Examining Communication Technologies of IoT for Best QoS

The Internet of Things (IoT) architecture has gained an increased amount of attention from academia as well as the industry sector as a significant methodology for the development of innovative applications and systems. Currently, the merging of this architecture with that of Cloud computing has been largely motivated by the need for various applications and infrastructures in IoT. In addition to this, the Cloud ascends as an eminent solution that would help solve various challenges that are faced by the IoT standard when varied physical devices. There are an excessive number of Cloud service providers the web along with many other services. Thus, it becomes critical to choose the provider who can be efficient, consistent, and suitable, and who can deliver the best Quality of Service (QoS). Thus, this chapter discusses QoS for cloud computing and IoT.

Extending IoTs Into the Cloud-Based Platform for Examining Amazon Web Services

The public cloud Amazon Web Service (AWS) provides a wide range of services like computation, networking, analytics, development and management tools, application services, mobile services, and management of Internet-of-Things (IoT) devices. The Amazon Web Services (AWS) IoT is an excellent IoT cloud platform and is exclusively responsible for connecting devices into various fields like healthcare, biology, municipal setup, smart homes, marketing, industrial, agriculture, education, automotive, etc. This chapter highlights many other initiatives promoted by AWS IoT. The main motive of this chapter is to present how AWS IoT works. The chapter starts with the design principles of AWS IoT services. Further, the authors present a detailed description of the AWS IoT components (e.g., Device SDK, Message Broker, Rule Engine, Security and Identity Service, Thing Registry, Thing Shadow, and Thing Shadow Service). The chapter concludes with a description of various challenges faced by AWS IoT and future research directions.

Examining IoT's Applications Using Cloud Services

Cloud IoT has evolved from the convergence of Cloud computing with Internet of Things (IoT). The networked devices in the IoT world grow exponentially in the distributed computing paradigm and thus require the power of the Cloud to access and share computing and storage for these devices. Cloud offers scalable on-demand services to the IoT devices for effective communication and knowledge sharing. It alleviates the computational load of IoT, which makes the devices smarter. This chapter explores the different IoT services offered by the Cloud as well as application domains that are benefited by the Cloud IoT. The challenges on offloading the IoT computation into the Cloud are also discussed.

Examining Big Data Management Techniques for Cloud-Based IoT Systems

This chapter provides an insight into big data, its technical background, and how need for it has arisen globally. The evolution of Cloud technology provides a favorable environment for IoTs to nurture and flourish, creating an exponential increase in the amount of data. The Cloud environment provides easy access to this vast data from anywhere on the globe, but this availability has given rise to some challenges for organizations in managing big data efficiently. The chapter discusses the key concepts and technical and architectural principles of big data technologies that help to curb the challenges in managing big data generated by IoTs in the Cloud environment and identifies the important research directions in this area.

Examining Current Standards for Cloud Computing and IoT

The advent of Cloud computing has acted as a catalyst for the design and deployment of scalable Internet of Things business models and applications. Therefore, IoT and Cloud are nowadays two very closely affiliated future internet technologies, which go hand in hand in non-trivial IoT deployments. Furthermore, most modern IoT ecosystems are cloud-based, as will be illustrated in the chapter. This chapter briefly introduces the main cloud computing and IoT standards.

Genesis of Cloud-Based IoT Systems for Smart Generation

Internet of Things (IoT) and Cloud computing are exceptionally different innovations that have become the backbone of the smart world. This paradigm where IoT and Cloud are integrated is anticipated as an empowering influence to an extensive number of smart applications. In this chapter, the integration of Cloud and IoT is explored. This chapter also provides a picture of the integration of Cloud IoT applications. Finally, some future open issues are described.

Examining Data Lake Design Principle for Cloud Computing Technology and IoT

In the Cloud-based IoT systems, the major issue is handling the data because IoT will deliver an abundance of data to the Cloud for computing. In this situation, the cloud servers will compute the big data and try to identify the relevant data and give decisions accordingly. In the world of big data, it is a herculean task to manage inflow, storage, and exploration of millions of data files and the volume of information coming from multiple systems. The growth of this information calls for good design principles so that it can leverage the different big data tools available in the market today. From the information consumption standpoint, business users are exploring new insights from the big data that can uncover potential business value. Data lake is a technology framework that helps to solve this big data challenge.

Examining Software-Defined Networking for Cloud-Based IoT Systems

The Internet of Things (IoT) represents the current and future state of the internet. The large number of things (objects) connected to the internet produces a huge amount of data that needs a lot of effort and processing operations to transfer it to useful information. Maximizing the utilization of this paradigm requires fine-grained QoS support for differentiated application requirements, context-aware semantic information retrieval, and quick and easy deployment of resources, among many other objectives. These objectives can only be achieved if components of the IoT can be dynamically managed end-to-end across heterogeneous objects, transmission technologies, and networking architectures. In this chapter, Software Defined Systems (SDS) is described as a new paradigm to hide all complexity in traditional system architecture by abstracting all the controls and management operations from the underling devices (things in the IoT) and setting them inside a middleware layer, a software layer, using a software-based control plane.

Examining Different Applications of Cloud-Based IoT

The integration of Cloud computing and IoT provides the capability of omnipresent sensing services and powerful, efficient storage as well as processing of sensor data beyond the capability of distinct things or devices. The ability of Cloud platform in providing automatic and reliable decision making will boost the development of newer and innovative applications, like smart healthcare, cities, buildings, agriculture practices and buildings, etc. This chapter surveys a few key application areas where Cloud-based IoT technology can mark its impact. The Cloud-based architecture has been proposed for these applications, simultaneously examining and identifying the challenges involved. The salient points identified in this chapter will help researchers and scientists to explore newer applications based on the Cloud-IoT platform.

Security Issues and Its Countermeasures in Examining the Cloud-Assisted IoT

Internet of Things (IoT) offers the capability to connect and integrate both digital and physical objects to the internet and to enable machine-to-machine and machine-to-human communication or interactions services. The real-time adoptions and deployments of such systems for different applications such as smart cities, smart grids, smart homes, or smart environments require guaranteed security and privacy-enabled IoT services. This is due to fact that devices in the IoT generate, process, and exchange huge amounts of safety-critical data as well as privacy-sensitive information. In order to ensure secure and safe operation and to avoid cyber-attacks on such systems, it is crucial to incorporate security and privacy measures to countermeasure the different possible attacks. This chapter presents different security and privacy requirements and a taxonomy of security threats in the context of the IoT. In addition, the authors survey the most relevant defense strategies available in the literature related to IoT security with their merits and demerits.