The Future of the Internet

2019 ◽  
Keyword(s):  
Big Data ◽  
Sensor Networks ◽  
Internet Of Things ◽  
The Internet ◽  
Network Neutrality ◽  
Network Industries ◽  
Disruptive Innovations ◽  
The Future ◽  
The Internet Of Things

Strong dynamics and multifaceted innovations characterise the Internet. In this rapidly evolving ecosystem, challenges but also questions concerning innovation, integration and sustainability arise. The Internet of things brings disruptive innovations which are no longer limited to communication applications, but rather spur the transition of traditional network industries into intelligent (smart) networks. Critical requirements are QoS differentiated All-IP bandwidth capacities combined with sensor networks, geopositioning services and big data. In this volume, leading international researchers present their latest findings on the dynamics of the Internet in the future, covering a variety of current and highly relevant issues related to the Internet of things, 5G, interconnection, Internet ecosystem innovation and network neutrality. With contributions by Günter Knieps, Volker Stocker, Bert Sadowski, Onder Nomaler, Jason Whalley, Thomas Fetzer, Johannes M. Bauer, William Lehr, Iris Henseler-Unger, Falk von Bornstaedt, Marlies Van der Wee, ­Frederic Vannieuwenborg, Sofie Verbrugge, Christopher S. Yoo, Jesse Lambert­

The Future Is Already Here

2021 ◽  
pp. 225-251
Keyword(s):  
Virtual Reality ◽  
Big Data ◽  
Augmented Reality ◽  
Internet Of Things ◽  
Building Blocks ◽  
The Internet ◽  
Human Race ◽  
Public Displays ◽  
The Future ◽  
The Internet Of Things

In Japan, the world's most technologically sophisticated society, the future has already happened with public displays of AI-powered systems and robots underpinned by big data and fast being incorporated along with other emerging technologies such as the internet of things (IoT), augmented reality (AR), virtual reality (VR), blockchain, and cryptocurrency. Hence, the building blocks of the future already exist today, perhaps within niches, and in the coming years, they will spread to make the ‘normal' of the future. The human race needs to forge a society that collectively and fairly controls how AI will ‘write' the future to avoid it being unequally spread and affected by inequalities, cancers, and the dysfunctional habits of today.

scholarly journals Big Data Integration with IoT to Achieve the Challenges

2019 ◽  
Vol 8 (S3) ◽  
pp. 45-49
Author(s):  
V. Bhagyasree ◽  
K. Rohitha ◽  
K. Kusuma ◽  
S. Kokila
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Real World ◽  
Physical World ◽  
Sensor Data ◽  
The Internet ◽  
The Future ◽  
Iot Devices ◽  
The Right ◽  
The Internet Of Things

The Internet of Things anticipates the combination of physical gadgets to the Internet and their access to wireless sensor data which makes it useful to restrain the physical world. Big Data convergence has many aspects and new opportunities ahead of business ventures to get into a new market or enhance their operations in the current market. The existing techniques and technologies is probably safe to say that the best solution is to use big data tools to provide an analytical solution to the Internet of Things. Based on the current technology deployment and adoption trends, it is visioned that the Internet of Things is the technology of the future; while to-day’s real-world devices can provide best and valuable analytics, and people in the real world use many IOT devices. In spite of all the advertisements that companies offer in connection with the Internet of Things, you as a liable consumer, have the right to be suspicious about IoT advertisements. This paper focuses on the Internet of things concerning reality and what are the prospects for the future.

scholarly journals Problems of Powering End Devices in Wireless Networks of the Internet of Things

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2417
Author(s):  
Andrzej Michalski ◽  
Zbigniew Watral
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Radio Frequency Identification ◽  
Wireless Sensor ◽  
Alternative Possibilities ◽  
The Internet ◽  
Power Sources ◽  
Wide Range ◽  
The Internet Of Things

This article presents the problems of powering wireless sensor networks operating in the structures of the Internet of Things (IoT). This issue was discussed on the example of a universal end node in IoT technology containing RFID (Radio Frequency Identification) tags. The basic methods of signal transmission in these types of networks are discussed and their impact on the basic requirements such as range, transmission speed, low energy consumption, and the maximum number of devices that can simultaneously operate in the network. The issue of low power consumption of devices used in IoT solutions is one of the main research objects. The analysis of possible communication protocols has shown that there is a possibility of effective optimization in this area. The wide range of power sources available on the market, used in nodes of wireless sensor networks, was compared. The alternative possibilities of powering the network nodes from Energy Harvesting (EH) generators are presented.

scholarly journals A Novel Bioinspired Multiobjective Optimization Algorithm for Designing Wireless Sensor Networks in the Internet of Things

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Jun Huang ◽  
Liqian Xu ◽  
Cong-cong Xing ◽  
Qiang Duan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Multiobjective Optimization ◽  
Optimization Algorithm ◽  
Chaotic Behavior ◽  
Ant Colony ◽  
Wireless Sensor ◽  
The Internet ◽  
The Internet Of Things

The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.

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