Generation Internet Of Things Research Articles

Harvesting Devices’ Heterogeneous Energy Profiles and QoS Requirements in IoT: WPT-NOMA vs BAC-NOMA

The next generation Internet of Things (IoT) exhibits a unique feature that IoT devices have different energy profiles and quality of service (QoS) requirements. In this paper, two energy and spectrally efficient transmission strategies, namely wireless power transfer assisted non-orthogonal multiple access (WPT-NOMA) and backscatter communication (Back-Com) assisted NOMA (BAC-NOMA), are proposed by utilizing this feature of IoT and employing spectrum and energy cooperation among the devices. In particular, the use of NOMA ensures that the devices with different QoS requirements can share the same spectrum, and WPT and Back-Com are employed to utilize the cooperation among the devices with different energy profiles, which avoids the use of a dedicated power beacon. Furthermore, for the proposed WPT-NOMA scheme, the application of hybrid successive interference cancelation (SIC) decoding order is also considered, and analytical results are developed to demonstrate that WPT-NOMA can avoid outage probability error floors and realize the full diversity gain. Unlike WPT-NOMA, BAC-NOMA suffers from an outage probability error floor, and the asymptotic behavior of this error floor is analyzed in the paper by applying the extreme value theory. In addition, the effect of a unique feature of BAC-NOMA, i.e., employing one device's signal as the carrier signal for another device, is studied, and its impact on the diversity gain is revealed. Simulation results are also provided to compare the performance of the proposed strategies and verify the developed analytical results.

Artificial Intelligence-Based Sensors for Next Generation IoT Applications: A Review

Sensors play a vital role in our daily lives and are an essential component for Internet of Things (IoT) based systems as they enable the IoT to collect data to take smart and intelligent decisions. Recent advances in IoT systems, applications, and technologies, including industrial Cyber-Physical Systems (CPSs), are being supported by a wide range of different types of sensors based on artificial intelligence (AI). These smart AI-based sensors are typically characterized by onboard intelligence and have the ability to communicate collaboratively or through the Internet. To achieve the high level of automation required in today’s smart IoT applications, sensors incorporated into nodes must be efficient, intelligent, context-aware, reliable, accurate, and connected. Such sensors must also be robust, safety- and privacy-aware for users interacting with them. Sensors leveraging advanced AI technologies, new capabilities have recently emerged which have the potential to detect, identify, and avoid performance degradation and discover new patterns. Along with knowledge from complex sensor datasets, they can promote product innovation, improve operation level, and open up novel business models. We review sensors, smart data processing, communication protocol, and artificial intelligence which will enable the deployment of AI-based sensors for next-generation IoT applications.

Multi-Layer Blockchain-Based Security Architecture for Internet of Things.

The proliferation of smart devices in the Internet of Things (IoT) networks creates significant security challenges for the communications between such devices. Blockchain is a decentralized and distributed technology that can potentially tackle the security problems within the 5G-enabled IoT networks. This paper proposes a Multi layer Blockchain Security model to protect IoT networks while simplifying the implementation. The concept of clustering is utilized in order to facilitate the multi-layer architecture. The K-unknown clusters are defined within the IoT network by applying techniques that utillize a hybrid Evolutionary Computation Algorithm while using Simulated Annealing and Genetic Algorithms. The chosen cluster heads are responsible for local authentication and authorization. Local private blockchain implementation facilitates communications between the cluster heads and relevant base stations. Such a blockchain enhances credibility assurance and security while also providing a network authentication mechanism. The open-source Hyperledger Fabric Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The simulation results demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported approaches. The proposed lightweight blockchain model is also shown to be better suited to balance network latency and throughput as compared to a traditional global blockchain.

Plug-in over Plug-in Evaluation in Heterogeneous 5G Enabled Networks and Beyond

With the cool upcoming wave of 5G, currently, the networking and telecommunication industries are facing various digital transformations, which are changing the very fundamental nature of the existing network management infrastructure. Besides the Internet of Things (IoT) domain, we also notice that the 5G network in itself is composed of millions of heterogeneous physical entities and nodes, multiple domains, complex protocols and technologies, different gateways, and so on. This heterogeneity imposes critical impacts on the application specific quality of service (QoS) requirements, performance and utilization of network resources, and data and user security. In order to alleviate the above impacts, researchers propose to use different technologies such as software-defined networking, network function virtualization, blockchain, and artificial intelligence in 5G-enabled IoT networking. We notice that the layers over layers (of protocols and technologies) act like a plug-in over plug-in (PoP) in the network in order to accomplish various aims, including meeting QoS demands, enhancing security, load balancing, and so on. On one hand, we agree that this integration of different technologies in 5G networks bring numerous advantages, but on the other hand, we realize that this has posed a lot of unique critical issues in modern 5G network management. In this article, we point out that this straightforward approach of PoP is eventually not a healthy approach for network transformation. In this regard, using open source MANO (OSM), we provide a proof of concept (PoC) to show that at varying degrees of heterogeneity, PoP adds the delay in the VNF deployment process and further impacts the VIM CPU performance. This eventually affects the QoS requirements of IoT nodes or applications. Following this, we propose a high-level holistic approach that helps to alleviate the PoP issue. Finally, in this context, we also discuss the associated challenges and research opportunities.

Shared-Aperture Slot-Based Sub-6-GHz and mm-Wave IoT Antenna for 5G Applications

In this article, a square concentric slot-based antenna is presented for sub-6-GHz and millimeter-wave (mm-wave) 5G-enabled Internet of Things (IoT) devices. The proposed antenna design exhibits an octaband operation for the sub-6-GHz spectrum while resonates at 28 GHz as well. The unique feature of the proposed design is the shared radiating aperture for both sub-6-GHz as well as mm-wave bands. The antenna consists of three concentric square slots etched out from a ground (GND) plane dimensions of 50 × 50 × 0.508 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . For the sub-6-GHz band, the antenna is excited by a single open-ended microstrip transmission line, while 1 × 8 power divider (PD) is used to excite the planar connected antenna arrays at the mm-wave band. The proposed antenna covers the following eight bands for sub-6-GHz operation: 1.05-1.23 GHz, 1.4-1.55 GHz, 1.9-2.3 GHz, 2.3-2.7 GHz, 3.1-3.7 GHz, 4.04-4.511 GHz, 4.83-5.2 GHz, and 5.66-6.151 GHz. The mm-wave band covers 27.4-28.4 GHz with the minimum bandwidth (BW) of 1 GHz. The proposed antenna covers most of the IoT bands, thus, it is a potential candidate for next-generation 5G-enabled IoT devices.

Business model innovation through the application of the Internet-of-Things: A comparative analysis

The Internet-of-Things (IoT) empowers remote monitoring and management of the performance of machines, vehicles, processes, etc., which facilitate service business models. However, companies in emerging and transitional economies, in particular, face challenges when applying IoT, not only related to the use of technology, but especially regarding the need for a new business model. The main goal of this paper is to better understand emerging IoT business models in Vietnam through identifying and interpreting business model design options and choices. The case studies and their commonalities are used to perform a morphological analysis and create a generic IoT business model providing business model alternatives for each of the four business model dimensions. The research provides insights into the commonalities and discrepancies of IoT-based business models. Also, it provides a novel application of morphological analysis to business model innovation to create a generic business model for IoT applications in emerging markets.

Efficient and Privacy Preserving Video Transmission in 5G-Enabled IoT Surveillance Networks: Current Challenges and Future Directions

Vision sensors in Internet of Things (IoT)-connected smart cities play a vital role in the exponential growth of video data, thereby making its analysis and storage comparatively tough and challenging. Those sensors continuously generate data for 24 hours, which requires huge storage resources, dedicated networks for sharing with data centers, and most importantly, it makes browsing, retrieval, and event searching a difficult and time-consuming job. Video summarization (VS) is a promising direction toward a solution to these problems by analyzing the visual contents acquired from a vision sensor and prioritizing them based on events, saliency, person's appearance, and so on. However, the current VS literature still lacks focus on resource-constrained devices that can summarize data over the edge and upload it to data repositories efficiently for instant analysis. Therefore, in this article, we carry out a survey of functional VS methods to understand their pros and cons for resource-constrained devices, with the ambition to provide a compact tutorial to the community of researchers in the field. Further, we present a novel saliency-aware VS framework, incorporating 5G-enabled IoT devices, which keeps only important data, thereby saving storage resources and providing representative data for immediate exploration. Keeping privacy of data as a second priority, we intelligently encrypt the salient frames over resource-constrained devices before transmission over the 5G network. The reported experimental results show that our proposed framework has additional benefits of faster transmission (1.8~13.77 percent frames of a lengthy video are considered for transmission), reduced bandwidth, and real-time processing compared to state-of-the-art methods in the field.

Architecture design of monitoring and controlling of IoT-based aquaponics system powered by solar energy

The demand for food is persistently increasing; the world is facing cannot be addressed with the land’s additional natural resources and exploitation. Currently, the agricultural industry is the world’s largest water user and consumes about 70% of the water in different processes. In this food and environmental crisis, the new methods for growing plants in the agricultural domain are various; one of these methods is aquaponics which is a sustainable agriculture system that combines two names: Aquaculture, which is the farming of fish and Hydroponic which is the cultivation of plants (Off-soil) using water enriched with mineral materials. Aquaponics comes as a solution to enhance farming and agriculture productivity. The attention towards the aquaponics system is increasing due to its high efficiency, availability, and fewer resources consumption. However, there is intensive automation, monitoring, and control requirement for a smart aquaponics system. To enhance the productivity of aquaponics, it is required to utilize IoT-based technologies and artificial intelligence (AI) algorithms. The main aim of this paper at hand consists of proposing a new contribution based on the Internet of Things (IoT) solution that could control and monitor water quality and environmental parameters by using the maximum of sensors(water level, water temperature, electrical conductivity, CO2, Taux Ammonia Nitrogen(TAN), etc.), and actuators (water pump, etc.,) in aquaponics farming. This paper provides an innovative solution based on an interoperable, secure, scalable, low-cost, fully self-powered, flexible, reliable and generic IoT architecture that meets the requirements of aquaponics.

On the Security of a Secure and Lightweight Authentication Scheme for Next Generation IoT Infrastructure

In recent years, the Internet of things (IoT) has become an encouraging communication paradigm that has numerous applications including smart city, smart home and intelligent transportation system. The information sensed by several IoT smart devices can be security stored at the (cloud) servers. An external user, being a client, can access the services from a server for the sensing information, provided that a mutual authentication happens among them. Using the established session key among the user and the server, encrypted information with the help of session key can be delivered to the user by the server securely. Recently, Rana et al. proposed a smart-card based remote user authentication scheme using user password. In this comment paper, we carefully analyzed the scheme of Rana et al. and tracked down that their scheme is insecure against serious attacks, including stolen smart card attack, privileged-insider attack, user impersonation attack, password change attack and Ephemeral Secret Leakage (ESL) attack. Furthermore, their scheme does not preserve untraceability feature. To remedy these security pitfalls, we also provide some remedies that can help in building more secure and effective user authentication scheme to apply in securing next generation IoT infrastructure.

Modeling-framework for model-based software engineering of complex Internet of things systems.

Internet of things (IoT) systems are composed of variety of units from different domains. While developing a complete IoT system, different professionals from different domains may have to work in collaboration. In this paper we provide a framework which allows using discrete and continuous time modeling and simulation approaches in combination for IoT systems. The proposed framework demonstrates on how to model Ad-hoc and general IoT systems for software engineering purpose. We demonstrate that model-based software engineering on one hand can provide a common platform to overcome communication gaps among collaborating stakeholders whereas, on the other hand can model and integrate heterogeneous components of IoT systems. While modeling heterogeneous IoT systems, one of the major challenges is to apply continuous and discrete time modeling on intrinsically varying components of the system. Another difficulty may be how to compose these heterogeneous components into one whole system. The proposed framework provides a road-map to model discrete, continuous, Ad-hoc, general systems along with composition mechanism of heterogeneous subsystems. The framework uses a combination of Agent-based modeling, Aspect-oriented modeling, contract-based modeling and services-oriented modeling concepts. We used this framework to model a scenario example of a service-oriented IoT system as proof of concept. We analyzed our framework with existing systems and discussed it in details. Our framework provides a mechanism to model different viewpoints. The framework also enhances the completeness and consistency of the IoT software models.

Security in 5G-Enabled Internet of Things Communication: Issues, Challenges, and Future Research Roadmap

5G mobile communication systems promote the mobile network to not only interconnect people, but also interconnect and control the machine and other devices. 5G-enabled Internet of Things (IoT) communication environment supports a wide-variety of applications, such as remote surgery, self-driving car, virtual reality, flying IoT drones, security and surveillance and many more. These applications help and assist the routine works of the community. In such communication environment, all the devices and users communicate through the Internet. Therefore, this communication agonizes from different types of security and privacy issues. It is also vulnerable to different types of possible attacks (for example, replay, impersonation, password reckoning, physical device stealing, session key computation, privileged-insider, malware, man-in-the-middle, malicious routing, and so on). It is then very crucial to protect the infrastructure of 5G-enabled IoT communication environment against these attacks. This necessitates the researchers working in this domain to propose various types of security protocols under different types of categories, like key management, user authentication/device authentication, access control/user access control and intrusion detection. In this survey paper, the details of various system models (i.e., network model and threat model) required for 5G-enabled IoT communication environment are provided. The details of security requirements and attacks possible in this communication environment are further added. The different types of security protocols are also provided. The analysis and comparison of the existing security protocols in 5G-enabled IoT communication environment are conducted. Some of the future research challenges and directions in the security of 5G-enabled IoT environment are displayed. The motivation of this work is to bring the details of different types of security protocols in 5G-enabled IoT under one roof so that the future researchers will be benefited with the conducted work.

Performance analysis of access class barring for next generation IoT devices

Massively dense deployment of Internet of Things (IoT) devices has put a stringent requirement on cellular networks to provide convenient service for not only human type traffic (HTC) but also for bursty traffic for IoT devices. Any bottleneck in the random access process means the bottleneck of the entire system because it is the first step before scheduled access. Access class barring (ACB) scheme is one of the key schemes in long term evolution advanced (LTE-A) to control the congestion in a random access process in which the access of some devices is barred based on a parameter, ACB factor, to relieve the congestion. In this paper, we analyze the ACB factor and criteria of its selection as the optimal selection of the ACB factor is essential for the maximum throughput of the system. The metrics used in the analysis of the ACB factor are total service time (TST), access delay and maximum collision, success, and idle probabilities with fixed and optimal ACB factor. Simulation results in MATLAB provide the complete picture of the behavior of the ACB factor and its control, used in the random access process.

An Intelligent UAV based Data Aggregation Algorithm for 5G-enabled Internet of Things

Unmanned Aerial Vehicle (UAV) has become a significant part of 5G or beyond 5G (B5G) paradigm, and is used in various scenarios, including cargo delivery, agricultural application, event surveillance, etc. Although plenty of studies have been proposed on UAV-based data aggregation, how to ensure security and energy-efficiency of the data aggregation process in 5G-enabled Internet of Things (IoT) is an open problem. In this paper, we propose an Intelligent UAV-based Data Aggregation Algorithm, named IDAA for 5G-Enabled IoT. Specifically, IDAA applies v-Support Vector Regression (v-svr) to predict the data collection rate. Then, a security level based task decomposition mechanism is designed that allows UAVs to accept the tasks of corresponding security levels. Finally, energy efficient routes for UAV are planned utilizing a deep reinforcement learning method to achieve the trade-off between the sinking ratio and the energy cost. The theoretical analysis and simulation results indicate that (i) IDAA improves the security of data aggregation; and (ii) IDAA enables UAVs to collect more data and consume less energy compared with baseline strategies.

On-Demand Efficient Clustering for Next Generation IoT Applications: A Hybrid NN Approach

The internet-of-things(IoT) extends the traditional Internet and realizes the interconnection of all things in a smart way. With the rapid development of 5G and beyond communication technology, the number of users and demands for IoT applications has increased significantly along with resource constraints networking in the communication systems. The next generation IoT applications challenges these issue using smarter cooperative communication with large heterogeneous clusters along in par with traditional IoT systems. The proposed work illustrates a hybrid neural network (NN) model for dynamic clustering for efficient next generation IoT applications. A dynamic cluster model based on hybrid NN optimization is proposed along with the Gaussian copula technique for realizing the correlation between the clusters for efficient cooperative communication. The mathematical analysis and simulation results show that the model maximizes the amount of information in the cluster and balances the resource allocation among nodes to improve the life of the entire network.

Design, Resource Management, and Evaluation of Fog Computing Systems: A Survey

A steady increase in Internet-of-Things (IoT) applications needing large-scale computation and long-term storage has lead to an overreliance on cloud computing. The resulting network congestion in the cloud, coupled with the distance of cloud data centers from IoT, contributes to unreliable end-to-end response delay. Fog computing has been introduced as an alternative to cloud, providing low-latency service by bringing processing and storage resources to the network edge. In this survey, we sequentially present the phases required in the implementation and realization of practical fog computing systems: 1) design and dimensioning of a fog infrastructure; 2) fog resource provisioning for IoT application use and IoT resource allocation to fog; 3) installation of fog frameworks for fog resource management; and 4) evaluation of fog infrastructure through simulation and emulation. Our focus is on determining the implementation aspects required to build a practical large-scale fog computing infrastructure to support the general IoT landscape.

Pairing a Circular Economy and the 5G-Enabled Internet of Things: Creating a Class of ?Looping Smart Assets?

The increase in the world's population has led to a massive rise in human consumption of the planet's natural resources, well beyond their replacement rate. Traditional recycling concepts and methods are not enough to counter such effects. In this context, a circular economy (CE), that is, a restorative and regenerative by-design economy, can reform today's "take-make-dispose" economic model. On the other hand, the Internet of Things (IoT) continues to gradually transform our everyday lives, allowing for the introduction of novel types of services while enhancing legacy ones. Taking this as our motivation, in this article we analyze the CE/IoT interplay, indicating innovative ways in which this interaction can drastically affect products and services, their underlying business models, and the associated ecosystems. Moreover, we present an IoT architecture that enables smart object integration into the IoT ecosystem. The presented architecture integrates circularityenabling features by maximizing the exploitation of assets toward a new type of IoT ecosystem that is circular by design (CbD). Finally, we provide a proof-of-concept implementation and an application study of the proposed architecture and results regarding the applicability of the proposed approach for the telecommunications (telecom) sector.

A survey of IoT protocols and their security issues through the lens of a generic IoT stack

The Internet of things (IoT) is rapidly growing, and many security issues relate to its wireless technology. These security issues are challenging because IoT protocols are heterogeneous, suit different needs, and are used in different application domains. From this assessment, we identify the need to provide a homogeneous formalism applying to every IoT protocols. In this survey, we describe a generic approach with twofold challenges. The first challenge we tackle is the identification of common principles to define a generic approach to compare IoT protocol stack. We base the comparison on five different criteria: the range, the openness of the protocol, the interoperability, the topology and the security practices of these IoT protocols. The second challenge we consider is to find a generic way to describe fundamental IoT attacks regardless of the protocol used. This approach exposes similar attacks amongst different IoT protocols and is divided into three parts: attacks focusing on packets (passive and active cryptographic attacks), attacks focusing on the protocol (MITM, Flooding, Sybil, Spoofing, Wormhole attacks) and attacks focusing on the whole system (Sinkhole, Selective forwarding attacks). It also highlights which mechanisms are different between two protocols to make both of them vulnerable to an attack. Finally, we draw some lessons and perspectives from this transversal study.

Harvesting Devices' Heterogeneous Energy Profiles and QoS Requirements in IoT: WPT-NOMA vs BAC-NOMA

The next generation Internet of Things (IoT) exhibits a unique feature that IoT devices have different energy profiles and quality of service (QoS) requirements. In this paper, two energy and spectrally efficient transmission strategies, namely wireless power transfer assisted non-orthogonal multiple access (WPT-NOMA) and backscatter communication assisted NOMA (BAC-NOMA), are proposed by utilizing this feature of IoT and employing spectrum and energy cooperation among the devices. Furthermore, for the proposed WPT-NOMA scheme, the application of hybrid successive interference cancelation (SIC) is also considered, and analytical results are developed to demonstrate that WPT-NOMA can avoid outage probability error floors and realize the full diversity gain. Unlike WPT-NOMA, BAC-NOMA suffers from an outage probability error floor, and the asymptotic behaviour of this error floor is analyzed in the paper by applying the extreme value theory. In addition, the effect of a unique feature of BAC-NOMA, i.e., employing one device's signal as the carrier signal for another device, is studied, and its impact on the diversity gain is revealed. Simulation results are also provided to compare the performance of the proposed strategies and verify the developed analytical results.

Alleviating Heterogeneity in SDN-IoT Networks to Maintain QoS and Enhance Security

Software-defined networks (SDNs) offer unique and attractive solutions to solve challenging management issues in Internet of Things (IoT)-based large-scale multitechnological networks. SDN-IoT network collaboration is innovative and attractive but expected to be extremely heterogeneous in future generation IoT systems. For example, multitechnology network, network externality, and nodes heterogeneity in SDN-IoT may seriously affect the flow or application-specific quality-of-service (QoS) requirements. Furthermore, it highly influences security adoption in a network of interconnected IoT nodes. We observe that both QoS and security are interdependent and nonnegligible factors, thus we emphasize that in order to alleviate heterogeneity it is inevitable to study both these factors hand to hand (or vice versa ). With this aim, first, we discuss significant and reasonable cases to encourage researchers to study QoS and security integrally in order to alleviate heterogeneity at SDN-IoT control plane. Second, we propose a framework which successfully transforms the $m$ heterogeneous controllers to $n$ homogeneous controller groups. The key metric of our observation and analysis is the SDN controller’s response time. Following this, to validate our approach, we use the mathematical model and a proof of concept (PoC) in a virtual SDN ecosystem is demonstrated. From performance evaluation, we observe that the proposed framework significantly alleviates heterogeneity which helps to maintain QoS and enhance security. This fundamental analysis will enable network security individuals to deal heterogeneity, QoS, and security, of SDN-IoT, in more successful and promising ways.

Intelligent based novel embedded system based IoT enabled air pollution monitoring system

The rapid growth of industry and transport within this contemporary progress, there was sufficient consideration given to air quality monitoring; but conventional air quality monitoring methods are inefficient to produce adequate spatial and temporal resolutions of the air quality information by cost-effective also the period time clarifications. During the paper, we propose a distinct methodology to achieve the air quality monitoring system, using this fog computing-based Internet of Things (IoT). In this paper proposed an embedded system, where sensors collect the air quality information within period time and send it over the fog nodes. Every fog node may be an extraordinarily virtualized program hosted at a committed computing node implemented with a connection interface. Data gathered by Microprocessor based IoT sensing things do not seem to be causing on into the cloud server to the process. Preferably, they do send through the adjacent fog node to get quick, including high-rise rate service. Though, fog node will refine non-actionable data (e.g., regular device measurement) also forward them to the Cloud for lengthy run storage and batch analytics. The Cloud may be a convenient location to run world analytics at information gathered from commonly shared devices over sustained periods (months, years). General purpose processor (microprocessor) and IoT cloud platforms were involved in developing this whole infrastructure and model for analysis. Empirical outcomes reveal that this advanced method is responsible for sensing air quality, which serves to expose the modification patterns regarding air quality through a certain level.