing for managing data flow and mitigating security risks. It also discusses the impact of BD on various fields like sports and business intelligence, along with the importance of data analysis for improving decision-making. The report concludes by emphasizing the need for cybersecurity measures and offers insights into future research directions, particularly in addressing integration and security challenges within IoT and cloud environments.

Running head: Big data challenges in IoT and cloud 0
Big data Challenges in IoT and Cloud
Paper
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Big data challenges in IoT and cloud 1
Big data challenges in IoT and cloud
Student Name – Student ID
Masters in IT – Networking
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ABSTRACT – Big data (BD) is helpful in data collection, integration, and transformation from the various
devices, such as IoT devices, databases, and many other things. In addition, IoT and cloud provide various
advantages in the management of business processes and data analytics. This paper will discuss about the
challenges of big data because of cloud and IoT. This paper will focus on the challenges of BD in collaboration
with the cloud and IoT. In addition, integration between cloud and BD is necessary to improve the
performance of data analytics and business functions. It is important to know about the challenges of BD in
cloud and IoT to implement it in a proper manner. This paper will mainly focus on the connection between
BD and IoT devices and cloud-based services. There are some technical and non-technical issues in the
integration. The main challenge of BD is data analysis, which can solve using various techniques of cloud
computing and cognitive algorithms as well as Artificial Intelligence (AI), machine learning, and other
systems. This paper will focus on the security and privacy challenges in front of BD in IoT and cloud. There
are some important benefits of BD will provide in this paper, which are helpful in the data analysis processes.
BD has provided data collection and management to the particular organization. Therefore, it is necessary to
manage the data and information in a proper way. It will improve the performance of the overall system. The
BD has faced challenges in the IoT applications and its integration. This paper will include different
platforms of data collection and management, which are SQL/NoSQL, OLTP, OLAP, and persistent data. It
will provide better results to improve the data analysis process of BD in IoT and cloud. Moreover, security
and privacy issues will solved in a proper manner using this approach of data collection and integration.
Keywords— big data, IoT, cloud, etc.
1. INTRODUCTION
BD provides many advantages to many industries. It
faces various challenges in Internet-of-Things (IoT), and
cloud.in addition, there are various benefits of the IoT
and Cloud Computing (CC) in the business processes of
an organization as well as many social works. In
addition, BD has used for many purposes in various
industries to improve their performance. In addition, this
paper will discuss about the BD challenges in IoT and
cloud. It will explain the role of BD in the IoT and cloud
with its benefits and drawbacks.
This paper will discuss about the various things,
which can help in the improvement of performance of
various business processes. It will provide details about
the technical issues and challenges of BD in detail. This
paper will describe about the relationship between BD,
IoT, and cloud. This paper will analyze all the things
based on the various analysis and comparisons as well as
contrast.
2. BACKGROUND/LITERATURE REVIEW
2.1 Big data relationship with IoT and cloud
The BD is a base of all the systems, as it provides
various services to upper-level technologies and
applications of various information systems. There are
many advantages of BD in the management of various
things in a proper manner. BD and IoT have a
relationship because it is necessary to manage data
collection and data management (SUN, SONG, JARA, &
BIE, 2016). There are various impacts of BD on data
collection from various IoT devices. Those data have
used for the business analytics and other reporting
(ARESS, 2019).
All the things are properly managed using BD and
other things. In addition, there are many critical issues in
front of BD with the integration of cloud and IoT. There
is some important factor of BD, which has depended on
the cloud and IoT. Besides, transformation of data from

Big data challenges in IoT and cloud 2
IoT devices and other benefits of data analytics and
business analytics on the business processes (BAESENS,
BAPNA, MARSDEN, VANTHIENEN, & ZHAO, 2016).
2.2 Role of integration between IoT application and
BD
Moreover, BD has used in the planning and
implementation of smart cities and other urban planning
(Batty, 2013). It has used for the management of a large
amount of data and information, which has collected
from various data sources, such as databases, open files,
IoT devices, transactional data and many other sources
(Ranjan, 2014). It makes huge impact on the business
processes of an organization (Mohapatra, Paikaray, &
Samal, 2015).
There are some important factors of data collection
and improvement in integration of processes, which
makes a huge impact on the operational processes of IoT
and cloud. All these things are necessary to improve the
processes of data analysis and project management. IoT
applications have used for the data generation and
optimization process (Rathore, Ahmad, Paul, & Rho,
2016). Therefore, it is necessary to improve the
relationship between BD and cloud with the IoT. It will
improve the process of data collection (Ray & Trovati,
2018).
There are three parts of the cloud, which are SaaS,
PaaS, and IaaS. In addition, service-as-a-service has
used for the users, which provides applications, data
storage, and other services to the end-user for their
particular work. Platform-as-a-Service has provided
different things for the application developers, such as
Operating systems and application servers as well as
stack network. It has provided many benefits to the
companies in their business functions. Infrastructure-as-
a-service has used for the IT infrastructure and network.
It is the main purpose of the IaaS to provide all the
services and manage them using proper server
configuration.
There is some basic need for the IoT and Cloud,
which provides help in the data analysis and business
analytics. However, there are various emerging
technologies has used for the integration of data and
other processes. BD has used for the reduction of
various things (Bou-Harb, Debbabi, & Assi, 2016).
BD has used in various fields. In case of sports, it has
provided better results and it is helpful for sportsman to
improve the performance and accuracy (Brousell, 2014).
In addition, it has provided high level of input to
improve the things, which can provide better results for
a sportsman (Brown, 2017).
Business Intelligence (BI) has dependent on the BD
and its processes, as data analytics has based on the data
and its significance in the analysis (Chen, Chiang, &
Storey, 2012). Data warehouse and BD have interlinked
with each other and it is necessary to help the main
objective of the BD, which is data analysis (Chowdhury,
2014). BD should have basic processes to improve the
data collection process. It makes huge impact on the
data and business analytics. It is also beneficial for the
privacy and security of data. There are some important
concepts of data collection, which must use in the
particular field and application to manage all the issues
and challenges (Clark, 2018).
BD has managed a large amount of data, which is
necessary for the data analysis and business intelligence
(Cuzzocrea, 2014). In addition, there are some
cybersecurity issues in the databases and other things.
BD has provided security to the data collection
(Datameer, 2018).

Big data challenges in IoT and cloud 3
BD is a base of all the systems, as the above diagram
showing the overall process of data collection and
manipulation. There are three things in whole process,
which are input, process, and output (Scurfield, 2016).
BD analytics have provided all the input for processing.
There are various tools for the processing of the data,
such as Hadoop, RDBMS, MAP REDUCE, NoSQL, and
many others (Subramaniam, 2019).
There is a relationship between the IoT and BD, as
IoT devices have provided a large amount of data to the
BD analytics, which produces a proper data records for
the analysis process (SUN, SONG, JARA, & BIE, 2016).
There are many data mining algorithms have used for
the analysis of the data, which has collected by the BD
(TAYLOR, 2018).
Data analysis is a necessary process to improve the
results of the overall process (VANTAZ, 2014). BD has
generated experimental data for the analysis, which
provides better results in terms of decision-making
process (Verma, 2018). BD has used various methods
for integration of the data from the IoT devices and store
that data on the cloud, such as MapReduce algorithms,
Hadoop and many other methods (Gandomi & Haider,
2015).
There is a strong relationship between the IoT, BD,
and cloud as all are connected with each other. A
particular work has related to particular techniques
(White, Ariyachandra, & White, 2017).
The above diagram has shown that IoT manages
messaging services between thousands of devices. All
the devices have generated a large amount of data,
which has gathered by the BD in their persistent storage
(GUPTA, DEOKAR, IYER, SHARDA, & SCHRADER, 2018).
3. SOLUTIONS/FINDINGS/RECOMMENDATIONS
3.1 Data collection techniques;
There are some important methods for the data
collection from the IoT devices. In addition, cloud-
commuting services must use security and privacy
methods to prevent various types of cyber-attacks
(WOODIE, 2018). Moreover, BD can improve the
integration and transformation approaches (ZHAROVA &
ALIN, 2017).
BD secure all the services using security API, such
as medical applications, transportation, mobile
applications, and many more.
3.2 Security and privacy management
BD provides a high level of security to the data using
various systems of security management.in addition;
there are some security issues in data collection and
transformation of data at the end of databases. In case of
smart city, there are various types of public data
included in the data collection. Therefore, security and
privacy are necessary for the whole system (Hashem, et
al., 2016).

Big data challenges in IoT and cloud 4
The fog computing layer provides proper
communication between the IoT layer and cloud
computing layer to avoid unnecessary conflicts.
There are some proper applications for
communication between machine-to-machine (M2M)
communications. It can use the MQTT protocol for the
management of communication between various
machines.
Moreover, there are some changes in front of BD in
the data collection process because of missing data and
network issues. Fog computing has provided help in
gathering data and information. There are some
important factors in which cloud technologies provide
help to manage all those issues in a proper manner.
Furthermore, BD can manage all the security and
privacy challenges using cybersecurity. BD is helpful in
behavior analysis, which is important for the business of
an organization (Kanavos, Iakovou, Sioutas, &
Tampakas, 2018). In the case of real-time cities, BD
provides help for data calculation and manipulation as
well as it provides proper reports about the data
collection (Kitchin, 2014).
4. CONCLUSION AND FUTURE RESEARCH
It has concluded that from the above section of this
paper that BD has provided many good approaches for
the management of data collection and various other
processes in IoT and cloud. This paper has provided the
impacts of BD techniques of the data analytics and
business analytics. There are some technical issues in
the BD because of IoT devices and applications. It is a
huge challenge in front of the cloud to provide data
analysis report.
This paper has critically analyzed the relationship of
BD in IoT and cloud. In addition, the security and
privacy of the data can be handled at the BD using their
internal architecture of data collection. Finally, BD has
faced integration and security challenges in many
processes. Organizations can use cybersecurity for
securing the data.
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