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Scalable and Efficient Networking and Communication Architectures in IoT Domain

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (31 January 2019) | Viewed by 71856

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Special Issue Editors

Prof. Dr. Floriano De Rango

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Department of Computer Engineering, Modelling, Electronics and Systems (DIMES), University of Calabria, 87036 Arcavacata of Rende, Cosenza, Italy
Interests: Internet of Things; advanced satellite networks for multimedia communications; wireless Ad Hoc networks; sensor networks; adaptive wireless systems; ultra wide band (UWB) technologies; channel modeling in wireless environment; security architectures and protocol over wireless networks; QoS services and architecture over distributed and centralized wireless systems
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Juan Carlos Cano

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Guest Editor

DISCA Dept., Politecnica Universitat de Valencia, Valencia, Spain
Interests: connected cars; vehicular ad hoc networks; flying ad hoc networks, modeling and simulation of wireless networks, the Internet of Things; Wi-Fi networks; wireless sensor networks; network security

Prof. Dr. Dongkyun Kim

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Guest Editor

School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
Interests: connected cars; vehicular ad hoc networks; the Internet of Things (machine-to-machine/device-to-device); Wi-Fi networks (including Wi-Fi Direct); wireless mesh networks; wireless sensor networks; future Internet
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the near future, billions of Internet of Things (IoT) devices, such sensors, Radio Frequency Identification (RFID)s, micro-cameras and smart-objects surround all places where we live, providing, not only computing-intensive, but also delay-sensitive or energy efficient, services, such as in home and building automation, intelligent transportation systems or eHealth-care domains. A great deal of data can be produced by these devices, creating a heavy traffic load, reducing the protocol scalability of a network, increasing delays and wasting energy, especially if some battery-powered devices are deployed. To face these issues, novel architectures able to combine the centralized approach of the cloud with more local policy, management and computation (e.g., edge and fog computing) can be designed and deployed. These paradigms employ more resourceful edge devices, e.g., small-scale servers, smart phones and laptops, to assist the low-end IoT devices. However, a lot of issues need to be addressed before these network architectures become fully operational. It is not clear which is the best application layer protocols to use (e.g., Constrained Application Protocol (COAP), Message Queuing Telemetry Transport (MQTT) and so on), as such, it needs to be investigated in order to determine how to distribute the computation, traffic load and functionalities among local nodes (e.g., fog nodes) and remote servers (cloud of things). Novel technologies and methods to customize the communication protocol to guarantee the coherence of data update at local and global level need to be designed. Novel data aggregation and fusion strategies can be combined to reduce the data traffic, saving energy, but, at the same time, maintaining the significance of data for application layer purposes.

This Special Issue solicits original research and practical contributions that advance IoT architectures, technologies and applications. Surveys and state-of-the-art tutorials will also be considered. Topics include, but are not limited to, the following research topics:

Architecture design for Scalable IoTs
Data-driven energy consumption and delay model of managing IoT architectures
QoS-aware IoTs architectures
The management of software in mobile transparent computing for IoTs
Communication protocol design in Scalable and Efficient IoT Architectures
Energy harvesting in energy efficient IoT architectures
Security, privacy, integrity, and trust in IoT computing offloading
Hardware design and prototyping for Scalable IoT architectures
Testbeds and simulation platforms for scalable and efficient IoT architectures.
Key applications where scalable IoT architectures can be mandatory (e.g., smart grid, home&building, connected vehicles, health-care).

Assoc. Prof. Floriano De Rango
Prof. Dr. Juan Carlos Cano
Prof. Dr. Dongkyun Kim
Guest Editors

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Keywords

IoT architectures for IoT
IoT Sensor networks
Fog computing for IoT
Cloud of things

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Published Papers (11 papers)

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Research

23 pages, 2003 KiB

Open AccessArticle

An IoT Surveillance System Based on a Decentralised Architecture

by Amilcare Francesco Santamaria, Pierfrancesco Raimondo, Mauro Tropea, Floriano De Rango and Carmine Aiello

Sensors 2019, 19(6), 1469; https://doi.org/10.3390/s19061469 - 26 Mar 2019

Cited by 56 | Viewed by 10597

Abstract

In the last few years, we witnessed numerous episodes of terrorist attacks and menaces in public crowded places. The necessity of better surveillance in these places pushed the development of new automated solutions to spot and notify possible menaces as fast as possible. In this work, we propose a novel approach to create a decentralized architecture to manage patrolling drones and cameras exploiting lightweight protocols used in the internet of things (IoT) domain. Through the adoption of the mist computing paradigm it is possible to give to all the object of the smart ecosystem a cognitive intelligence to speed up the recognition and analysis tasks. Distributing the intelligence among all the objects of the surveillance ecosystem allows a faster recognition and reaction to possible warning situations. The recognition of unusual objects in certain areas, e.g., airports, train stations and bus stations, has been made using computer vision algorithms. The adoption of the IoT protocols in a hierarchical architecture provides high scalability allowing an easy and painless join of other smart objects. Also a study on the soft real-time feasibility has been conducted and is herein presented. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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12 pages, 2061 KiB

Open AccessArticle

An Enhanced File Transfer Mechanism Using an Additional Blocking Communication Channel and Thread for IoT Environments

by Yangchan Moon and Mingyu Lim

Sensors 2019, 19(6), 1271; https://doi.org/10.3390/s19061271 - 13 Mar 2019

Cited by 3 | Viewed by 2717

Abstract

In this paper, we propose an enhanced file transfer mechanism for a communication framework (CM) for Internet of Things (IoT) applications. Our previous file transfer method uses a basic non-blocking communication channel and thread for the CM (non-blocking method), but this method has a cost of adding additional bytes to each original file block. Therefore, it is not suitable for the transfer of large-sized files. Other existing file transfer methods use a separate channel to transfer large-sized files. However, the creation of a separate channel increases the total transmission delay as the transfer frequency increases. The proposed method uses a dedicated blocking communication channel in a separate thread (blocking method). The blocking method uses a separate channel and thread which are dedicated to transferring file blocks. As it creates the separate channel in advance before the file transfer task, the proposed method does not have an additional channel creation cost at the moment of the file transfer. Through file transfer experiments, the blocking method showed a shorter file transfer time than the non-blocking method, and the transmission delay was increased as the file size grew. By supporting both non-blocking and blocking methods, an application can flexibly select the desirable method according to its requirement. If the application requires the transfer of small-sized files infrequently, it can use the non-blocking method. If the application needs to transfer small-sized or large-sized files frequently, a good alternative is to use the blocking method. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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17 pages, 1290 KiB

Open AccessArticle

A Novel Link-to-System Mapping Technique Based on Machine Learning for 5G/IoT Wireless Networks

by Eunmi Chu, Janghyuk Yoon and Bang Chul Jung

Sensors 2019, 19(5), 1196; https://doi.org/10.3390/s19051196 - 8 Mar 2019

Cited by 23 | Viewed by 7385

Abstract

In this paper, we propose a novel machine learning (ML) based link-to-system (L2S) mapping technique for inter-connecting a link-level simulator (LLS) and a system-level simulator (SLS). For validating the proposed technique, we utilized 5G K-Simulator, which was developed through a collaborative research project in Republic of Korea and includes LLS, SLS, and network-level simulator (NS). We first describe a general procedure of the L2S mapping methodology for 5G new radio (NR) systems, and then, we explain the proposed ML-based exponential effective signal-to-noise ratio (SNR) mapping (EESM) method with a deep neural network (DNN) regression algorithm. We compared the proposed ML-based EESM method with the conventional L2S mapping method. Through extensive simulation results, we show that the proposed ML-based L2S mapping technique yielded better prediction accuracy in regards to block error rate (BLER) while reducing the processing time. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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28 pages, 7264 KiB

Open AccessArticle

Design and Implementation of a Mixed IoT LPWAN Network Architecture

by Jesus Rubio-Aparicio, Fernando Cerdan-Cartagena, Juan Suardiaz-Muro and Javier Ybarra-Moreno

Sensors 2019, 19(3), 675; https://doi.org/10.3390/s19030675 - 7 Feb 2019

Cited by 26 | Viewed by 10929

Abstract

IoT is much more than a large number of objects or customer devices connected to the Internet. IoT offers organizations many more opportunities than they can imagine. According to this, sooner or later they will probably choose to build their own IoT network. In this article, we review the technologies of IoT LPWAN Sigfox and LoRa. It can be considered the most important at present due to its ability to make the smart city possible. We also propose the development, deployment and implementation of a mixed IoT architecture LoRa-Sigfox composed of components based on open hardware and software. The architecture is evaluated in a real environment focused on remote monitoring of water meter devices. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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24 pages, 720 KiB

Open AccessArticle

Whisper: Programmable and Flexible Control on Industrial IoT Networks

by Esteban Municio, Johann Marquez-Barja, Steven Latré and Stefano Vissicchio

Sensors 2018, 18(11), 4048; https://doi.org/10.3390/s18114048 - 20 Nov 2018

Cited by 20 | Viewed by 4408

Abstract

Software Defined Networking (SDN) centralizes network control to improve network programmability and flexibility. Contrary to wired settings, it is unclear how to support SDN in low power and lossy networks like typical Internet of Things (IoT) ones. Challenges encompass providing reliable in-band connectivity between the centralized controller and out-of-range nodes, and coping with physical limitations of the highly resource-constrained IoT devices. In this work, we present Whisper, an enabler for SDN in low power and lossy networks. The centralized Whisper controller of a network remotely controls nodes’ forwarding and cell allocation. To do so, the controller sends carefully computed routing and scheduling messages that are fully compatible with the protocols run in the network. This mechanism ensures the best possible in-band connectivity between the controller and all network nodes, capitalizing on an interface which is already supported by network devices. Whisper’s internal algorithms further reduce the number of messages sent by the controller, to make the exerted control as lightweight as possible for the devices. Beyond detailing Whisper’s design, we discuss compelling use cases that Whisper unlocks, including rerouting around low-battery devices and providing runtime defense to jamming attacks. We also describe how to implement Whisper in current IoT open standards (RPL and 6TiSCH) without modifying IoT devices’ firmware. This shows that Whisper can implement an SDN-like control for distributed low power networks with no specific support for SDN, from legacy to next generation IoT devices. Our testbed experiments show that Whisper successfully controls the network in both the scheduling and routing plane, with significantly less overhead than other SDN-IoT solutions, no additional latency and no packet loss. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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15 pages, 4779 KiB

Open AccessArticle

Hybrid TSR–PSR Alternate Energy Harvesting Relay Network over Rician Fading Channels: Outage Probability and SER Analysis

by Tan N. Nguyen, Phu Tran Tin, Duy Hung Ha, Miroslav Voznak, Phuong T. Tran, Minh Tran and Thanh-Long Nguyen

Sensors 2018, 18(11), 3839; https://doi.org/10.3390/s18113839 - 9 Nov 2018

Cited by 14 | Viewed by 4269

Abstract

In this research, we investigate a hybrid time-switching relay (TSR)–power-splitting relay (PSR) alternate energy harvesting (EH) relaying network over the Rician fading channels. For this purpose, the amplify-and-forward (AF) mode is considered for the alternative hybrid time TSR–PSR. The system model consists of one source, one destination and two alternative relays for signal transmission from the source to the destination. In the first step, the exact and asymptotic expressions of the outage probability and the symbol errors ratio (SER) are derived. Then, the influence of all system parameters on the system performance is investigated, and the Monte Carlo simulation verifies all results. Finally, the system performances of TSR–PSR, TSR, and PSR cases are compared in connection with all system parameters. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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21 pages, 1456 KiB

Open AccessArticle

qCon: QoS-Aware Network Resource Management for Fog Computing

by Cheol-Ho Hong, Kyungwoon Lee, Minkoo Kang and Chuck Yoo

Sensors 2018, 18(10), 3444; https://doi.org/10.3390/s18103444 - 13 Oct 2018

Cited by 26 | Viewed by 5099

Abstract

Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers. In fog computing, lightweight virtualization (e.g., containers) has been widely used to achieve low overhead for performance-limited fog devices such as WiFi access points (APs) and set-top boxes. Unfortunately, containers have a weakness in the control of network bandwidth for outbound traffic, which poses a challenge to fog computing. Existing solutions for containers fail to achieve desirable network bandwidth control, which causes bandwidth-sensitive applications to suffer unacceptable network performance. In this paper, we propose qCon, which is a QoS-aware network resource management framework for containers to limit the rate of outbound traffic in fog computing. qCon aims to provide both proportional share scheduling and bandwidth shaping to satisfy various performance demands from containers while implementing a lightweight framework. For this purpose, qCon supports the following three scheduling policies that can be applied to containers simultaneously: proportional share scheduling, minimum bandwidth reservation, and maximum bandwidth limitation. For a lightweight implementation, qCon develops its own scheduling framework on the Linux bridge by interposing qCon’s scheduling interface on the frame processing function of the bridge. To show qCon’s effectiveness in a real fog computing environment, we implement qCon in a Docker container infrastructure on a performance-limited fog device—a Raspberry Pi 3 Model B board. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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17 pages, 535 KiB

Open AccessArticle

Enhancing the Isolation and Performance of Control Planes for Fog Computing

by Kyungwoon Lee, Chiyoung Lee, Cheol-Ho Hong and Chuck Yoo

Sensors 2018, 18(10), 3267; https://doi.org/10.3390/s18103267 - 28 Sep 2018

Cited by 6 | Viewed by 3624

Abstract

Fog computing, which places computing resources close to IoT devices, can offer low latency data processing for IoT applications. With software-defined networking (SDN), fog computing can enable network control logics to become programmable and run on a decoupled control plane, rather than on a physical switch. Therefore, network switches are controlled via the control plane. However, existing control planes have limitations in providing isolation and high performance, which are crucial to support multi-tenancy and scalability in fog computing. In this paper, we present optimization techniques for Linux to provide isolation and high performance for the control plane of SDN. The new techniques are (1) separate execution environment (SE2), which separates the execution environments between multiple control planes, and (2) separate packet processing (SP2), which reduces the complexity of the existing network stack in Linux. We evaluate the proposed techniques on commodity hardware and show that the maximum performance of a control plane increases by four times compared to the native Linux while providing strong isolation. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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15 pages, 3676 KiB

Open AccessArticle

DM-MQTT: An Efficient MQTT Based on SDN Multicast for Massive IoT Communications

by Jun-Hong Park, Hyeong-Su Kim and Won-Tae Kim

Sensors 2018, 18(9), 3071; https://doi.org/10.3390/s18093071 - 12 Sep 2018

Cited by 56 | Viewed by 10869

Abstract

Edge computing is proposed to solve the problem of centralized cloud computing caused by a large number of IoT (Internet of Things) devices. The IoT protocols need to be modified according to the edge computing paradigm, where the edge computing devices for analyzing IoT data are distributed to the edge networks. The MQTT (Message Queuing Telemetry Transport) protocol, as a data distribution protocol widely adopted in many international IoT standards, is suitable for cloud computing because it uses a centralized broker to effectively collect and transmit data. However, the standard MQTT may suffer from serious traffic congestion problem on the broker, causing long transfer delays if there are massive IoT devices connected to the broker. In addition, the big data exchange between the IoT devices and the broker decreases network capability of the edge networks. The authors in this paper propose a novel MQTT with a multicast mechanism to minimize data transfer delay and network usage for the massive IoT communications. The proposed MQTT reduces data transfer delays by establishing bidirectional SDN (Software Defined Networking) multicast trees between the publishers and the subscribers by means of bypassing the centralized broker. As a result, it can reduce transmission delay by 65% and network usage by 58% compared with the standard MQTT. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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20 pages, 8672 KiB

Open AccessArticle

Disaster Management System Aided by Named Data Network of Things: Architecture, Design, and Analysis

by Abdul Hannan, Sobia Arshad, Muhammad Awais Azam, Jonathan Loo, Syed Hassan Ahmed, Muhammad Faran Majeed and Sayed Chhattan Shah

Sensors 2018, 18(8), 2431; https://doi.org/10.3390/s18082431 - 26 Jul 2018

Cited by 36 | Viewed by 7425

Abstract

Disasters are the uncertain calamities which within no time can change the situation quite drastically. They not only affect the system’s infrastructure but can also put an adverse effect on human life. A large chunk of the IP-based Internet of Things (IoT) schemes tackle disasters such as fire, earthquake, and flood. Moreover, recently proposed Named Data Networking (NDN) architecture exhibited promising results for IoT as compare to IP-based approaches. Therefore to tackle disaster management system (DMS), it is needed to explore it through NDN architecture and this is the main motivation behind this work. In this research, a NDN based IoT-DMS (fire disaster) architecture is proposed, named as NDN-DISCA. In NDN-DISCA, NDN producer pushes emergency content towards nearby consumers. To provide push support, Beacon Alert Message (BAM) is created using fixed sequence number. NDN-DISCA is simulated in ndnSIM considering the disaster scenario of IoT-based smart campus (SC). From results, it is found that NDN-DISCA exhibits minimal delay and improved throughput when compared to the legacy NDN and existing PUSH schemes. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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15 pages, 3558 KiB

Open AccessArticle

Pitfall of the Strongest Cells in Static Random Access Memory Physical Unclonable Functions

by Mingyang Gong, Hailong Liu, Run Min and Zhenglin Liu

Sensors 2018, 18(6), 1776; https://doi.org/10.3390/s18061776 - 1 Jun 2018

Cited by 7 | Viewed by 3346

Abstract

Static Random Access Memory (SRAM) Physical Unclonable Functions (PUFs) are some of the most popular PUFs that provide a highly-secured solution for secret key storage. Given that PUF responses are noisy, the key reconstruction must use error correcting code (ECC) to reduce the noise. Repetition code is widely used in resource constrained systems as it is concise and lightweight, however, research has shown that repetition codes can lead to information leakage. In this paper we found that the strongest cell distribution in a SRAM array may leak information of the responses of SRAM PUF when the repetition code is directly applied. Experimentally, on an ASIC platform with the HHGRACE 0.13 μm process, we recovered 8.3% of the measured response using the strongest cells revealed by the helper data, and we finally obtained a clone response 79% similar to weak response using the public helper data. We therefore propose Error Resistant Fuzzy Extractor (ERFE), a 4-bit error tolerant fuzzy extractor, that extracts the value of the sum of the responses as a unique key and reduces the failure rate to 1.8 × 10⁻⁸ with 256 bit entropy. Full article

(This article belongs to the Special Issue Scalable and Efficient Networking and Communication Architectures in IoT Domain)

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