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Future Internet
Special Issues
Big Data and Internet of Thing
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Big Data and Internet of Thing

A special issue of Future Internet (ISSN 1999-5903).

Deadline for manuscript submissions: closed (15 March 2018) | Viewed by 81959

Special Issue Editors

Dr. Simon Fong

E-Mail Website
Guest Editor
Department of Computer and Information Science, University of Macau, Room 4023, E11, FST Building, Taipa, Macau 999078, China
Interests: data stream mining; big data; advanced analytics; bio-inspired optimization algorithms and applications; business intelligence; e-commerce; biomedical applications; wireless sensor networks
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sabah Mohammed

E-Mail Website
Guest Editor
Department of Computer Science, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
Interests: artificial intelligence; ambient intelligence; decision support systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is a platform and a phenomenon that allows everything to process information, communicate data, analyze context collaboratively, and is in the service or individuals, organizations, and businesses. In the process of doing so, a large amount of data with different formats and content should be efficiently processed, quickly and intelligently, through advanced algorithms, techniques, models, and tools. This new paradigm is enabled by the maturity of several different technologies, including the Internet, wireless communication, cloud computing, sensors, big data analytics, and machine learning algorithms.

Big data is another paradigm to describe the processing of data to have it “make sense” to people using IoT. Big data has five characteristics: Volume, velocity, variety, veracity, and value. There are reports that businesses and research communities equipped with big data skills can provide additional incentives, opportunities, funding, and innovation to their long-term strategies. The new knowledge, tools, practices, and infrastructure produced will enable breakthrough discoveries and innovation in physical science, engineering, mobile services, medicine, business, education, Earth science, security, and risk analysis.

Coupling IoT and big data will provide new synergies in all aspects, including technological advances, innovative ideas, intelligent services, smart cities incentives, and useful applications. IoT that serves as data collection platforms, and big data, which is the gold mine at the backend, are awaiting big data analytics to discover valuable insights. These two areas of IoT and big data complement each other, working hand-in-hand naturally, enabling new services and applications for improving our daily lives, as well as for better city planning and disaster and emergency control.

The aim of this Special Issue is to compile and publish novel ideas relating to the areas of IoT and/or big data, especially on new applications and related technology when these two fields fuse. We would like to solicit contributions from researchers from different disciplines, industrial practitioners, government agencies, and academia to discuss new ideas, research questions, recent results, and future challenges in this converging R&D field of IoT and big data. Topics including, but not limited to, the following are sought for submission.

  • Big Data fundamentals - Services Computing, Techniques, Recommendations and Frameworks
  • Modelling, Experiments, Sharing Technologies & Platforms
  • SQL/NoSQL databases, Data Processing Techniques, Visualization and Modern Technologies
  • Analytics, Intelligence and Knowledge Engineering
  • Data Centred Enabled Technologies
  • Sensor, Wireless Technologies, APIs
  • Data Management for Large Data
  • Security, Privacy and Risk
  • Software Frameworks (MapReduce, Spark, etc.) and Simulations
  • Volume, Velocity, Variety, Veracity and Value
  • Social Science and Implications for Big Data
  • Big Data as a Service (BDaaS) including Frameworks, Empirical Approaches and Data Processing Techniques
  • Big Data Algorithm, Methodology, Business Models and Challenges
  • Wireless Systems and Applications
  • Software Engineering for Big Data Analytics
  • Smart City and Transportation
  • Large-scale Information Systems and Applications
  • Energy, Environment and Natural Science Applications
  • Social Networks Analysis, Media and e-Government
  • Risk Modelling, Simulation, Legal Challenges
  • Open data: Issues, Services and Solutions
  • Case Studies of Real Adoption
  • Healthcare Services and Health Informatics
  • Cancer and Tumour Studies with Big Data
  • Data and Knowledge Management
  • Context-awareness and Location-awareness
  • Security, Privacy and Trust
  • Performance Evaluation and Modelling
  • Machine to Machine Communications
  • Intelligent Systems for IoT and Services Computing
  • Energy Efficiency
  • Social Implications for IoT
  • Pattern Recognition and Behavioral Investigations for Vehicles, Green Systems and Smart City
  • Artificial Intelligence
  • Internet of Things
  • Sensors Technologies

Associate Prof. Simon James Fong
Prof. Sabah Mohammed
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 submissions that pass pre-check are 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. Future Internet is an international peer-reviewed open access monthly 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 1600 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.



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Published Papers (10 papers)

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Research

17 pages, 1503 KiB  
Article
Certificateless Provable Group Shared Data Possession with Comprehensive Privacy Preservation for Cloud Storage
by Hongbin Yang, Shuxiong Jiang, Wenfeng Shen and Zhou Lei
Future Internet 2018, 10(6), 49; https://doi.org/10.3390/fi10060049 - 7 Jun 2018
Cited by 16 | Viewed by 4567
Abstract
Provable Data Possession (PDP) protocol makes it possible for cloud users to check whether the cloud servers possess their original data without downloading all the data. However, most of the existing PDP schemes are based on either public key infrastructure (PKI) or identity-based [...] Read more.
Provable Data Possession (PDP) protocol makes it possible for cloud users to check whether the cloud servers possess their original data without downloading all the data. However, most of the existing PDP schemes are based on either public key infrastructure (PKI) or identity-based cryptography, which will suffer from issues of expensive certificate management or key escrow. In this paper, we propose a new construction of certificateless provable group shared data possession (CL-PGSDP) protocol by making use of certificateless cryptography, which will eliminate the above issues. Meanwhile, by taking advantage of zero-knowledge protocol and randomization method, the proposed CL-PGSDP protocol leaks no information of the stored data and the group user’s identity to the verifiers during the verifying process, which is of the property of comprehensive privacy preservation. In addition, our protocol also supports efficient user revocation from the group. Security analysis and experimental evaluation indicate that our CL-PGSDP protocol provides strong security with desirable efficiency. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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20 pages, 4448 KiB  
Article
Test Bed of Semantic Interaction of Smart Objects in the Web of Things
by Santiago Guerrero-Narváez, Miguel-Ángel Niño-Zambrano, Dalila-Jhoana Riobamba-Calvache and Gustavo-Adolfo Ramírez-González
Future Internet 2018, 10(5), 42; https://doi.org/10.3390/fi10050042 - 9 May 2018
Cited by 1 | Viewed by 4927
Abstract
Semantic interaction in the Internet of Things (IoT) is an important concept within current IoT development, given that smart things require further autonomy with greater processing, storage, and communication capacities. The problem is now becoming one of how to get these things to [...] Read more.
Semantic interaction in the Internet of Things (IoT) is an important concept within current IoT development, given that smart things require further autonomy with greater processing, storage, and communication capacities. The problem is now becoming one of how to get these things to interact and collaborate with each other; to form intelligent environments amongst themselves and thus generate better services for users. This article explores a solution approach that consists in providing collaborative behavior to smart things, through the incorporation of an ontology and an architecture. It makes possible things that can communicate and collaborate with each other, allowing the generation of new services of interaction according to user needs. For this task, a real test bed of smart things was created, in which the proposed solution was deployed (Smart Room). Finally, it was concluded that the creation of these types of test bed is feasible, taking into account that response times and the information delivered by the different managed processes are acceptable. New challenges were encountered, however, such as problems of critical region in test beds with conflicting services and management of multiple users. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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14 pages, 1256 KiB  
Article
How Data Will Transform Industrial Processes: Crowdsensing, Crowdsourcing and Big Data as Pillars of Industry 4.0
by Virginia Pilloni
Future Internet 2018, 10(3), 24; https://doi.org/10.3390/fi10030024 - 1 Mar 2018
Cited by 116 | Viewed by 15023
Abstract
We are living in the era of the fourth industrial revolution, namely Industry 4.0. This paper presents the main aspects related to Industry 4.0, the technologies that will enable this revolution, and the main application domains that will be affected by it. The [...] Read more.
We are living in the era of the fourth industrial revolution, namely Industry 4.0. This paper presents the main aspects related to Industry 4.0, the technologies that will enable this revolution, and the main application domains that will be affected by it. The effects that the introduction of Internet of Things (IoT), Cyber-Physical Systems (CPS), crowdsensing, crowdsourcing, cloud computing and big data will have on industrial processes will be discussed. The main objectives will be represented by improvements in: production efficiency, quality and cost-effectiveness; workplace health and safety, as well as quality of working conditions; products’ quality and availability, according to mass customisation requirements. The paper will further discuss the common denominator of these enhancements, i.e., data collection and analysis. As data and information will be crucial for Industry 4.0, crowdsensing and crowdsourcing will introduce new advantages and challenges, which will make most of the industrial processes easier with respect to traditional technologies. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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30 pages, 1400 KiB  
Article
A Virtual Learning Architecture Enhanced by Fog Computing and Big Data Streams
by Riccardo Pecori
Future Internet 2018, 10(1), 4; https://doi.org/10.3390/fi10010004 - 3 Jan 2018
Cited by 44 | Viewed by 12860
Abstract
In recent years, virtual learning environments are gaining more and more momentum, considering both the technologies deployed in their support and the sheer number of terminals directly or indirectly interacting with them. This essentially means that every day, more and more smart devices [...] Read more.
In recent years, virtual learning environments are gaining more and more momentum, considering both the technologies deployed in their support and the sheer number of terminals directly or indirectly interacting with them. This essentially means that every day, more and more smart devices play an active role in this exemplary Web of Things scenario. This digital revolution, affecting education, appears clearly intertwined with the earliest forecasts of the Internet of Things, envisioning around 50 billions heterogeneous devices and gadgets to be active by 2020, considering also the deployment of the fog computing paradigm, which moves part of the computational power to the edge of the network. Moreover, these interconnected objects are expected to produce more and more significant streams of data, themselves generated at unprecedented rates, sometimes to be analyzed almost in real time. Concerning educational environments, this translates to a new type of big data stream, which can be labeled as educational big data streams. Here, pieces of information coming from different sources (such as communications between students and instructors, as well as students’ tests, etc.) require accurate analysis and mining techniques in order to retrieve fruitful and well-timed insights from them. This article presents an overview of the current state of the art of virtual learning environments and their limitations; then, it explains the main ideas behind the paradigms of big data streams and of fog computing, in order to introduce an e-learning architecture integrating both of them. Such an action aims to enhance the ability of virtual learning environments to be closer to the needs of all the actors in an educational scenario, as demonstrated by a preliminary implementation of the envisioned architecture. We believe that the proposed big stream and fog-based educational framework may pave the way towards a better understanding of students’ educational behaviors and foster new research directions in the field. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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4548 KiB  
Article
Proposed Fuzzy-NN Algorithm with LoRaCommunication Protocol for Clustered Irrigation Systems
by Sotirios Kontogiannis, George Kokkonis, Soultana Ellinidou and Stavros Valsamidis
Future Internet 2017, 9(4), 78; https://doi.org/10.3390/fi9040078 - 7 Nov 2017
Cited by 13 | Viewed by 6880
Abstract
Modern irrigation systems utilize sensors and actuators, interconnected together as a single entity. In such entities, A.I. algorithms are implemented, which are responsible for the irrigation process. In this paper, the authors present an irrigation Open Watering System (OWS) architecture that spatially clusters [...] Read more.
Modern irrigation systems utilize sensors and actuators, interconnected together as a single entity. In such entities, A.I. algorithms are implemented, which are responsible for the irrigation process. In this paper, the authors present an irrigation Open Watering System (OWS) architecture that spatially clusters the irrigation process into autonomous irrigation sections. Authors’ OWS implementation includes a Neuro-Fuzzy decision algorithm called FITRA, which originates from the Greek word for seed. In this paper, the FITRA algorithm is described in detail, as are experimentation results that indicate significant water conservations from the use of the FITRA algorithm. Furthermore, the authors propose a new communication protocol over LoRa radio as an alternative low-energy and long-range OWS clusters communication mechanism. The experimental scenarios confirm that the FITRA algorithm provides more efficient irrigation on clustered areas than existing non-clustered, time scheduled or threshold adaptive algorithms. This is due to the FITRA algorithm’s frequent monitoring of environmental conditions, fuzzy and neural network adaptation as well as adherence to past irrigation preferences. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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2055 KiB  
Article
A Design Space for Virtuality-Introduced Internet of Things
by Kota Gushima and Tatsuo Nakajima
Future Internet 2017, 9(4), 60; https://doi.org/10.3390/fi9040060 - 2 Oct 2017
Cited by 8 | Viewed by 7825
Abstract
Augmented reality (AR) and virtual reality (VR) technologies have been dramatically expanded in recent years. In the near future, we expect that diverse digital services that employ Internet of Things (IoT) technologies enhanced with AR and VR will become more popular. Advanced information [...] Read more.
Augmented reality (AR) and virtual reality (VR) technologies have been dramatically expanded in recent years. In the near future, we expect that diverse digital services that employ Internet of Things (IoT) technologies enhanced with AR and VR will become more popular. Advanced information technologies will enable the physical world to be fused with the virtual world. These digital services will be advanced via virtuality, which means that things that do not physically exist make people believe in their existence. We propose a design space for digital services that are enhanced via virtuality based on insights extracted from three case studies that we have developed and from discussions in focus groups that analyze how existing commercial IoT products proposed in a commercial crowdfunding platform, Kickstarter, could be enhanced through virtuality. The derived design space offers three dimensions to design a digital service to fuse IoT technologies with virtuality: (1) Taxonomy of IoT; (2) Visualizing Level, and (3) Virtuality Level. The design space will help IoT-based digital service designers to develop advanced future IoT products that incorporate virtuality. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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727 KiB  
Article
Cost-Aware IoT Extension of DISSECT-CF
by Andras Markus, Attila Kertesz and Gabor Kecskemeti
Future Internet 2017, 9(3), 47; https://doi.org/10.3390/fi9030047 - 14 Aug 2017
Cited by 11 | Viewed by 6375
Abstract
In the age of the Internet of Things (IoT), more and more sensors, actuators and smart devices get connected to the network. Application providers often combine this connectivity with novel scenarios involving cloud computing. Before implementing changes in these large-scale systems, an in-depth [...] Read more.
In the age of the Internet of Things (IoT), more and more sensors, actuators and smart devices get connected to the network. Application providers often combine this connectivity with novel scenarios involving cloud computing. Before implementing changes in these large-scale systems, an in-depth analysis is often required to identify governance models, bottleneck situations, costs and unexpected behaviours. Distributed systems simulators help in such analysis, but they are often problematic to apply in this newly emerging domain. For example, most simulators are either too detailed (e.g., need extensive knowledge on networking), or not extensible enough to support the new scenarios. To overcome these issues, we discuss our IoT cost analysis oriented extension of DIScrete event baSed Energy Consumption simulaTor for Clouds and Federations (DISSECT-CF). Thus, we present an in-depth analysis of IoT and cloud related pricing models of the most widely used commercial providers. Then, we show how the fundamental properties (e.g., data production frequency) of IoT entities could be linked to the identified pricing models. To allow the adoption of unforeseen scenarios and pricing schemes, we present a declarative modelling language to describe these links. Finally, we validate our extensions by analysing the effects of various identified pricing models through five scenarios coming from the field of weather forecasting. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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340 KiB  
Article
Digital Pre-Distortion of Carrier Frequency Offset for Reliable Wi-Fi Enabled IoTs
by Il-Gu Lee
Future Internet 2017, 9(3), 46; https://doi.org/10.3390/fi9030046 - 9 Aug 2017
Cited by 2 | Viewed by 6223
Abstract
The Internet of Things (IoTs) will change the requirements for wireless connectivity significantly, mainly with regard to service coverage, data rate, and energy efficiency. Therefore, to improve robustness and reliability, WiFi-enabled IoT devices have been developed to use narrowband communication. However, narrowband transmission [...] Read more.
The Internet of Things (IoTs) will change the requirements for wireless connectivity significantly, mainly with regard to service coverage, data rate, and energy efficiency. Therefore, to improve robustness and reliability, WiFi-enabled IoT devices have been developed to use narrowband communication. However, narrowband transmission in WiFi such as IEEE 802.11ah causes relatively higher frequency error due to the reduced subcarrier space, which is larger than legacy wireless local area networks (WLANs) in 2.4/5 GHz frequencies. In a direct conversion receiver, this error degrades the signal quality due to the presence of direct current (DC) offset cancellation circuits. In this paper, a digital carrier frequency offset (CFO) predistortion scheme is proposed for a reliable communication link in dense networks. Evaluation results demonstrate that the proposed scheme can improve received signal quality in terms of packet error rate and error vector magnitude. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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462 KiB  
Article
Interference-Aware Opportunistic Dynamic Energy Saving Mechanism for Wi-Fi Enabled IoTs
by Il-Gu Lee
Future Internet 2017, 9(3), 38; https://doi.org/10.3390/fi9030038 - 18 Jul 2017
Cited by 3 | Viewed by 5296
Abstract
The wireless local area network (WLAN) is one of the most popular wireless technologies offering connectivity today, and one of the candidates for the internet of things (IoTs). However, WLAN’s inefficiency in terms of complexity and relatively large power consumption compared with other [...] Read more.
The wireless local area network (WLAN) is one of the most popular wireless technologies offering connectivity today, and one of the candidates for the internet of things (IoTs). However, WLAN’s inefficiency in terms of complexity and relatively large power consumption compared with other wireless standards has been reported as a major barrier for IoTs applications. This paper proposes an interference-aware opportunistic dynamic energy saving mechanism to improve energy efficiency for Wi-Fi enabled IoTs. The proposed scheme optimizes operating clock frequencies adaptively for signal processing when the mobile station transmits packets in partial sub-channels. Evaluation results demonstrate that the proposed scheme improves energy efficiency by approximately 34%. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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2702 KiB  
Article
Design and Development of a Real-Time Monitoring System for Multiple Lead–Acid Batteries Based on Internet of Things
by Ashish Rauniyar, Mohammad Irfan, Oka Danil Saputra, Jin Woo Kim, Ah Ra Lee, Jae Min Jang and Soo Young Shin
Future Internet 2017, 9(3), 28; https://doi.org/10.3390/fi9030028 - 29 Jun 2017
Cited by 18 | Viewed by 10474
Abstract
In this paper, real-time monitoring of multiple lead-acid batteries based on Internet of things is proposed and evaluated. Our proposed system monitors and stores parameters that provide an indication of the lead acid battery’s acid level, state of charge, voltage, current, and the [...] Read more.
In this paper, real-time monitoring of multiple lead-acid batteries based on Internet of things is proposed and evaluated. Our proposed system monitors and stores parameters that provide an indication of the lead acid battery’s acid level, state of charge, voltage, current, and the remaining charge capacity in a real-time scenario. To monitor these lead–acid battery parameters, we have developed a data acquisition system by building an embedded system, i.e., dedicated hardware and software. The wireless local area network is used as the backbone network. The information collected from all the connected battery clients in the system is analyzed in an asynchronous transmission control protocol/user datagram protocol-based C♯ server program running on a personal computer (server) to determine important parameters like the state of charge of the individual battery, and if required, appropriate action can be taken in advance to prevent excessive impairment to the battery. Further, data are also displayed on an Android mobile device and are stored in an SQL server database. We have developed a real prototype to devise an end product for our proposed system. Full article
(This article belongs to the Special Issue Big Data and Internet of Thing)
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