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Special Issue "Intelligent Internet of Things (IoT) Networks"

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

Deadline for manuscript submissions: closed (30 June 2016).

Special Issue Editors

Guest Editor
Prof. Dr. Ingrid Moerman Website E-Mail
Department of Information Technology (INTEC), Internet Based Communication Networks and Services (IBCN), Ghent University – iMinds, Gaston Crommenlaan 8/201, B-9050 Gent, Belgium
Interests: wireless sensor networks; Internet of Things; cognitive radio; cognitive radio networks; cooperative networks; intelligent wireless networks; network protocols; programmable network architectures; experimentally-supported research
Guest Editor
Prof. Dr. Jeroen Hoebeke Website E-Mail
Department of Information Technology (INTEC), Internet Based Communication Networks and Services (IBCN), Ghent University – iMinds, Gaston Crommenlaan 8/201, B-9050 Gent, Belgium
Interests: mobile and wireless telecommunication networks; virtual networks; sensor networks and the Internet of Things; application enablers for the Internet of Things, ranging from conceptual idea, analysis, architectural design, protocol design and evaluation up to proof-of-concept implementation
Guest Editor
Prof. Dr. Eli De Poorter Website E-Mail
Department of Information Technology (INTEC), Internet Based Communication Networks and Services (IBCN), Ghent University – iMinds, Gaston Crommenlaan 8/201, B-9050 Gent, Belgium
Interests: wireless network protocols; network architectures; wireless sensor and ad hoc networks; future internet; self-learning networks and next-generation network architectures

Special Issue Information

Dear Colleagues,

Emerging IoT networks will consist of a massive number of heterogeneous wireless devices that compete for limited wireless resources (spectrum, energy, memory/processing capacity, etc.) and have to meet elastic traffic demands with diverging QoS requirements in terms of bandwidth, latency, reliability, burstiness, feedback loops, etc. Such IoT networks are characterized by a high degree of heterogeneity at different levels: (1) device hardware and software capabilities (low-end resource constrained devices versus high-end devices); (2) wireless technologies (low data rate versus high data rate, licensed versus unlicensed); and (3) applications which may have very different and time-varying traffic demands. IoT networks can also take various deployment strategies (from densely deployed co-located devices to networked devices that are distributed over the Internet). Many IoT solutions are already available today: from standardized solutions that are widely applicable, but further limited in flexibility, to proprietary solutions that are tailored to a specific vertical market and that are not interoperable.

The main challenge for future IoT networks is how to cope with such complex systems, where a huge number of devices compete for limited wireless resources and where heterogeneity is ever-increasing. There is an urgent need for more intelligent networks that lead to more interoperable solutions and that can make autonomous decisions on optimal operation modes and configurations.

This Special Issue targets innovative and validated solutions for improving the deployment and operation of IoT networks, including but not limited to:

  • reprogrammable and reconfigurable software architectures enabling runtime selection of operation mode and parameter settings of IoT devices at different levels (radio, network, application)
  • monitoring, analysis and diagnosis of the network context
  • intelligent algorithms and strategies for network optimization for taking optimal decisions on operation mode and configurations
  • application enablers: constrained protocols and abstractions for building IoT applications aiming to reduce programming effort, to offload the network or to improve performance or interoperability
  • adaptive quality of service (QoS) provisioning for constrained devices
  • adaptive privacy, trust and security solutions for sensors networks with constrained embedded devices
  • cooperative and heterogeneous networks
  • routing, MAC and transport layer protocols in cognitive sensor networks
  • cross-layer optimization solutions
  • tools and frameworks for designing, deploying and maintaining intelligent IoT networks
  • open source platforms for cognitive sensor networks
  • experimental validation of IoT solutions

Prof. Dr. Ingrid Moerman
Prof. Dr. Jeroen Hoebeke
Dr. Eli De Poorter
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

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
  • sensor networks
  • embedded devices
  • adaptive solutions
  • intelligent networking
  • reprogrammable software architectures
  • reconfigurable software architectures
  • network protocols
  • experimental validation
  • interoperability
  • deployment
  • maintenance

Published Papers (17 papers)

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Open AccessArticle
Device Centric Throughput and QoS Optimization for IoTsin a Smart Building Using CRN-Techniques
Sensors 2016, 16(10), 1647; https://doi.org/10.3390/s16101647 - 06 Oct 2016
Cited by 6
Abstract
The Internet of Things (IoT) has gained an incredible importance in the communication and networking industry due to its innovative solutions and advantages in diverse domains. The IoT’ network is a network of smart physical objects: devices, vehicles, buildings, etc. The IoT has [...] Read more.
The Internet of Things (IoT) has gained an incredible importance in the communication and networking industry due to its innovative solutions and advantages in diverse domains. The IoT’ network is a network of smart physical objects: devices, vehicles, buildings, etc. The IoT has a number of applications ranging from smart home, smart surveillance to smart healthcare systems. Since IoT consists of various heterogeneous devices that exhibit different traffic patterns and expect different quality of service (QoS) in terms of data rate, bit error rate and the stability index of the channel, therefore, in this paper, we formulated an optimization problem to assign channels to heterogeneous IoT devices within a smart building for the provisioning of their desired QoS. To solve this problem, a novel particle swarm optimization-based algorithm is proposed. Then, exhaustive simulations are carried out to evaluate the performance of the proposed algorithm. Simulation results demonstrate the supremacy of our proposed algorithm over the existing ones in terms of throughput, bit error rate and the stability index of the channel. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Home Automation System Based on Intelligent Transducer Enablers
Sensors 2016, 16(10), 1595; https://doi.org/10.3390/s16101595 - 28 Sep 2016
Cited by 30
Abstract
This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, [...] Read more.
This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Virtualized MME Design for IoT Support in 5G Systems
Sensors 2016, 16(8), 1338; https://doi.org/10.3390/s16081338 - 22 Aug 2016
Cited by 3
Abstract
Cellular systems are recently being considered an option to provide support to the Internet of Things (IoT). To enable this support, the 3rd Generation Partnership Project (3GPP) has introduced new procedures specifically targeted for cellular IoT. With one of these procedures, the transmissions [...] Read more.
Cellular systems are recently being considered an option to provide support to the Internet of Things (IoT). To enable this support, the 3rd Generation Partnership Project (3GPP) has introduced new procedures specifically targeted for cellular IoT. With one of these procedures, the transmissions of small and infrequent data packets from/to the devices are encapsulated in signaling messages and sent through the control plane. However, these transmissions from/to a massive number of devices may imply a major increase of the processing load on the control plane entities of the network and in particular on the Mobility Management Entity (MME). In this paper, we propose two designs of an MME based on Network Function Virtualization (NFV) that aim at facilitating the IoT support. The first proposed design partially separates the processing resources dedicated to each traffic class. The second design includes traffic shaping to control the traffic of each class. We consider three classes: Mobile Broadband (MBB), low latency Machine to Machine communications (lM2M) and delay-tolerant M2M communications. Our proposals enable reducing the processing resources and, therefore, the cost. Additionally, results show that the proposed designs lessen the impact between classes, so they ease the compliance of the delay requirements of MBB and lM2M communications. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Virtual Wireless Sensor Networks: Adaptive Brain-Inspired Configuration for Internet of Things Applications
Sensors 2016, 16(8), 1323; https://doi.org/10.3390/s16081323 - 19 Aug 2016
Cited by 5
Abstract
Many researchers are devoting attention to the so-called “Internet of Things” (IoT), and wireless sensor networks (WSNs) are regarded as a critical technology for realizing the communication infrastructure of the future, including the IoT. Against this background, virtualization is a crucial technique for [...] Read more.
Many researchers are devoting attention to the so-called “Internet of Things” (IoT), and wireless sensor networks (WSNs) are regarded as a critical technology for realizing the communication infrastructure of the future, including the IoT. Against this background, virtualization is a crucial technique for the integration of multiple WSNs. Designing virtualized WSNs for actual environments will require further detailed studies. Within the IoT environment, physical networks can undergo dynamic change, and so, many problems exist that could prevent applications from running without interruption when using the existing approaches. In this paper, we show an overall architecture that is suitable for constructing and running virtual wireless sensor network (VWSN) services within a VWSN topology. Our approach provides users with a reliable VWSN network by assigning redundant resources according to each user’s demand and providing a recovery method to incorporate environmental changes. We tested this approach by simulation experiment, with the results showing that the VWSN network is reliable in many cases, although physical deployment of sensor nodes and the modular structure of the VWSN will be quite important to the stability of services within the VWSN topology. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
A Self-Provisioning Mechanism in OpenStack for IoT Devices
Sensors 2016, 16(8), 1306; https://doi.org/10.3390/s16081306 - 17 Aug 2016
Cited by 11
Abstract
The aim of this paper is to introduce a plug-and-play mechanism for an Internet of Things (IoT) device to instantiate a Software as a Service (SaaS) application in a private cloud, built up with OpenStack. The SaaS application is the digital avatar of [...] Read more.
The aim of this paper is to introduce a plug-and-play mechanism for an Internet of Things (IoT) device to instantiate a Software as a Service (SaaS) application in a private cloud, built up with OpenStack. The SaaS application is the digital avatar of a physical object connected to Internet. As a proof of concept, a Vending Machine is retrofitted and connected to Internet with and Arduino Open Hardware device. Once the self-configuration mechanism is completed, it is possible to order a product from a mobile communication device. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Bindings and RESTlets: A Novel Set of CoAP-Based Application Enablers to Build IoT Applications
Sensors 2016, 16(8), 1217; https://doi.org/10.3390/s16081217 - 02 Aug 2016
Cited by 4
Abstract
Sensors and actuators are becoming important components of Internet of Things (IoT) applications. Today, several approaches exist to facilitate communication of sensors and actuators in IoT applications. Most communications go through often proprietary gateways requiring availability of the gateway for each and every [...] Read more.
Sensors and actuators are becoming important components of Internet of Things (IoT) applications. Today, several approaches exist to facilitate communication of sensors and actuators in IoT applications. Most communications go through often proprietary gateways requiring availability of the gateway for each and every interaction between sensors and actuators. Sometimes, the gateway does some processing of the sensor data before triggering actuators. Other approaches put this processing logic further in the cloud. These approaches introduce significant latencies and increased number of packets. In this paper, we introduce a CoAP-based mechanism for direct binding of sensors and actuators. This flexible binding solution is utilized further to build IoT applications through RESTlets. RESTlets are defined to accept inputs and produce outputs after performing some processing tasks. Sensors and actuators could be associated with RESTlets (which can be hosted on any device) through the flexible binding mechanism we introduced. This approach facilitates decentralized IoT application development by placing all or part of the processing logic in Low power and Lossy Networks (LLNs). We run several tests to compare the performance of our solution with existing solutions and found out that our solution reduces communication delay and number of packets in the LLN. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Experimental Evaluation of Unicast and Multicast CoAP Group Communication
Sensors 2016, 16(7), 1137; https://doi.org/10.3390/s16071137 - 21 Jul 2016
Cited by 15
Abstract
The Internet of Things (IoT) is expanding rapidly to new domains in which embedded devices play a key role and gradually outnumber traditionally-connected devices. These devices are often constrained in their resources and are thus unable to run standard Internet protocols. The Constrained [...] Read more.
The Internet of Things (IoT) is expanding rapidly to new domains in which embedded devices play a key role and gradually outnumber traditionally-connected devices. These devices are often constrained in their resources and are thus unable to run standard Internet protocols. The Constrained Application Protocol (CoAP) is a new alternative standard protocol that implements the same principals as the Hypertext Transfer Protocol (HTTP), but is tailored towards constrained devices. In many IoT application domains, devices need to be addressed in groups in addition to being addressable individually. Two main approaches are currently being proposed in the IoT community for CoAP-based group communication. The main difference between the two approaches lies in the underlying communication type: multicast versus unicast. In this article, we experimentally evaluate those two approaches using two wireless sensor testbeds and under different test conditions. We highlight the pros and cons of each of them and propose combining these approaches in a hybrid solution to better suit certain use case requirements. Additionally, we provide a solution for multicast-based group membership management using CoAP. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud
Sensors 2016, 16(7), 992; https://doi.org/10.3390/s16070992 - 28 Jun 2016
Cited by 19
Abstract
This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to [...] Read more.
This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
A Power-Efficient Clustering Protocol for Coal Mine Face Monitoring with Wireless Sensor Networks Under Channel Fading Conditions
Sensors 2016, 16(6), 835; https://doi.org/10.3390/s16060835 - 07 Jun 2016
Cited by 11
Abstract
This study proposes a novel power-efficient and anti-fading clustering based on a cross-layer that is specific to the time-varying fading characteristics of channels in the monitoring of coal mine faces with wireless sensor networks. The number of active sensor nodes and a sliding [...] Read more.
This study proposes a novel power-efficient and anti-fading clustering based on a cross-layer that is specific to the time-varying fading characteristics of channels in the monitoring of coal mine faces with wireless sensor networks. The number of active sensor nodes and a sliding window are set up such that the optimal number of cluster heads (CHs) is selected in each round. Based on a stable expected number of CHs, we explore the channel efficiency between nodes and the base station by using a probe frame and the joint surplus energy in assessing the CH selection. Moreover, the sending power of a node in different periods is regulated by the signal fade margin method. The simulation results demonstrate that compared with several common algorithms, the power-efficient and fading-aware clustering with a cross-layer (PEAFC-CL) protocol features a stable network topology and adaptability under signal time-varying fading, which effectively prolongs the lifetime of the network and reduces network packet loss, thus making it more applicable to the complex and variable environment characteristic of a coal mine face. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Data-Driven Design of Intelligent Wireless Networks: An Overview and Tutorial
Sensors 2016, 16(6), 790; https://doi.org/10.3390/s16060790 - 01 Jun 2016
Cited by 22
Abstract
Data science or “data-driven research” is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function [...] Read more.
Data science or “data-driven research” is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT
Sensors 2016, 16(5), 722; https://doi.org/10.3390/s16050722 - 18 May 2016
Cited by 14
Abstract
Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we [...] Read more.
Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
CoR-MAC: Contention over Reservation MAC Protocol for Time-Critical Services in Wireless Body Area Sensor Networks
Sensors 2016, 16(5), 656; https://doi.org/10.3390/s16050656 - 09 May 2016
Cited by 16
Abstract
Reserving time slots for urgent data, such as life-critical information, seems to be very attractive to guarantee their deadline requirements in wireless body area sensor networks (WBASNs). On the other hand, this reservation imposes a negative impact on performance for the utilization of [...] Read more.
Reserving time slots for urgent data, such as life-critical information, seems to be very attractive to guarantee their deadline requirements in wireless body area sensor networks (WBASNs). On the other hand, this reservation imposes a negative impact on performance for the utilization of a channel. This paper proposes a new channel access scheme referred to as the contention over reservation MAC (CoR-MAC) protocol for time-critical services in wireless body area sensor networks. CoR-MAC uses the dual reservation; if the reserved time slots are known to be vacant, other nodes can access the time slots by contention-based reservation to maximize the utilization of a channel and decrease the delay of the data. To measure the effectiveness of the proposed scheme against IEEE 802.15.4 and IEEE 802.15.6, we evaluated their performances with various performance indexes. The CoR-MAC showed 50% to 850% performance improvement in terms of the delay of urgent and time-critical data according to the number of nodes. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
TTEO (Things Talk to Each Other): Programming Smart Spaces Based on IoT Systems
Sensors 2016, 16(4), 467; https://doi.org/10.3390/s16040467 - 01 Apr 2016
Cited by 7
Abstract
The Internet of Things allows things in the world to be connected to each other and enables them to automate daily tasks without human intervention, eventually building smart spaces. This article demonstrates a prototype service based on the Internet of Things, TTEO (Things [...] Read more.
The Internet of Things allows things in the world to be connected to each other and enables them to automate daily tasks without human intervention, eventually building smart spaces. This article demonstrates a prototype service based on the Internet of Things, TTEO (Things Talk to Each Other). We present the full details on the system architecture and the software platforms for IoT servers and devices, called Mobius and &Cube, respectively, complying with the globally-applicable IoT standards, oneM2M, a unique identification scheme for a huge number of IoT devices, and service scenarios with an intuitive smartphone app. We hope that our approach will help developers and lead users for IoT devices and application services to establish an emerging IoT ecosystem, just like the ecosystem for smartphones and mobile applications. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
SmartPort: A Platform for Sensor Data Monitoring in a Seaport Based on FIWARE
Sensors 2016, 16(3), 417; https://doi.org/10.3390/s16030417 - 22 Mar 2016
Cited by 16
Abstract
Seaport monitoring and management is a significant research area, in which infrastructure automatically collects big data sets that lead the organization in its multiple activities. Thus, this problem is heavily related to the fields of data acquisition, transfer, storage, big data analysis and [...] Read more.
Seaport monitoring and management is a significant research area, in which infrastructure automatically collects big data sets that lead the organization in its multiple activities. Thus, this problem is heavily related to the fields of data acquisition, transfer, storage, big data analysis and information visualization. Las Palmas de Gran Canaria port is a good example of how a seaport generates big data volumes through a network of sensors. They are placed on meteorological stations and maritime buoys, registering environmental parameters. Likewise, the Automatic Identification System (AIS) registers several dynamic parameters about the tracked vessels. However, such an amount of data is useless without a system that enables a meaningful visualization and helps make decisions. In this work, we present SmartPort, a platform that offers a distributed architecture for the collection of the port sensors’ data and a rich Internet application that allows the user to explore the geolocated data. The presented SmartPort tool is a representative, promising and inspiring approach to manage and develop a smart system. It covers a demanding need for big data analysis and visualization utilities for managing complex infrastructures, such as a seaport. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Lightweight CoAP-Based Bootstrapping Service for the Internet of Things
Sensors 2016, 16(3), 358; https://doi.org/10.3390/s16030358 - 11 Mar 2016
Cited by 20
Abstract
The Internet of Things (IoT) is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these [...] Read more.
The Internet of Things (IoT) is becoming increasingly important in several fields of industrial applications and personal applications, such as medical e-health, smart cities, etc. The research into protocols and security aspects related to this area is continuously advancing in making these networks more reliable and secure, taking into account these aspects by design. Bootstrapping is a procedure by which a user obtains key material and configuration information, among other parameters, to operate as an authenticated party in a security domain. Until now solutions have focused on re-using security protocols that were not developed for IoT constraints. For this reason, in this work we propose a design and implementation of a lightweight bootstrapping service for IoT networks that leverages one of the application protocols used in IoT : Constrained Application Protocol (CoAP). Additionally, in order to provide flexibility, scalability, support for large scale deployment, accountability and identity federation, our design uses technologies such as the Extensible Authentication Protocol (EAP) and Authentication Authorization and Accounting (AAA). We have named this service CoAP-EAP. First, we review the state of the art in the field of bootstrapping and specifically for IoT. Second, we detail the bootstrapping service: the architecture with entities and interfaces and the flow operation. Third, we obtain performance measurements of CoAP-EAP (bootstrapping time, memory footprint, message processing time, message length and energy consumption) and compare them with PANATIKI. The most significant and constrained representative of the bootstrapping solutions related with CoAP-EAP. As we will show, our solution provides significant improvements, mainly due to an important reduction of the message length. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessArticle
Leasing-Based Performance Analysis in Energy Harvesting Cognitive Radio Networks
Sensors 2016, 16(3), 305; https://doi.org/10.3390/s16030305 - 27 Feb 2016
Cited by 8
Abstract
In this paper, we consider an energy harvesting cognitive radio network (CRN), where both of primary user (PU) and secondary user (SU) are operating in time slotted mode, and the SU powered exclusively by the energy harvested from the radio signal of the [...] Read more.
In this paper, we consider an energy harvesting cognitive radio network (CRN), where both of primary user (PU) and secondary user (SU) are operating in time slotted mode, and the SU powered exclusively by the energy harvested from the radio signal of the PU. The SU can only perform either energy harvesting or data transmission due to the hardware limitation. In this case, the entire time-slot is segmented into two non-overlapping fractions. During the first sub-timeslot, the SU can harvest energy from the ambient radio signal when the PU is transmitting. In order to obtain more revenue, the PU leases a portion of its time to SU, while the SU can transmit its own data by using the harvested energy. According to convex optimization, we get the optimal leasing time to maximize the SU’s throughput while guaranteeing the quality of service (QoS) of PU. To evaluate the performance of our proposed spectrum leasing scheme, we compare the utility of PU and the energy efficiency ratio of the entire networks in our framework with the conventional strategies respectively. The numerical simulation results prove the superiority of our proposed spectrum leasing scheme. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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Open AccessBrief Report
Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges
Sensors 2016, 16(2), 215; https://doi.org/10.3390/s16020215 - 06 Feb 2016
Cited by 24
Abstract
The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive [...] Read more.
The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. Full article
(This article belongs to the Special Issue Intelligent Internet of Things (IoT) Networks)
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