Developing IoT Applications for Future Networks

Applications in the IoT domain need to manage and integrate huge amounts of heterogeneous devices. Usually these devices are treated as external dependencies residing at the edge of the infrastructure mainly transmitting sensed data or reacting to their environment. Recently, these devices will fuel the evolution of the IoT as they feed sensor data to the Internet at a societal scale. Leveraging volunteers and their mobiles as a sensing data collection outlet is known as Mobile Crowd Sensing (MCS) and poses interesting challenges, with particular regard to the management of sensing resource contributors, dealing with their subscription, random and unpredictable join and leave, and node churn. In addition, with the advent of new wireless technologies, it is expected that the use of Machine-Type Communication (MTC) will significantly increase in next generation IoT. MTC has broad application prospects and market potential. In this chapter, we explore new IoT applications for future IoT paradigms.

New Game Paradigm for IoT Systems

Game theory is a mathematical language for describing strategic interactions, in which each player's choice affects the payoff of other players. The impact of game theory in psychology has been limited by the lack of cognitive mechanisms underlying game theoretic predictions. Behavioral game, inference game, inspection game and Markov game are recent approaches linking game theory to cognitive science by adding cognitive details, theories of limits on iterated thinking, and statistical theories of how players learn and influence others. These new directions include the effects of game descriptions on choice, strategic heuristics, and mental representation. These ideas will help root game theory more deeply in cognitive science and extend the scope of both enterprises.

Cloud-Based IoT System Control Problems

Cloud computing and IoT are two very different technologies that are both already part of our life. Their adoption and use are expected to be more and more pervasive, making them important components of the Future Internet. A novel paradigm where Cloud and IoT are merged together is foreseen as disruptive and as an enabler of a large number of application scenarios. In this chapter, we focus our attention on the integration of Cloud and IoT. Reviewing the rich and articulate state of the art in this field, some issues are selected; Cloud Radio Access Network (C-RAN), Mobile Cloud IoT (MCIoT), Social Cloud (SC) and Fog Radio Access Network (F-RAN). C-RAN provides infrastructure layer services to mobile users by managing virtualized infrastructure resources. SC is a service or resource sharing framework on top of social networks, and built on the trust-based social relationships. In recent years, the idea of SC has been gaining importance because of its potential applicability. With an explosive growth of Mobile Cloud (MC) and IoT technologies, the MCIoT concept has become a new trend for the future Internet. MCIoT paradigm extends the existing facility of computing process to different mobile applications executing in mobile and portable devices. As a promising paradigm for the 5G wireless communication system, a new evolution of the cloud radio access network has been proposed, named as F-RANs. It is an advanced socially-aware mobile networking architecture to provide a high spectral and energy efficiency while alleviating backhaul burden. With the ubiquitous nature of social networks and cloud computing, IoT technologies exploit these developing new paradigms.

Basic Concepts of Internet of Things and Game Theory

With the evolution of the Internet and related technologies, there has been an evolution of new paradigm, which is the Internet of Things (IoT). IoT is the network of physical objects, such as devices, embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data. In the IoT, a large number of objects are connected to one another for information sharing, irrespective of their locations (Corcoran, 2016). Even though the IoT was defined at 1999, the concept of IoT has been in development for decades. As the technology and implementation of the IoT ideas move forward, different views for the concept of the IoT have appeared (Ma, 2011). Based on different views, in this book, the IoT is defined as a kind of modern technology, implicating machine to machine communications and person to computer communications will be extended to everything from everyday household objects to sensors monitoring the movement. Currently, we can see a few key areas of focus for the Internet of Things (IoT) that will require special attention over the course of the next decade on the part of computer science, energy technology, networks, wireless communication, and system platform. There are already a number of implementation case studies emerging from companies across a range of industry sectors.

Energy-Aware Network Control Approaches

Energy is considered as valuable resource for loT network, because the devices used for loT applications are low power-battery operated nodes. In some applications the devices are placed in remote area, when battery of the device would drain out its power, it is difficult to replace the battery. Radio Frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to overcome the barriers that prevent the real world wireless device deployment. Meanwhile, for cellular networks, the base stations (BSs) account for more than 50 percent of the energy consumption of the networks. Therefore, reducing the power consumption of BSs is crucial to energy efficient wireless networks. It can also subsequently reduce the carbon footprints. In this chapter, we focus our attention on the energy-aware IoT control algorithms. For the next-generation IoT systems, they will be key techniques.

IoT System Resource Sharing Mechanisms

As the IoT technology continues to grow, it needs to support an increasing range of services. Therefore, IoT networking over which services are provided has become an area of great importance. In particular, the management of IoT resources and the way new technology integrates into the network operator's infrastructure is critical to the success of IoT. The key to supporting a large number of services is IoT system resource. Therefore, all performance guarantees in IoT systems are conditional on currently available resource capacity. In this chapter, we focus our attention on the IoT resource allocation problem. First, an effective bandwidth allocation algorithm for heterogeneous networks is introduced. And then, a new Bitcoin mining protocol with the incentive payment process is explained. To share the computation resource, this Bitcoin protocol adopts the concept of the group bargaining solution by considering a peer-to-peer relationship.