Cloud Computing and Internet of Things Towards Smart World for Real-Time Applications

Research Trends and Interest Trends about the Cloud and IoT

Internet of Things (IoT), which has been evolved as a fascinating and unimaginative technology, has not only made technical improvements but also made our day-to-day routine work easier and more sorted beyond our expectations. The impact that IoT has caused on human lives is huge and it is right to label it as "the next internet." IoT is a network of networks of physical objects or things such as devices, buildings, vehicles, and various embedded items equipped with sensors and internet connections that enables them to collect and exchange data. IoT applications in the real world are limitless. Yet, there are many hindrances to avail the full potential of IoT such as limited storage capacity and processing capability of devices and major concerns regarding reliability, performance, privacy, and security [1—8].

In contrast to this, cloud computing (CC) offers almost unlimited storage capacity and processing capability. CC technology is mature enough to solve problems of IoT to a certain level [9,11,12,13,14]. CC has given numerous benefits in terms of scalability and cost-effectiveness due to its pay-as-you-go utility. Its on-demand approach has set the user free from all infrastructure and platform management techniques by changing an ownership-based approach to a subscription-based approach. IoT and CC are complementary to each other and can bring revolution in the current and future real world. The integration of cloud and IoT is known as CloudloT or Cloud of Things or Cloud-Enabled IoT [15].

In the literature, lots of work has been performed in both the areas separately. In the work, I have performed in-depth analysis of the CloudloT paradigm. By adopting this CloudloT paradigm, numerous applications are gaining momentum.

After performing rich analysis in this field, I analyzed that both the topics of the cloud and IoT are gaining popularity as depicted in Figure 11.1(a) and (b). In this chapter, I have reviewed the literature of the cloud and IoT, focusing on integrating the cloud and IoT as both together, which can be proved as a promising tool witnessed by the increasing trend of searching the cloud and IoT together as depicted in Figure 11.1(c). These results are obtained from Google Trends.

Inspired by our results in the analysis, I adopt the systematic methodology in my work as depicted in Figure 11.2. In Section 11.2,1 have given a brief introduction to IoT and CC to provide the reader with the basic understanding necessary to deal with the integration of the cloud and IoT. I present a detailed view of the drivers for integration of the technologies. I elaborated the role of CC in IoT and convergence techniques of both the technologies. Section 11.3 highlights the challenges and issues that can arise from adopting the integration of the two. Section 11.4 discusses various applications of Cloud of Things. In Section 11.5,1 describe the implementation platform and research projects of Cloud of Things. Finally, I close this chapter with concluding remarks and future scope.

Convergence of IoT and Cloud Computing

Cloud and IoT technologies have seen rapid and independent growth in the real world. These two technologies are independent but still complementary to each other.

Cloud provides various services such as Platform as a Service (PaaS), Infrastructure as a Service (IaaS), Software as a Service (SaaS), and Network as a Service (NaaS). This service business model of CC serves billion of devices connected over the internet. The number of devices connected to the internet have reached billions and are expected to grow rapidly and reach 75.44 billion by 2025 [16,15,17, 20].

The IoT vision in reality involves any interconnected devices such as sensors, computers, buildings, home appliances, smart planes, vehicles, real infrastructure devices, or any other device that can have internet connectivity or can be monitored or attached. These interconnected devices require huge amount of data for storage and processing. Large amounts of information sources in IoT produces semi-structure or unstructured data with volume, velocity, and variety as three major characteristics. CC aims at providing an on- demand service.

The cloud features such as ubiquitous computing, on-demand service, resource pooling, scalability, and elasticity support the obstacles of IoT such as reliability, efficiency, storage, and processing capabilities.

So, it's rightly said

IoT is a king, Big Data is a queen and Cloud is a palace [21].


(a) Term "cloud" search—as per Google Trends (April 2015 to October 2019 report); (b) term "IoT" search—as per Google Trends (April 2015 to October 2019 report); (c) term "Cloud of Things" search—as per Google Trends (2019-2020 report).

Figure 11.3 [22] depicts how IoT generates services for the management of which it is dependent on CC and generated services are consumed by users over the internet.

Not only is IoT benefiting from CC, but CC can also benefit from IoT by exploring its scope in dealing with real-world things in a more distributed and dynamic way. In reality, the cloud serves as an intermediate layer that functions between the objects and applications where it abstracts the complexity and functionality used to implement the latter.


Research methodology adopted in this chapter.


IoT using cloud computing.

Drivers for Cloud Computing and IoT Integration

There are various aspects of cloud and IoT that makes them a better combination or complementary to each other. These characteristics are listed here:

  • 1. Displacement: Where IoT is pervasive, Cloud is centralized. Both the techniques work towards increasing the efficiency of everyday tasks. IoT generates a huge amount of data and CC serves as a path for this data to travel.
  • 2. Reachability: The reach of IoT is very limited, whereas CC knows no boundaries; it is far and wide spread.
  • 3. Storage: IoT provides none or very limited storage, whereas CC provides virtual storage that is large or never ending.
  • 4. Role of the Internet: In the case of IoT, the internet acts as a convergence point, whereas in the case of CC, it serves as a means for delivering services.
  • 5. Computing Capability: IoT provides less or no computing capability, whereas CC provides virtually unlimited computing capability. Cloud is a rescue power when IoT finds itself in the demand of processing and computational power. CC allows the developers of IoT to offload processing capabilities to CC services.
  • 6. Components: IoT runs on hardware components such as sensors, gateways, and smart devices, whereas CC runs on virtual machines that imitate hardware components. CC allows the innovators and developers of IoT to explore the real world without having large infrastructure. CC offers readymade infrastructure to talented and creative innovators where they can just plug and play their devices and services.
  • 7. Big Data: IoT generates big data, whereas CC is a means to manage big data.

Due to offerings that a cloud provides in IoT, several new expansions of cloud services have evolved, which are listed in Table 11.1.

The architectural view of the cloud service for IoT is depicted in Figure 11.4.

TABLE 11.1

New Paradigms Evolved by Cloud of Things: Everything as Service

XaaS (Acronym)

X (Expansion)

Description Change

Things as a Service [23-25]

CC and IoT-based sendee system

S2aaS [12,26,27]

Sensing as a Service

Huge sensor data and related context-capturing techniques and challenges resolved by cloud- based management, storing, archiving, and processing capabilities.

SAaaS [28]

Sensing and Actuation as a Service

Control logics automatically enabled and managed in the cloud

SEaaS [28,29]

Sensor Event as a Service

Dispatching the services and signals generated back and from the sensor

SenaaS [30]

Sensor as a Service

Performing ubiquitous management of sensors

DBaaS [30]

DataBase as a Service

IOT generates huge data and the cloud manages that data in the database.

DaaS [30]

Data as a Service

Enabling access to ubiquitous data

EaaS [30]

Ethernet as a Service

Providing connectivity over the internet

IPMaaS [30]

Identity and Policy Management as a Service

Providing controlled access over data

VSaaS [31]

Video Surveillance as a Service

Providing complete visual control over data


Cloud service architecture for IoT.

Convergence Approaches

Two convergence approaches of the cloud and IoT exist:

Cloud-Centric IoT

Cloud-centric IoT is bringing IoT functionality into the cloud so that cloud can explore the diversions of the real world. It implements processing and computing of IoT data into the cloud and its management into the cloud (Figure 11.5).


Cloud-centric IoT.


IoT-centric cloud.

loT-Centric Cloud

The IoT-centric cloud is bringing cloud functionalities into IoT. This paradigm extends CC services with a view in mind to process and store the data closer to users. It supports dense geographical distribution that solves various problems like latency, traffic, hop count, etc. It also supports end-user security. It provides local autonomy when data is coming from the same location.

The IoT-centric cloud scheme consists of two clouds as depicted in Figure 11.6.

  • Local Cloud: An on-demand cloud created to provide a sufficient amount of storage and appropriate computing and networking capabilities to the users in a particular geographical area over a particular time period. The ultimate goal is to serve users of a certain area.
  • Global Cloud: Has an illusion of infinite storage and processing capabilities and serves business users.

Challenges to Bridge between the Cloud and IoT

IoT has changed our life chores to smart chores. As demand for processing power increases, the cloud will rescue IoT. The cloud can offer various services to IoT such as infrastructure, analytics and monitoring capability, and security and privacy, and can smooth interservice and interdevice communication; yet, there exists several challenges on the way to


Application scenarios driven by the CloudloT paradigm and its related challenges.

integrate the two. Figure 11.7 [32] explains various applications of CloudloT and major challenges associated with each application.

  • 1. Heterogeneity: A big challenge to be tackled while implementing CloudloT is heterogeneity of devices, OS, and platform. In the case of CC, heterogeneity is not a big concern as the cloud service comes with a proprietary interface. Resource integration is customized in the case of CC based on specific providers. The aspect of a multi-cloud approach has been partially taken into account and solved by cloud brokering. In IoT, on the other hand, all the components are tightly coupled as per specific application. It becomes a challenging issue with the cloud to deal with heterogeneous things. There is a need for an interoperable programming interface to deal with this diversity.
  • 2. Privacy/Access Control: Major IoT security challenges are related to authorization and authentication of devices, secure communication, ensuring privacy and integrity, managing vulnerabilities, and so on. The property of IoT of "everywhere, everything" simply implies a threat to privacy and when an IoT application is upgraded to the cloud, an issue of trust arises like lack of knowledge about Service Level Agreements (SLAs), physical location of data, and so on. Multitenancy of clouds brings another security issue. Distribution of data on the cloud raises several other concerns on security such as session hijacking, SQL injection, and virtual machine escape.
  • 3. Performance: Quality of Service (QoS) becomes a major issue in CloudloT as there are delays, jitter, bandwidth issues, high packet loss ratio in the communication.

In the case of IoT, a good amount of performance ratio is required in terms of time due to real-time response. But CloudloT QoS parameters are highly affected by distributed architecture mostly when multimedia streaming is required.

  • 4. Reliability: When applications are deployed in the cloud environment, a number of challenges related to the device not being reachable always exist [33].
  • 5. Large Scale: Cloud IoT involves billions of devices that are networked and these devices produce a huge amount of data. These billions of IoT objects connected through the cloud will definitely overstretch the cloud storage. It may sometimes lead to a difficult situation in analyzing the need for the amount of resources required for that particular application.
  • 6. Legal and Social Aspect: These challenges are equally important but partly related. For example, both the cloud and IoT services need to conform to different laws.
  • 7. Big Data: Billions of devices are networked in CloudloT and these devices produce vast amount of data. IoT is one of the major sources of big data and cloud facilitates its storage. Ubiquity of devices demands for scalability. It has been observed in studies that no solution exists for the cloud to manage big data.
  • 8. Sensor Network: Different objects use different protocols. For example, WirelessHART, Zigbee, and IEEE 1451, for connectivity. The cloud no doubt offers new opportunities for sensor data aggregation. But in contrast to this, lack of mobility of some sensors has caused a big problem in the implementation of CloudloT freely.
  • 9. Monitoring: The three major characteristics of IoT data—volume, velocity and variety—has affected the monitoring requirements of the cloud.
  • 10. Fog Computing: Research shows that the adoption of fog computing for edge location has mandate usage of specific algorithms and methodologies.

In addition to these challenges, there could be some generic issues of importance [15]:

  • • Virtualization of IoT devices
  • • Portability of services
  • • Real-time communication
  • • Interoperability between CloudloT services and infrastructure
  • • Accountability services and data hosted and executed across borders
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