scholarly journals Recent Advances in Antenna Design for 5G Heterogeneous Networks

Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 146
Author(s):  
Issa Elfergani ◽  
Abubakar Sadiq Hussaini ◽  
Jonathan Rodriguez ◽  
Raed A. Abd-Alhameed

Fifth-generation will support significantly faster mobile broadband speeds, low latency, and reliable communications, as well as enabling the full potential of the Internet of Things (IoT) [...]

2021 ◽  
Vol 25 (1) ◽  
pp. 34-38
Author(s):  
Jonathan Oostvogels ◽  
Fan Yang ◽  
Sam Michiels ◽  
Wouter Joosen ◽  
Danny Hughes

Latency-sensitive applications for the Internet of Things (IoT) often require performance guarantees that contemporary wireless networks fail to offer. Application scenarios involving real-time control of industrial machinery, robotics, or delay-sensitive actuation therefore typically still rely on cables: today's wireless networks cannot deliver messages in a sufficiently small and predictable amount of time. Drop-in wireless replacements for these cabled systems would nevertheless provide great benefit by eliminating the high cost and complexity associated with running cables in harsh industrial environments [1]. The symbolsynchronous bus, introduced in this article and embodied in a platform called Zero-Wire, is a novel wireless networking paradigm that addresses this gap. Using concurrent optical transmissions, it strives to bring low-latency deterministic networking to the wireless IoT.


Author(s):  
Laura Belli ◽  
Simone Cirani ◽  
Luca Davoli ◽  
Gianluigi Ferrari ◽  
Lorenzo Melegari ◽  
...  

The Internet of Things (IoT) will consist of billions (50 billions by 2020) of interconnected heterogeneous devices denoted as “Smart Objects:” tiny, constrained devices which are going to be pervasively deployed in several contexts. To meet low-latency requirements, IoT applications must rely on specific architectures designed to handle the gigantic stream of data coming from Smart Objects. This paper propose a novel Cloud architecture for Big Stream applications that can efficiently handle data coming from Smart Objects through a Graph-based processing platform and deliver processed data to consumer applications with low latency. The authors reverse the traditional “Big Data” paradigm, where real-time constraints are not considered, and introduce the new “Big Stream” paradigm, which better fits IoT scenarios. The paper provides a performance evaluation of a practical open-source implementation of the proposed architecture. Other practical aspects, such as security considerations, and possible business oriented exploitation plans are presented.


2020 ◽  
pp. 1260-1284
Author(s):  
Laura Belli ◽  
Simone Cirani ◽  
Luca Davoli ◽  
Gianluigi Ferrari ◽  
Lorenzo Melegari ◽  
...  

The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.


Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2783 ◽  
Author(s):  
Linh-An Phan ◽  
Taehong Kim

Smart home is one of the most promising applications of the Internet of Things. Although there have been studies about this technology in recent years, the adoption rate of smart homes is still low. One of the largest barriers is technological fragmentation within the smart home ecosystem. Currently, there are many protocols used in a connected home, increasing the confusion of consumers when choosing a product for their house. One possible solution for this fragmentation is to make a gateway to handle the diverse protocols as a central hub in the home. However, this solution brings about another issue for manufacturers: compatibility. Because of the various smart devices on the market, supporting all possible devices in one gateway is also an enormous challenge. In this paper, we propose a software architecture for a gateway in a smart home system to solve the compatibility problem. By creating a mechanism to dynamically download and update a device profile from a server, the gateway can easily handle new devices. Moreover, the proposed gateway also supports unified control over heterogeneous networks. We implemented a prototype to prove the feasibility of the proposed gateway architecture and evaluated its performance from the viewpoint of message execution time over heterogeneous networks, as well as the latency for device profile downloads and updates, and the overhead needed for handling unknown commands.


2018 ◽  
Vol 7 (6) ◽  
pp. 31-37 ◽  
Author(s):  
Muhammad Asif Habib ◽  
Mudassar Ahmad ◽  
Sohail Jabbar ◽  
Syed Hassan Ahmed ◽  
Joel J.P.C. Rodrigues

Author(s):  
Antonio Marcos M. Medeiros ◽  
Cleidimar Garcia Pereira ◽  
Joao Victor Ramos de Castilho ◽  
Marcos Antonio de Souza ◽  
Murilo Livio de Oliveira ◽  
...  

2021 ◽  
Author(s):  
Jehad Ali ◽  
Byeong-hee Roh

Separating data and control planes by Software-Defined Networking (SDN) not only handles networks centrally and smartly. However, through implementing innovative protocols by centralized controllers, it also contributes flexibility to computer networks. The Internet-of-Things (IoT) and the implementation of 5G have increased the number of heterogeneous connected devices, creating a huge amount of data. Hence, the incorporation of Artificial Intelligence (AI) and Machine Learning is significant. Thanks to SDN controllers, which are programmable and versatile enough to incorporate machine learning algorithms to handle the underlying networks while keeping the network abstracted from controller applications. In this chapter, a software-defined networking management system powered by AI (SDNMS-PAI) is proposed for end-to-end (E2E) heterogeneous networks. By applying artificial intelligence to the controller, we will demonstrate this regarding E2E resource management. SDNMS-PAI provides an architecture with a global view of the underlying network and manages the E2E heterogeneous networks with AI learning.


Author(s):  
Tommy Prayoga ◽  
Juneman Abraham

There are at least two complementary levels in the Internet of Things. The first (back) end comes from the big data companies that mine and analyze every log of activities through every device that are attached to the second (front) end, i.e., the many aspects of our lives. However, what keeps this wheel of innovation going forward is actually the front end user. Technology, however improved and innovative, will not fulfill its full potential if users do not adopt and accept it as part of their lives. They must be willing to work with the technology - sold as way to ease and improve lives - for the machine to work and be meaningful. By then the big data companies can gather information about what users want and how they behave to grasp a better understanding and make better decisions about next technology improvement. Users' acceptance and decisions to appropriate shape how big data companies work and innovate. Acceptance and appropriation are the two of the most important areas to explore in the field of IoT optimization in the business world.


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