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Special Issue "Next Generation Technologies for Sensor Networks and Internet of Things"

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

Deadline for manuscript submissions: closed (30 July 2018).

Special Issue Editor

Dr. Ilker Demirkol
E-Mail Website
Guest Editor
Department of Network Engineering, Universitat Politecnica de Catalunya, c/ Jordi Girona 1-3, Modul C3 Barcelona, Catalunya 08034, Spain
Interests: Internet of Things; wireless mesh; ad hoc and sensor networks; wake-up radio systems; 5G; LTE; network algorithms
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Sensors and their networking allow the monitoring of physical objects and/or events, whereas the Internet of Things (IoT) paradigm enables the inter-communication of everyday objects and humans. There is a significant overlap between the targets of these topics, including the critical objective of low-cost, low-power communication and networking solutions. This is especially important to justify the economic feasibility of employing such solutions in billions of objects, as well as to reduce the maintenance cost by increasing the lifetime of the batteries and/or energy harvesting methods used.

Along this line, there has been a tremendous effort from both the industrial and scientific communities developing disruptive solutions, such as Low Power WAN (LP-WAN), high-efficiency energy harvesting methods/materials, alternative communication media (e.g., visible light communication, molecular communication), etc. In this Special Issue, we will cover the studies that evaluate and/or improve such disruptive solutions, or that propose promising ideas for the next generation communication/networking technologies for wireless sensor networks (WSN) and/or IoT.

The topics of interest include, but are not limited to:

  • LP-WAN technologies including LoRaWAN, NB-IoT, etc.

  • 5G and Beyond 5G access technologies for IoT/WSN

  • Software-defined networking for IoT/WSN

  • Mobile Edge Computing, multi-access edge computing, fog computing for IoT/WSN

  • Energy efficiency and energy harvesting for IoT/WSN

  • Novel security solutions for IoT/WSN

  • Licensed, Unlicensed, and Mixed Spectrum Systems

  • IPv6 over Networks of Resource-constrained Nodes (6lo), IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH), Routing Over Low power and Lossy networks (ROLL) solutions including 6LoWPAN, IPv6 over Bluetooth Low Energy

  • Future Internet architectures and IoT

  • Standardization in communication and networking for IoT/WSN, e.g., WoT, oneM2M, CoAP, etc.

  • Named Data Networking for IoT/WSN

  • Energy-autonomous WSN/IoT solutions

  • Wake-up radio systems

Dr. Ilker Demirkol
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Internet of Things (IoT)

  • Wireless sensor networks (WSN)

  • LP-WAN

  • NB-IoT

  • Energy efficient, low-power communication

  • IPv6 for resource-constrained nodes

Published Papers (13 papers)

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Research

Open AccessArticle
Reputation-Aware Recruitment and Credible Reporting for Platform Utility in Mobile Crowd Sensing with Smart Devices in IoT
Sensors 2018, 18(10), 3305; https://doi.org/10.3390/s18103305 - 01 Oct 2018
Cited by 1
Abstract
The Internet of things (IoT) comprises a huge collection of electronic devices connected to the Internet to ensure the dependable exchange of sensing information. It involves mobile workers (MWs) who perform various activities to support enormous online services and applications. In mobile crowd [...] Read more.
The Internet of things (IoT) comprises a huge collection of electronic devices connected to the Internet to ensure the dependable exchange of sensing information. It involves mobile workers (MWs) who perform various activities to support enormous online services and applications. In mobile crowd sensing (MCS), a massive amount of sensing data is also generated by smart devices. Broadly, in the IoT, verifying the credibility and truthfulness of MWs’ sensing reports is needed for MWs to expect attractive rewards. MWs are recruited by paying monetary incentives that must be awarded according to the quality and quantity of the task. The main problem is that MWs may perform false reporting by sharing low-quality reported data to reduce the effort required. In the literature, false reporting is improved by hiring enough MWs for a task to evaluate the trustworthiness and acceptability of information by aggregating the submitted reports. However, it may not be possible due to budget constraints, or when malicious reporters are not identified and penalized properly. Recruitment is still not a refined process, which contributes to low sensing quality. This paper presents Reputation, Quality-aware Recruitment Platform (RQRP) to recruit MWs based on reputation for quality reporting with the intention of platform profit maximization in the IoT scenario. RQRP comprises two main phases: filtration in the selection of MWs and verifying the credibility of reported tasks. The former is focused on the selection of suitable MWs based on different criteria (e.g., reputation, bid, expected quality, and expected platform utility), while the latter is more concerned with the verification of sensing quality, evaluation of reputation score, and incentives. We developed a testbed to evaluate and analyze the datasets, and a simulation was performed for data collection scenario from smart sensing devices. Results proved the superiority of RQRP against its counterparts in terms of truthfulness, quality, and platform profit maximization. To the best of our knowledge, we are the first to study the impact of truthful reporting on platform utility. Full article
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Open AccessArticle
Overcoming Limitations of LoRa Physical Layer in Image Transmission
Sensors 2018, 18(10), 3257; https://doi.org/10.3390/s18103257 - 27 Sep 2018
Cited by 3
Abstract
As a possible implementation of a low-power wide-area network (LPWAN), Long Range (LoRa) technology is considered to be the future wireless communication standard for the Internet of Things (IoT) as it offers competitive features, such as a long communication range, low cost, and [...] Read more.
As a possible implementation of a low-power wide-area network (LPWAN), Long Range (LoRa) technology is considered to be the future wireless communication standard for the Internet of Things (IoT) as it offers competitive features, such as a long communication range, low cost, and reduced power consumption, which make it an optimum alternative to the current wireless sensor networks and conventional cellular technologies. However, the limited bandwidth available for physical layer modulation in LoRa makes it unsuitable for high bit rate data transfer from devices like image sensors. In this paper, we propose a new method for mangrove forest monitoring in Malaysia, wherein we transfer image sensor data over the LoRa physical layer (PHY) in a node-to-node network model. In implementing this method, we produce a novel scheme for overcoming the bandwidth limitation of LoRa. With this scheme the images, which requires high data rate to transfer, collected by the sensor are encrypted as hexadecimal data and then split into packets for transfer via the LoRa physical layer (PHY). To assess the quality of images transferred using this scheme, we measured the packet loss rate, peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) index of each image. These measurements verify the proposed scheme for image transmission, and support the industrial and academic trend which promotes LoRa as the future solution for IoT infrastructure. Full article
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Open AccessArticle
NovaGenesis Applied to Information-Centric, Service-Defined, Trustable IoT/WSAN Control Plane and Spectrum Management
Sensors 2018, 18(9), 3160; https://doi.org/10.3390/s18093160 - 19 Sep 2018
Cited by 1
Abstract
We integrate, for the first time in the literature, the following ingredients to deal with emerging dynamic spectrum management (DSM) problem in heterogeneous wireless sensors and actuators networks (WSANs), Internet of things (IoT) and Wi-Fi: (i) named-based routing to provide provenance and location-independent [...] Read more.
We integrate, for the first time in the literature, the following ingredients to deal with emerging dynamic spectrum management (DSM) problem in heterogeneous wireless sensors and actuators networks (WSANs), Internet of things (IoT) and Wi-Fi: (i) named-based routing to provide provenance and location-independent access to control plane; (ii) temporary storage of control data for efficient and cohesive control dissemination, as well as asynchronous communication between software-controllers and devices; (iii) contract-based control to improve trust-ability of actions; (iv) service-defined configuration of wireless devices, approximating their configurations to real services needs. The work is implemented using NovaGenesis architecture and a proof-of-concept is evaluated in a real scenario, demonstrating our approach to automate radio frequency channel optimization in Wi-Fi and IEEE 802.15.4 networks in the 2.4 GHz bands. An integrated cognitive radio system provides the dual-mode best channel indications for novel DSM services in NovaGenesis. By reconfiguring Wi-Fi/IoT devices to best channels, the proposed solution more than doubles the network throughput, when compared to the case of mutual interference. Therefore, environments equipped with the proposal provide enhanced performance to their users. Full article
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Open AccessArticle
A Self-Adaptive Progressive Support Selection Scheme for Collaborative Wideband Spectrum Sensing
Sensors 2018, 18(9), 3011; https://doi.org/10.3390/s18093011 - 08 Sep 2018
Cited by 1
Abstract
The sampling rate of wideband spectrum sensing for sparse signals can be reduced by sub-Nyquist sampling with a Modulated Wideband Converter (MWC). In collaborative spectrum sensing, the fusion center recovers the spectral support from observation and measurement matrices reported by a network of [...] Read more.
The sampling rate of wideband spectrum sensing for sparse signals can be reduced by sub-Nyquist sampling with a Modulated Wideband Converter (MWC). In collaborative spectrum sensing, the fusion center recovers the spectral support from observation and measurement matrices reported by a network of CRs, to improve the precision of spectrum sensing. However, the MWC has a very high hardware complexity due to its parallel structure; it sets a fixed threshold for a decision without considering the impact of noise intensity, and needs a priori information of signal sparsity order for signal support recovery. To address these shortcomings, we propose a progressive support selection based self-adaptive distributed MWC sensing scheme (PSS-SaDMWC). In the proposed scheme, the parallel hardware sensing channels are scattered on secondary users (SUs), and the PSS-SaDMWC scheme takes sparsity order estimation, noise intensity, and transmission loss into account in the fusion center. More importantly, the proposed scheme uses a support selection strategy based on a progressive operation to reduce missed detection probability under low SNR levels. Numerical simulations demonstrate that, compared with the traditional support selection schemes, our proposed scheme can achieve a higher support recovery success rate, lower sampling rate, and stronger time-varying support recovery ability without increasing hardware complexity. Full article
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Open AccessArticle
Energy Efficient Policies for Data Transmission in Disruption Tolerant Heterogeneous IoT Networks
Sensors 2018, 18(9), 2891; https://doi.org/10.3390/s18092891 - 31 Aug 2018
Cited by 3
Abstract
The Internet-of-things facilitates the development of many groundbreaking applications. A large number of these applications involve mobile end nodes and a sparsely deployed network of base stations that operate as gateways to the Internet. Most of the mobile nodes, at least within city [...] Read more.
The Internet-of-things facilitates the development of many groundbreaking applications. A large number of these applications involve mobile end nodes and a sparsely deployed network of base stations that operate as gateways to the Internet. Most of the mobile nodes, at least within city areas, are connected through low power wide area networking technologies (LPWAN) using public frequencies. Mobility and sparse network coverage result in long delays and intermittent connectivity for the end nodes. Disruption Tolerant Networks and utilization of heterogeneous wireless interfaces have emerged as key technologies to tackle the problem at hand. The first technology renders communication resilient to intermittent connectivity by storing and carrying data while the later increases the communication opportunities of the end nodes and at the same time reduces energy consumption whenever short-range communication is possible. However, one has to consider that end nodes are typically both memory and energy constrained devices which makes finding an energy efficient data transmission policy for heterogeneous disruption tolerant networks imperative. In this work we utilize information related to the spatial availability of network resources and localization information to formulate the problem at hand as a dynamic programming problem. Next, we utilize the framework of Markov Decision Processes to derive approximately optimal and suboptimal data transmission policies. We also prove that we can achieve improved packet transmission policies and reduce energy consumption, extending battery lifetime. This is achieved by knowing the spatial availability of heterogeneous network resources combined with the mobile node’s location information. Numerical resultsshow significant gains achieved by utilizing the derived approximately optimal and suboptimal policies. Full article
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Open AccessArticle
A High-Efficiency Data Collection Method Based on Maximum Recharging Benefit in Sensor Networks
Sensors 2018, 18(9), 2887; https://doi.org/10.3390/s18092887 - 31 Aug 2018
Cited by 1
Abstract
To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the [...] Read more.
To reduce time delays during data collection and prolong the network lifetime in Wireless Rechargeable Sensor Networks (WRSNs), a type of high-efficiency data collection method based on Maximum Recharging Benefit (DCMRB) is proposed in this paper. According to the minimum number of the Mobile Data Collectors (MDCs), the network is firstly divided into several regions with the help of the Virtual Scan Line (VSL). Then, the MDCs and the Wireless Charging Vehicles (WCVs) are employed in each region for high efficient data collection and energy replenishment. In order to ensure the integrity of data collection and reduce the rate of packet loss, a speed adjustment scheme for MDC is also proposed. In addition, by calculating the adaptive threshold of the recharging request, those nodes with different energy consumption rates are recharged in a timely way that avoids their premature death. Finally, the limited battery capacity of WCVs and their energy consumption while moving are also taken into account, and an adaptive recharging scheme based on maximum benefit is proposed. Experimental results show that the energy consumption is effectively balanced in DCMRB. Furthermore, this can not only enhance the efficiency of data collection, but also prolong the network lifetime compared with the Energy Starvation Avoidance Online Charging scheme (ESAOC), Greedy Mobile Scheme based on Maximum Recharging Benefit (GMS-MRB) and First-Come First-Served (FCFS) methods. Full article
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Open AccessArticle
Robust Channel Allocation with Heterogeneous Requirements for Wireless Mesh Backbone Networks
Sensors 2018, 18(8), 2687; https://doi.org/10.3390/s18082687 - 16 Aug 2018
Cited by 1
Abstract
When multiple mobile sensors and actuators share a common wireless mesh backbone network of defence systems, the channel allocation mechanism must guarantee the heterogeneous link requirements under conditions of uncertainty. In this paper, a robust channel allocation mechanism is proposed by exploiting partially [...] Read more.
When multiple mobile sensors and actuators share a common wireless mesh backbone network of defence systems, the channel allocation mechanism must guarantee the heterogeneous link requirements under conditions of uncertainty. In this paper, a robust channel allocation mechanism is proposed by exploiting partially overlapped channels for directional multi-channel wireless mesh networks. The approach relies on a chance-constrained optimization problem, in which the objective is to minimize the spectrum usage of the network, and the constraints are the signal-to-interference-plus-noise ratio requirements of links with uncertainty. We convert the proposed integer non-linear optimization problem into a mixed-integer convex problem by using efficient transition and approximation. The optimal channel allocation is obtained by solving the proposed optimization problem which adapts to the heterogeneous link and robustness requirements. The simulation results show that the proposed method ensures the heterogeneous link requirements under uncertain conditions while minimizing the spectrum usage of the network. Full article
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Open AccessArticle
Unified Channel Management for Cognitive Radio Sensor Networks Aided Internet of Things
Sensors 2018, 18(8), 2665; https://doi.org/10.3390/s18082665 - 14 Aug 2018
Cited by 1
Abstract
Cognitive capabilities are indispensable for the Internet of Things (IoT) not only to equip them with learning, thinking, and decision-making capabilities but also to cater to their unprecedented huge spectrum requirements due to their gigantic numbers and heterogeneity. Therefore, in this paper, a [...] Read more.
Cognitive capabilities are indispensable for the Internet of Things (IoT) not only to equip them with learning, thinking, and decision-making capabilities but also to cater to their unprecedented huge spectrum requirements due to their gigantic numbers and heterogeneity. Therefore, in this paper, a novel unified channel management framework (CMF) is introduced for cognitive radio sensor networks (CRSNs), which comprises an (1) opportunity detector (ODR), (2) opportunity scheduler (OSR), and (3) opportunity ranker (ORR) to specifically address the immense and diverse spectrum requirements of CRSN-aided IoT. The unified CMF is unique for its type as it covers all three angles of spectrum management. The ODR is a double threshold based multichannel spectrum sensor that allows an IoT device to concurrently sense multiple channels to maximize spectrum opportunities. OSR is an integer linear programming (ILP) based channel allocation mechanism that assigns channels to heterogeneous IoT devices based on their minimal quality of service (QoS) requirements. ORR collects feedback from IoT devices about their transmission experience and generates special channel-sensing order (CSO) for each IoT device based on the data rate and idle-time probabilities. The simulation results demonstrate that the proposed CMF outperforms the existing ones in terms of collision probability, detection probability, blocking probability, idle-time probability, and data rate. Full article
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Open AccessArticle
Energy-Efficient Multicast Service Delivery Exploiting Single Frequency Device-To-Device Communications in 5G New Radio Systems
Sensors 2018, 18(7), 2205; https://doi.org/10.3390/s18072205 - 09 Jul 2018
Cited by 1
Abstract
The forthcoming fifth generation (5G) networks are claimed to deliver the large amount of traffic generated by the huge number of heterogeneous devices that constitute the Internet of Things (IoT). This unprecedented volume of both human- and machine-generated traffic to be managed imposes [...] Read more.
The forthcoming fifth generation (5G) networks are claimed to deliver the large amount of traffic generated by the huge number of heterogeneous devices that constitute the Internet of Things (IoT). This unprecedented volume of both human- and machine-generated traffic to be managed imposes 5G network operators to move the focus from throughput-optimized to energy-efficiency-optimized resource allocation solutions. Device-to-device (D2D) communications are recognized as an effective offloading technique that the 5G network can exploit to boost the capacity and energy efficiency of future 5G networks. In this paper, we design a technique to efficiently deliver multicast traffic in a 5G New Radio (NR) network by exploiting the benefits of D2D communication and single-frequency operation in order to improve the overall network energy efficiency. In the designed solution, the subset of devices in better channel conditions are served through a conventional multicast transmission, while cell-edge devices receive the multicast service from relay nodes that simultaneously transmit in D2D mode the same content. The dimension of the multicast serving area and the set of D2D connections to establish are chosen in order to maximize the overall network energy efficiency. Performed simulation results show the effectiveness of the proposed solution under varying frame configurations and number of multicast devices. Full article
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Open AccessArticle
Contention-Aware Adaptive Data Rate for Throughput Optimization in LoRaWAN
Sensors 2018, 18(6), 1716; https://doi.org/10.3390/s18061716 - 25 May 2018
Cited by 2
Abstract
In Long Range Wide Area Network (LoRaWAN), the data rate of the devices can be adjusted to optimize the throughput by changing the spreading factor. However, the adaptive data rate has to be carefully utilized because the collision probability, which directly affects the [...] Read more.
In Long Range Wide Area Network (LoRaWAN), the data rate of the devices can be adjusted to optimize the throughput by changing the spreading factor. However, the adaptive data rate has to be carefully utilized because the collision probability, which directly affects the throughput, is changed according to the use of spreading factors. Namely, the greater the number of devices using the same spreading factor, the greater the probability of collision, resulting in a decrease of total throughput. Nevertheless, in the current system, the only criteria to determine the data rate to be adjusted is a link quality. Therefore, contention-aware adaptive data rate should be designed for the throughput optimization. Here, the number of devices which can use a specific data rate is restricted, and accordingly the optimization problem can be regarded as constrained optimization. To find an optimal solution, we adopt the gradient projection method. By adjusting the data rate based on the retrieved set of optimal data rate, the system performance can be significantly improved. The numerical results demonstrate that the proposed method outperforms the comparisons regardless of the number of devices and is close to the theoretical upper bound of throughput. Full article
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Open AccessArticle
Digital Self-Interference Cancellation for Asynchronous In-Band Full-Duplex Underwater Acoustic Communication
Sensors 2018, 18(6), 1700; https://doi.org/10.3390/s18061700 - 24 May 2018
Cited by 3
Abstract
To improve the throughput of underwater acoustic (UWA) networking, the In-band full-duplex (IBFD) communication is one of the most vital pieces of research. The major drawback of IBFD-UWA communication is Self-Interference (SI). This paper presents a digital SI cancellation algorithm for asynchronous IBFD-UWA [...] Read more.
To improve the throughput of underwater acoustic (UWA) networking, the In-band full-duplex (IBFD) communication is one of the most vital pieces of research. The major drawback of IBFD-UWA communication is Self-Interference (SI). This paper presents a digital SI cancellation algorithm for asynchronous IBFD-UWA communication system. We focus on two issues: one is asynchronous communication dissimilar to IBFD radio communication, the other is nonlinear distortion caused by power amplifier (PA). First, we discuss asynchronous IBFD-UWA signal model with the nonlinear distortion of PA. Then, we design a scheme for asynchronous IBFD-UWA communication utilizing the non-overlapping region between SI and intended signal to estimate the nonlinear SI channel. To cancel the nonlinear distortion caused by PA, we propose an Over-Parameterization based Recursive Least Squares (RLS) algorithm (OPRLS) to estimate the nonlinear SI channel. Furthermore, we present the OPRLS with a sparse constraint to estimate the SI channel, which reduces the requirement of the length of the non-overlapping region. Finally, we verify our concept through simulation and the pool experiment. Results demonstrate that the proposed digital SI cancellation scheme can cancel SI efficiently. Full article
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Open AccessArticle
A Lightweight Protocol for Secure Video Streaming
Sensors 2018, 18(5), 1554; https://doi.org/10.3390/s18051554 - 14 May 2018
Cited by 7
Abstract
The Internet of Things (IoT) introduces many new challenges which cannot be solved using traditional cloud and host computing models. A new architecture known as fog computing is emerging to address these technological and security gaps. Traditional security paradigms focused on providing perimeter-based [...] Read more.
The Internet of Things (IoT) introduces many new challenges which cannot be solved using traditional cloud and host computing models. A new architecture known as fog computing is emerging to address these technological and security gaps. Traditional security paradigms focused on providing perimeter-based protections and client/server point to point protocols (e.g., Transport Layer Security (TLS)) are no longer the best choices for addressing new security challenges in fog computing end devices, where energy and computational resources are limited. In this paper, we present a lightweight secure streaming protocol for the fog computing “Fog Node-End Device” layer. This protocol is lightweight, connectionless, supports broadcast and multicast operations, and is able to provide data source authentication, data integrity, and confidentiality. The protocol is based on simple and energy efficient cryptographic methods, such as Hash Message Authentication Codes (HMAC) and symmetrical ciphers, and uses modified User Datagram Protocol (UDP) packets to embed authentication data into streaming data. Data redundancy could be added to improve reliability in lossy networks. The experimental results summarized in this paper confirm that the proposed method efficiently uses energy and computational resources and at the same time provides security properties on par with the Datagram TLS (DTLS) standard. Full article
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Open AccessArticle
A Multi-Hop Clustering Mechanism for Scalable IoT Networks
Sensors 2018, 18(4), 961; https://doi.org/10.3390/s18040961 - 23 Mar 2018
Cited by 1
Abstract
It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet [...] Read more.
It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network. Full article
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