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Showing papers in "Eurasip Journal on Wireless Communications and Networking in 2021"


Journal ArticleDOI
TL;DR: A new elbow point discriminant method is proposed to work out a statistical metric estimating an optimal cluster number when clustering on a dataset and the experimental results demonstrated that the estimated optimal clusters number output by the newly proposed method is better than widely used Silhouette method.
Abstract: Clustering, a traditional machine learning method, plays a significant role in data analysis. Most clustering algorithms depend on a predetermined exact number of clusters, whereas, in practice, clusters are usually unpredictable. Although the Elbow method is one of the most commonly used methods to discriminate the optimal cluster number, the discriminant of the number of clusters depends on the manual identification of the elbow points on the visualization curve. Thus, experienced analysts cannot clearly identify the elbow point from the plotted curve when the plotted curve is fairly smooth. To solve this problem, a new elbow point discriminant method is proposed to yield a statistical metric that estimates an optimal cluster number when clustering on a dataset. First, the average degree of distortion obtained by the Elbow method is normalized to the range of 0 to 10. Second, the normalized results are used to calculate the cosine of intersection angles between elbow points. Third, this calculated cosine of intersection angles and the arccosine theorem are used to compute the intersection angles between elbow points. Finally, the index of the above-computed minimal intersection angles between elbow points is used as the estimated potential optimal cluster number. The experimental results based on simulated datasets and a well-known public dataset (Iris Dataset) demonstrated that the estimated optimal cluster number obtained by our newly proposed method is better than the widely used Silhouette method.

96 citations


Journal ArticleDOI
Wen-Tao Li1, Mingxiong Zhao1, Yu-Hui Wu1, Jun-Jie Yu1, Bao Lingyan1, Huan Yang1, Di Liu1 
TL;DR: In this paper, the authors investigated a UAV-enabled MEC network with the consideration of multiple tasks either for computing or caching, and aimed to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices.
Abstract: Recently, unmanned aerial vehicle (UAV) acts as the aerial mobile edge computing (MEC) node to help the battery-limited Internet of Things (IoT) devices relieve burdens from computation and data collection, and prolong the lifetime of operating. However, IoT devices can ONLY ask UAV for either computing or caching help, and collaborative offloading services of UAV are rarely mentioned in the literature. Moreover, IoT device has multiple mutually independent tasks, which make collaborative offloading policy design even more challenging. Therefore, we investigate a UAV-enabled MEC networks with the consideration of multiple tasks either for computing or caching. Taking the quality of experience (QoE) requirement of time-sensitive tasks into consideration, we aim to minimize the total energy consumption of IoT devices by jointly optimizing trajectory, communication and computing resource allocation at UAV, and task offloading decision at IoT devices. Since this problem has highly non-convex objective function and constraints, we first decompose the original problem into three subproblems named as trajectory optimization ( $$\mathbf {P}_{\mathbf {T}}$$ ), resource allocation at UAV ( $$\mathbf {P}_{\mathbf {R}}$$ ) and offloading decisions at IoT devices ( $$\mathbf {P}_{\mathbf {O}}$$ ) and then propose an iterative algorithm based on block coordinate descent method to cope with them in a sequence. Numerical results demonstrate that collaborative offloading can effectively reduce IoT devices’ energy consumption while meeting different kinds of offloading services, and satisfy the QoE requirement of time-sensitive tasks at IoT devices.

63 citations


Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors designed a secure medical big data ecosystem on top of the Hadoop big data platform and implemented a personalized health information system that allows patient users to understand their treatment and rehabilitation status anytime and anywhere.
Abstract: In order to improve the intelligence of the medical system, this paper designs and implements a secure medical big data ecosystem on top of the Hadoop big data platform. It is designed against the background of the increasingly serious trend of the current security medical big data ecosystem. In order to improve the efficiency of traditional medical rehabilitation activities and enable patients to maximize their understanding of their treatment status, this paper designs a personalized health information system that allows patient users to understand their treatment and rehabilitation status anytime and anywhere, and all medical health data distributed in different independent medical institutions to ensure that these data are stored independently. As a distributed accounting technology for multi-party maintenance and backup information security, blockchain is a good breakthrough point for innovation in medical data sharing. In this paper, the system realizes the personal health data centre on the Hadoop big data platform, and the original distributed data are stored and analyzed centrally through the data synchronization module and the independent data acquisition system. Utilizing the advantages of the Hadoop big data platform, the personalized health information system for stroke has designed to provide personalized health management services for patients and facilitate the management of patients by medical staff.

35 citations


Journal ArticleDOI
TL;DR: In this paper, a hybrid blockchain mechanism based on 5G MEC smart grid is proposed, where both public blockchain and private blockchain are deployed on the MEC gateway/server to realize the connection of massive power IoT devices at the edge of 5G network.
Abstract: This work investigates the unified coding and identification of smart grid IoT devices, as more and more IoT devices in smart grid need to be managed and controlled. We combine blockchain technology with 5G MEC to realize the connection of massive power IoT devices at the edge of 5G network. Due to blockchain’s distributed storage and credibility, it is used to identify and register IoT devices in smart grid, ensuring the reliability and accuracy of smart grid IoT devices management. In this paper, we propose a hybrid blockchain mechanism based on 5G MEC smart grid, where both public blockchain and private blockchain are deployed on the MEC gateway/server. To facilitate the data searching and extracting, we endeavor to build a blockchain explorer indexed by IoT device identifier. After that, we study the typical consensus algorithms in the blockchain such as PoW, PoS, DPoS, PDFT, and discuss their feasibility in the hybrid blockchain. Finally, we analyzed and compared the performance of different consensus algorithms from the perspective of average computing time and average time to agreement.

33 citations


Journal ArticleDOI
TL;DR: In this article, a simple parametric polynomial line-of-sight channel model for the 100-450 GHz band is presented, which relies on simple absorption line shape functions that are fitted to the actual response given by complex but exact database approach.
Abstract: This paper documents a simple parametric polynomial line-of-sight channel model for 100–450 GHz band. The band comprises two popular beyond fifth generation (B5G) frequency bands, namely, the D band (110–170 GHz) and the low-THz band (around 275–325 GHz). The main focus herein is to derive a simple, compact, and accurate molecular absorption loss model for the 100–450 GHz band. The derived model relies on simple absorption line shape functions that are fitted to the actual response given by complex but exact database approach. The model is also reducible for particular sub-bands within the full range of 100–450 GHz, further simplifying the absorption loss estimate. The proposed model is shown to be very accurate by benchmarking it against the exact response and the similar models given by International Telecommunication Union Radio Communication Sector. The loss is shown to be within ±2 dBs from the exact response for one kilometer link in highly humid environment. Therefore, its accuracy is even much better in the case of usually considered shorter range future B5G wireless systems.

31 citations


Journal ArticleDOI
TL;DR: In this paper, a comprehensive analysis on the applications of blockchain in the Internet of Vehicles (IoV) is presented, and the future research directions related to the integration are highlighted.
Abstract: Blockchain technology has completely changed the area of cryptocurrency with a Peer-to-Peer system named Bitcoin. It can provide a distributed, transparent and highly confidential database by recording immutable transactions. Currently, the technique has obtained great research interest on other areas, including the Internet of vehicles (IoVs). In order to solve some centralized problems and improve the architecture of the IoVs, the blockchain technology is utilized to build a decentralized and secure vehicular environment. In this survey, we aim to construct a comprehensive analysis on the applications of blockchain in the IoV. This paper starts with the introduction of the IoVs and the blockchain. Additionally, some existing surveys on the blockchain enabled IoVs are reviewed. Besides, the combination of the blockchain technology and the IoVs is analyzed from seven aspects to describe how the blockchain is implemented in the IoVs. Finally, the future research directions related to the integration are highlighted.

29 citations


Journal ArticleDOI
TL;DR: In this paper, the authors proposed feature clusters in terms of Flow, Message Queuing Telemetry Transport (MQTT) and Transmission Control Protocol (TCP) by using features in UNSW-NB15 data-set.
Abstract: Internet of Things (IoT) devices are well-connected; they generate and consume data which involves transmission of data back and forth among various devices Ensuring security of the data is a critical challenge as far as IoT is concerned Since IoT devices are inherently low-power and do not require a lot of compute power, a Network Intrusion Detection System is typically employed to detect and remove malicious packets from entering the network In the same context, we propose feature clusters in terms of Flow, Message Queuing Telemetry Transport (MQTT) and Transmission Control Protocol (TCP) by using features in UNSW-NB15 data-set We eliminate problems like over-fitting, curse of dimensionality and imbalance in the data-set We apply supervised Machine Learning (ML) algorithms, ie, Random Forest (RF), Support Vector Machine and Artificial Neural Networks on the clusters Using RF, we, respectively, achieve 9867% and 9737% of accuracy in binary and multi-class classification In clusters based techniques, we achieved 9696%, 914% and 9754% of classification accuracy by using RF on Flow & MQTT features, TCP features and top features from both clusters Moreover, we show that the proposed feature clusters provide higher accuracy and requires lesser training time as compared to other state-of-the-art supervised ML-based approaches

27 citations


Journal ArticleDOI
TL;DR: In this article, the main drivers and requirements of MTC towards 6G were discussed, and a wide variety of enabling technologies were discussed for MTC-optimized holistic end-to-end network architecture.
Abstract: The recently introduced 5G New Radio is the first wireless standard natively designed to support critical and massive machine type communications (MTC). However, it is already becoming evident that some of the more demanding requirements for MTC cannot be fully supported by 5G networks. Alongside, emerging use cases and applications towards 2030 will give rise to new and more stringent requirements on wireless connectivity in general and MTC in particular. Next generation wireless networks, namely 6G, should therefore be an agile and efficient convergent network designed to meet the diverse and challenging requirements anticipated by 2030. This paper explores the main drivers and requirements of MTC towards 6G, and discusses a wide variety of enabling technologies. More specifically, we first explore the emerging key performance indicators for MTC in 6G. Thereafter, we present a vision for an MTC-optimized holistic end-to-end network architecture. Finally, key enablers towards (1) ultra-low power MTC, (2) massively scalable global connectivity, (3) critical and dependable MTC, and (4) security and privacy preserving schemes for MTC are detailed. Our main objective is to present a set of research directions considering different aspects for an MTC-optimized 6G network in the 2030-era.

24 citations


Journal ArticleDOI
TL;DR: Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes, and develops a strong network backbone that provides fail-over-proof routing.
Abstract: Wireless sensor network (WSN)-based Internet of Things (IoT) applications suffer from issues including limited battery capacity, frequent disconnections due to multi-hop communication and a shorter transmission range. Clustering and routing are treated separately in different solutions and, therefore, efficient solutions in terms of energy consumption and network lifetime could not be provided. This work focuses data collection from IoT-nodes distributed in an area and connected through WSN. We address two interlinked issues, clustering and routing, for large-scale IoT-based WSN and propose an improved clustering and routing protocol to jointly solve both of these issues. Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes. During process of clustering, cluster-heads are selected in such a way that provide fail-over-proof routing. An efficient routing path is achieved by finding the minimal hop-count with the availability of alternate routing paths. The results are compared with state-of-the-art benchmark protocols. Theoretical and simulation results demonstrate reliable network topology, improved network lifetime, efficient node density management and improved overall network capacity.

19 citations


Journal ArticleDOI
TL;DR: In this article, the basic operation of antenna array and metasurface based RIS is described and a review of the literature on the use of RIS in wireless communication applications operating below 10 GHz frequency band is provided.
Abstract: Reconfigurable intelligent surface (RIS) is a programmable structure that can be used to control the propagation of electromagnetic waves by changing the electric and magnetic properties of the surface. By placing these surfaces in an environment, the properties of radio channels can be controlled. This opens up new opportunities to improve the performance of wireless systems. In this paper, the basic operation of antenna array and metasurface based RIS is described. While the current long term (6G) research on RIS often prioritizes very high frequencies from tens to hundreds of GHz, this paper puts emphasis rather on operating frequencies below 10 GHz which promise a much faster to market track for RIS applications. For this purpose, review of the literature on the use of RIS in wireless communication applications operating below 10 GHz frequency band is provided.

18 citations


Journal ArticleDOI
TL;DR: A task-offloading decision mechanism with particle swarm optimization for IoV-based edge computing and the experimental results show that the proposed offloading strategy can effectively reduce the energy consumption of terminal devices while guarantee the service quality of users.
Abstract: As a technology integrated with Internet of things, mobile edge computing (MEC) can provide real-time and low-latency services to the underlying network and improve the storage and computation ability of the networks instead of central cloud infrastructure. In mobile edge computing-based Internet of Vehicle (MEC-IoV), the vehicle users can deliver their tasks to the associated MEC servers based on offloading policy, which improves the resource utilization and computation performance greatly. However, how to evaluate the impact of uncertain interconnection between the vehicle users and MEC servers on offloading decision-making and avoid serious degradation of the offloading efficiency are important problems to be solved. In this paper, a task-offloading decision mechanism with particle swarm optimization for MEC-IoV is proposed. First, a mathematical model to calculate the computation offloading cost for cloud-edge computing system is defined. Then, the particle swarm optimization is applied to convert the offloading of task into the process and obtain the optimal offloading strategy. Furthermore, to avoid falling into local optimization, the inertia weight factor is designed to change adaptively with the value of the objective function. The experimental results show that the proposed offloading strategy can effectively reduce the energy consumption of terminal devices while guarantee the service quality of users.

Journal ArticleDOI
TL;DR: In this article, the authors investigated the energy cost minimization for mission-critical internet-of-things (IoT) in mobile edge computing (MEC) system, where short data packets are transmitted between the IoT devices and the access points (APs) to reduce transmission latency and prolong the battery life of the devices.
Abstract: The energy cost minimization for mission-critical internet-of-things (IoT) in mobile edge computing (MEC) system is investigated in this work. Therein, short data packets are transmitted between the IoT devices and the access points (APs) to reduce transmission latency and prolong the battery life of the IoT devices. The effects of short-packet transmission on the radio resource allocation is explicitly revealed. We mathematically formulate the energy cost minimization problem as a mixed-integer non-linear programming (MINLP) problem, which is difficult to solve in an optimal way. More specifically, the difficulty is essentially derived from the coupling of the binary offloading variables and the resource management among all the IoT devices. For analytical tractability, we decouple the mixed-integer and non-convex optimization problem into two sub-problems, namely, the task offloading decision-making and the resource optimization problems, respectively. It is proved that the resource allocation problem for IoT devices under the fixed offloading strategy is convex. On this basis, an iterative algorithm is designed, whose performance is comparable to the best solution for exhaustive search, and aims to jointly optimize the offloading strategy and resource allocation. Simulation results verify the convergence performance and energy-saving function of the designed joint optimization algorithm. Compared with the extensive baselines under comprehensive parameter settings, the algorithm has better energy-saving effects.

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a secure mutual authentication protocol based on edge computing for use in a smart grid (SG) which is an advanced power grid system deployed in a cloud center and smart meters (at the consumer end) that provides higher reliability, better data protection, improved power efficiency, automatic monitoring and effective management of power consumption.
Abstract: A smart grid (SG) is an advanced power grid system deployed in a cloud center and smart meters (at the consumer end) that provides higher reliability, better data protection, improved power efficiency, automatic monitoring, and effective management of power consumption. However, an SG also poses certain challenges that need to be addressed. For example, data provided by a smart meter are time-sensitive and cannot handle high latency in an SG. Moreover, a smart meter depends on memory, energy, and other factors. Besides, the security between a cloud center and a smart meter is a critical issue that needs to be resolved. Edge computing, an extension of cloud computing deployed in an edge network between a cloud center and the end devices, is an efficient solution to the aforementioned issues. Therefore, in this study, we propose a secure mutual authentication protocol based on edge computing for use in an SG.

Journal ArticleDOI
TL;DR: In this article, a multi-agent load balancing distribution based on deep reinforcement learning DTOMALB, a distributed task allocation algorithm, is proposed to improve user experience and balance resource utilization.
Abstract: In the last few years, the Internet of Things (IOT), as a new disruptive technology, has gradually changed the world. With the prosperous development of the mobile Internet and the rapid growth of the Internet of Things, various new applications continue to emerge, such as mobile payment, face recognition, wearable devices, driverless, VR/AR, etc. Although the computing power of mobile terminals is getting higher and the traditional cloud computing model has higher computing power, it is often accompanied by higher latency and cannot meet the needs of users. In order to reduce user delay to improve user experience, and at the same time reduce network load to a certain extent, edge computing, as an application of IOT, came into being. In view of the new architecture after dating edge computing, this paper focuses on the task offloading in edge computing, from task migration in multi-user scenarios and edge server resource management expansion, and proposes a multi-agent load balancing distribution based on deep reinforcement learning DTOMALB, a distributed task allocation algorithm, can perform a reasonable offload method for this scenario to improve user experience and balance resource utilization. Simulations show that the algorithm has a certain adaptability compared to the traditional algorithm in the scenario of multi-user single cell, and reduces the complexity of the algorithm compared to the centralized algorithm, and reduces the average response delay of the overall user. And balance the load of each edge computing server, improve the robustness and scalability of the system.

Journal ArticleDOI
TL;DR: In this article, a mobile fronthaul system based on millimeter 5G NR OFDM signaling compliant with 3GPP Rel-15 was demonstrated in an experimental demonstration.
Abstract: The sixth generation (6G) mobile systems will create new markets, services, and industries making possible a plethora of new opportunities and solutions Commercially successful rollouts will involve scaling enabling technologies, such as cloud radio access networks, virtualization, and artificial intelligence This paper addresses the principal technologies in the transition towards next generation mobile networks The convergence of 6G key-performance indicators along with evaluation methodologies and use cases are also addressed Free-space optics, Terahertz systems, photonic integrated circuits, softwarization, massive multiple-input multiple-output signaling, and multi-core fibers, are among the technologies identified and discussed Finally, some of these technologies are showcased in an experimental demonstration of a mobile fronthaul system based on millimeter 5G NR OFDM signaling compliant with 3GPP Rel 15 The signals are generated by a bespoke 5G baseband unit and transmitted through both a 10 km prototype multi-core fiber and 4 m wireless V-band link using a pair of directional 60 GHz antennas with 10° beamwidth Results shown that the 5G and beyond fronthaul system can successfully transmit signals with both wide bandwidth (up to 800 MHz) and fully centralized signal processing As a result, this system can support large capacity and accommodate several simultaneous users as a key candidate for next generation mobile networks Thus, these technologies will be needed for fully integrated, heterogeneous solutions to benefit from hardware commoditization and softwarization They will ensure the ultimate user experience, while also anticipating the quality-of-service demands that future applications and services will put on 6G networks

Journal ArticleDOI
TL;DR: A model to improve the access control security of the Internet of Things, which is based on zero-knowledge proof and smart contract technology in the blockchain, and achieves effective attribute privacy protection.
Abstract: Information security has become a hot topic in Internet of Things (IoT), and traditional centralized access control models are faced with threats such as single point failure, internal attack, and central leak. In this paper, we propose a model to improve the access control security of the IoT, which is based on zero-knowledge proof and smart contract technology in the blockchain. Firstly, we deploy attribute information of access control in the blockchain, which relieves the pressure and credibility problem brought by the third-party information concentration. Secondly, encrypted access control token is used to gain the access permission of the resources, which makes the user's identity invisible and effectively avoids attribute ownership exposure problem. Besides, the use of smart contracts solves the problem of low computing efficiency of IoT devices and the waste of blockchain computing power resources. Finally, a prototype of IoT access control system based on blockchain and zero-knowledge proof technology is implemented. The test analysis results show that the model achieves effective attribute privacy protection, compared with the Attribute-Based Access Control model of the same security level, the access efficiency increases linearly with the increase of access scale.

Journal ArticleDOI
TL;DR: A multi-path QoS (Quality of Service) routing security algorithm based on blockchain by improving the traditional AODV (Ad hoc On-Demand Distance Vector) protocol (AODV-MQS) is proposed.
Abstract: Ad hoc network is a special network with centerless and dynamic topology. Due to the free mobility of the nodes, routing security has been a bottleneck problem that plagues its development. Therefore, a multi-path QoS (quality of service) routing security algorithm based on blockchain by improving the traditional AODV (ad hoc on-demand distance vector) protocol (AODV-MQS) is proposed. Firstly, a chain of nodes is established in the network and the states of all nodes by making the intermediate nodes on the chain are saved. Secondly, the smart contract in the blockchain is set to filter out the nodes that meet the QoS constraints. Finally, two largest unrelated communication paths are found in the blockchain network through smart contract, one of which is the main path and the other is the standby path. Simulation experiments show that the performance of the proposed algorithm is better than other algorithms, especially in an unsafe environment.

Journal ArticleDOI
TL;DR: In this article, the authors investigated some key MAC protocols that could be exploited in WBANs based on their characteristics, service specifications, technical issues such as energy wastage issues, and possible technical solutions were provided to enhance energy efficiency, channel utilization, data transmission rate, and dealy rate.
Abstract: Internet of things (IoT) is a concept that is currently gaining a lot of popularity as a result of its potential to be incorporated into many heterogeneous systems Because of its diversity, integrating IoT is conceivable in almost all fields, including the healthcare sector For instance, a promising technology in the healthcare sector known as wireless body area network (WBAN) could be integrated with the IoT to enhance its productivity However, in order to guarantee the optimization of the operation of the healthcare applications facilitated by the WBAN-enabled IoT technology, there must be enough support from all the different protocol stack layers so as to satisfy the critical quality-of-service (QoS) requirements of the WBAN systems Consequently, the medium access control (MAC) protocol has recently been gaining lots of attention in the area of WBANs due to its ability to manage and coordinate when a shared communication channel can be accessed For the purpose of achieving efficient MAC protocols for WBAN-enabled IoT technology, this paper investigates some key MAC protocols that could be exploited in WBANs based on their characteristics, service specifications, technical issues such as energy wastage issues, and possible technical solutions were provided to enhance energy efficiency, channel utilization, data transmission rate, and dealy rate Also, these MAC protocols were grouped and compared based on short- and long-range communication standards Following this, future directions and open research issues are pointed out

Journal ArticleDOI
TL;DR: Based on the architecture of the Internet of Things smart home, this article constructed an indoor air quality monitoring system to explore how people can live in an environment with good air quality, and the common points of the two indices are combined, and indoor and outdoor environmental parameters are analyzed, and controllable environment variables are simulated to analyze their effects on air quality.
Abstract: With rapidly changing technology, people have more and more requirements for thermal comforts regarding indoor temperature, humidity, and wind speed, and pay more attention to air quality. Indoor air quality has serious effects on the elderly, children, and those with respiratory allergies. Based on the architecture of the Internet of Things smart home, this study constructed an indoor air quality monitoring system to explore how people can live in an environment with good air quality. Among the numerous air quality indices (AQIs), the carbon dioxide index and AQI of the American Society of Heating, Refrigerating and Air-Conditioning Engineers are selected as the indices suitable for this study. The common points of the two indices are combined, and then, based on the data of the Environmental Protection Administration, indoor and outdoor environmental parameters are analyzed, and controllable environment variables are simulated to analyze their effects on air quality. This study designed effective load control using fuzzy control and developed a fuzzy rule base for simulation of the environment variables. Decision logic was used to replace the threshold control of indoor air quality in the past, and a comfortable air quality monitoring system was designed by combining the Arduino Uno development board and ESP8266 Wi-Fi wireless transmission modules.

Journal ArticleDOI
TL;DR: Li et al. as mentioned in this paper proposed a lightweight trust management scheme (LTMS) based on binomial distribution for defending against the internal attacks in hierarchical wireless sensor network (WSN), where distance domain, energy domain, security domain and environment domain are considered and introduced to propose a multidimensional secure clustered routing (MSCR) scheme by using dynamic dimension weight in hierarchical WSNs.
Abstract: For hierarchical wireless sensor network (WSN), the clustered routing protocol can effectively deal with large-scale application requirements, thereby, how to efficiently elect the secure cluster heads becomes very critical. Unfortunately, many current studies only focus on improving security while neglecting energy efficiency and transmission performance. In this paper, a lightweight trust management scheme (LTMS) is proposed based on binomial distribution for defending against the internal attacks. Simultaneously, distance domain, energy domain, security domain and environment domain are considered and introduced to propose a multidimensional secure clustered routing (MSCR) scheme by using dynamic dimension weight in hierarchical WSNs. The simulation results show that LTMS can effectively prevent a malicious node from being elected as a cluster head, and MSCR can achieve a balance between security, transmission performance and energy efficiency under the requirements of environmental applications.

Journal ArticleDOI
TL;DR: In this article, the authors proposed an energy-aware task offloading with deadline constraint (DRL-E2D) algorithm for a multi-eNB MEC environment, which is to maximize the reward under the deadline constraint of the tasks.
Abstract: With the development of the wireless network, increasing mobile applications are emerging and receiving great popularity. These applications cover a wide area, such as traffic monitoring, smart homes, real-time vision processing, objective tracking, and so on, and typically require computation-intensive resources to achieve a high quality of experience. Although the performance of mobile devices (MDs) has been continuously enhanced, running all the applications on a single MD still causes high energy consumption and latency. Fortunately, mobile edge computing (MEC) allows MDs to offload their computation-intensive tasks to proximal eNodeBs (eNBs) to augment computational capabilities. However, the current task offloading schemes mainly concentrate on average-based performance metrics, failing to meet the deadline constraint of the tasks. Based on the deep reinforcement learning (DRL) approach, this paper proposes an Energy-aware Task Offloading with Deadline constraint (DRL-E2D) algorithm for a multi-eNB MEC environment, which is to maximize the reward under the deadline constraint of the tasks. In terms of the actor-critic framework, we integrate the action representation into DRL-E2D to handle the large discrete action space problem, i.e., using the low-complexity k-nearest neighbor as an approximate approach to extract optimal discrete actions from the continuous action space. The extensive experimental results show that DRL-E2D achieves better performance than the comparison algorithms on all parameter settings, indicating that DRL-E2D is robust to the state changes in the MEC environment.

Journal ArticleDOI
TL;DR: In this article, the authors discuss the practical application of network multimedia courseware in college basketball teaching, including teaching content, teacher guidance, student learning, and courseware completion by using Flash mx2004 plug-in.
Abstract: With the acceleration of informatization and the coverage of wireless networks, homes, conferences, schools and other places have a higher pursuit of the wireless transmission capabilities of electronic devices. Wireless screen transmission technology is used more frequently in life, work and study. This article mainly discusses the practical application of network multimedia courseware in college basketball teaching. This article first elaborates the teaching plan of multimedia courseware, including teaching content, teacher guidance, student learning and multimedia courseware. Secondly, the multimedia courseware of basketball tactics basic teaching is completed by using Flash mx2004 plug-in. After that, it specifically introduces the process of how to transmit basketball teaching content through multimedia equipment to the video network for students to learn under the wireless network environment. It emphasizes that the “wireless multimedia communication” course is an important course in the electronic information subject. Finally, through the teaching experiment, the accuracy of the multimedia teaching method was tested, and the validity of the courseware content was tested by the empirical validity evaluation method. At the same time, after the teaching experiment, in order to test the two groups of students’ mastery of the basic coordination theory of basketball tactics, the basic coordination theory of basketball tactics was tested. The experimental group had 22 students with a score of 90 or more, accounting for 27.5%, and the control group had 13 students with a score of 90 or more, accounting for 16.5%. The results show that wireless network multimedia computer-assisted teaching has a positive effect on improving students’ interest in learning.

Journal ArticleDOI
TL;DR: In this paper, the authors proposed an energy-efficient hierarchical routing protocol for WSNs based on fog computing, which can minimize sensor nodes' energy consumption, data packet losses, and extends the network lifetime.
Abstract: Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the twenty-first century The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use In the literature, different methods have been proposed to minimize the energy consumption of sensor nodes to prolong WSNs utilization In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called energy-efficient hierarchical routing protocol for wireless sensor networks based on fog computing Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of things applications In addition, we propose an improved ant colony optimization algorithm that can be used to construct an optimal path for efficient data transmission for sensor nodes The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses, and extends the network lifetime We are aware that in WSNs, the certainty of the sensed data collected by a sensor node can vary due to many reasons such as environmental factors, drained energy, and hardware failures

Journal ArticleDOI
Qi Xie1, Keheng Li1, Xiao Tan1, Lidong Han1, Wen Tang1, Bin Hu1 
TL;DR: Wang et al. as discussed by the authors proposed a secure and privacy-preserving authentication protocol for WSN in smart city, which can improve the efficiency of managing assets and resources, optimize urban services and improve the quality of citizens' life.
Abstract: Smart city can improve the efficiency of managing assets and resources, optimize urban services and improve the quality of citizens’ life. Wireless sensor networks (WSNs) can solve many problems in smart city, such as smart transportation, smart healthcare and smart energy. However, security and privacy are the biggest challenges for WSN. Recently, Banerjee et al. proposed a security-enhanced authentication and key agreement scheme for WSN, but their scheme cannot resist offline password guessing attack, impersonation attack, and does not achieve session key secrecy, identity unlinkability, and perfect forward secrecy. In order to fix these flaws, a secure and privacy-preserving authentication protocol for WSN in smart city is proposed. We prove the security of the proposed protocol by using applied pi calculus-based formal verification tool ProVerif and show that it has high computational efficiency by comparison with some related schemes.

Journal ArticleDOI
TL;DR: The detection success rate of the power transformer fault diagnosis system model established is as high as 95.6%, the training error is less than 0.000l, and it can correctly identify the fault types of the non training samples.
Abstract: Transformer is the most important equipment in the power system. The research and development of fault diagnosis technology for Internet of Things equipment can effectively detect the operation status of equipment and eliminate hidden faults in time, which is conducive to reducing the incidence of accidents and improving people's life safety index. To explore the utility of Internet of Things in power transformer fault diagnosis system. A total of 30 groups of transformer fault samples were selected, and 10 groups were randomly selected for network training, and the rest samples were used for testing. The matter-element extension mathematical model of power transformer fault diagnosis was established, and the correlation function was improved according to the characteristics of three ratio method. Each group of power transformer was diagnosed for four months continuously, and the monitoring data and diagnosis were recorded and analyzed result. GPRS communication network is used to complete the communication between data acquisition terminal and monitoring terminal. According to the parameters of the database, the working state of the equipment is set, and various sensors are controlled by the instrument driver module to complete the diagnosis of transformer fault system. The detection success rate of the power transformer fault diagnosis system model established in this paper is as high as 95.6%, the training error is less than 0.0001, and it can correctly identify the fault types of the non training samples. It can be seen that the technical support of the Internet of Things is helpful to the upgrading and maintenance of the power transformer fault diagnosis system.

Journal ArticleDOI
TL;DR: In this article, a private and rateless adaptive coded computation (PRAC) algorithm for distributed matrix-vector multiplication is proposed, which takes into account the privacy requirements of IoT applications and devices, and the heterogeneous and time-varying resources of edge devices.
Abstract: Edge computing is emerging as a new paradigm to allow processing data near the edge of the network, where the data is typically generated and collected. This enables critical computations at the edge in applications such as Internet of Things (IoT), in which an increasing number of devices (sensors, cameras, health monitoring devices, etc.) collect data that needs to be processed through computationally intensive algorithms with stringent reliability, security and latency constraints. Our key tool is the theory of coded computation, which advocates mixing data in computationally intensive tasks by employing erasure codes and offloading these tasks to other devices for computation. Coded computation is recently gaining interest, thanks to its higher reliability, smaller delay, and lower communication costs. In this paper, we develop a private and rateless adaptive coded computation (PRAC) algorithm for distributed matrix-vector multiplication by taking into account (1) the privacy requirements of IoT applications and devices, and (2) the heterogeneous and time-varying resources of edge devices. We show that PRAC outperforms known secure coded computing methods when resources are heterogeneous. We provide theoretical guarantees on the performance of PRAC and its comparison to baselines. Moreover, we confirm our theoretical results through simulations and implementations on Android-based smartphones.

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors used the seasonal autoregressive integrated moving average model (SARIMA) and support vector machines (SVM) to establish a traffic flow prediction model for short-term passenger flow prediction in urban rail transit.
Abstract: Short-term passenger flow prediction in urban rail transit plays an important role because it in-forms decision-making on operation scheduling However, passenger flow prediction is affected by many factors This study uses the seasonal autoregressive integrated moving average model (SARIMA) and support vector machines (SVM) to establish a traffic flow prediction model The model is built using intelligent data provided by a large-scale urban traffic flow warning system, such as accurate passenger flow data, collected using the Internet of things and sensor networks The model proposed in this paper can adapt to the complexity, nonlinearity, and periodicity of passenger flow in urban rail transit Test results on a Beijing traffic dataset show that the SARI-MA–SVM model can improve accuracy and reduce errors in traffic prediction The obtained pre-diction fits well with the measured data Therefore, the SARIMA–SVM model can fully charac-terize traffic variations and is suitable for passenger flow prediction

Journal ArticleDOI
TL;DR: In this paper, a sensory data fusion model suitable for the supply chain of agricultural products is obtained, and information technology based on the Internet of things is used to transform and optimize the internet of things in the circulation of agricultural items.
Abstract: There are often agricultural product quality problems in the production and circulation of agricultural products. Therefore, there are more and more people on the agricultural product supply chain based on the Internet of things. This article mainly introduces the research on the perception data fusion of agricultural product supply chain in the context of the Internet of things. This is a simple research result based on the Internet of things technology platform, which analyzes the current status of the product according to market demand. After analysis and comparison, a sensory data fusion model suitable for the supply chain of agricultural products is obtained, and information technology based on the Internet of things is used to transform and optimize the Internet of things in the circulation of agricultural products. The experimental results of this article show that data fusion technology based on the Internet of things can solve and track 69.45% of the problem of unknown sources of agricultural products, improve the supply efficiency of agricultural products by 43%, reduce the health problems of agricultural products by 31.24%, and reduce the prices of agricultural products by 13–20%. Improving logistics efficiency can save 5 million tons of agricultural products.

Journal ArticleDOI
TL;DR: In this article, the authors proposed a hybrid ring-Mesh protocol (HRMP) that applies cooperation network coding (CoNC) in a wired ring topology (WRT) to improve exchanging the BD significantly in wireless mesh network (WMN).
Abstract: Wired and wireless communication data is getting bigger and bigger at such a high pace. Accordingly, the big data (BD) communication networks should be developed as quickly as the quick increase in the exchanging data size is. Based on this regard, this paper proposes a wired and wireless protocol that applies cooperation Network coding (CoNC) in a wired ring topology (WRT) to improve exchanging the BD significantly in wireless mesh network (WMN). The paper presents a solution for distributed nodes to deal with big data over 5G by proposing Hybrid Ring-Mesh Protocols (HRMP) that exploit the CoNC technique at distributed nodes. The proposed protocol (X-ORING) deterministically combines the data that is received at a base station (BS), where the BS wirelessly retransmits the combined data to the WMN members, instead of just forwarding them to the WMN members. Moreover, all members of the WMN are connected by wired optical fibre channels in a WRT and directly to the BS. The results show that applying CoNC in the proposed protocols exploits the advantages of the WRP between the WMN members, and consequently, the WMN packet error rate is significantly improved. Moreover, using optical fibre wires between the mesh network members and the BS increases the WMN coverage region considerably, and allows the BS to receive all members' packets correctly. Finally, the results show that applying CoNC on the WRT improves the entire network maintenance and reliability greatly, simply because the proposed HRMP can continue broadcasting even if one of the direct optical fibre goes out of serves, i.e. the fibre link between one of the N member and the BS lost the connectivity.

Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper extended their work to design a lightweight pseudonym identity based authentication and key agreement protocol using smart card and analyzed the interaction between participants authentication path to ensure security protection from simulated attacks.
Abstract: With the widespread use of Internet of Things and cloud computing in smart cities, various security and privacy challenges may be encountered.The most basic problem is authentication between each application, such as participating users, IoT devices, distributed servers, authentication centers, etc. In 2020, Kang et al. improved an authentication protocol for IoT-Enabled devices in a distributed cloud computing environment and its main purpose was in order to prevent counterfeiting attacks in Amin et al.’ protocol, which was published in 2018. However, We found that the Kang et al.’s protocol still has a fatal vulnerability, that is, it is attacked by offline password guessing, and malicious users can easily obtain the master key of the control server. In this article, we extend their work to design a lightweight pseudonym identity based authentication and key agreement protocol using smart card. For illustrating the security of our protocol, we used the security protocol analysis tools of AVISPA and Scyther to prove that the protocol can defend against various existing attacks. We will further analyze the interaction between participants authentication path to ensure security protection from simulated attacks detailedly. In addition, based on the comparison of security functions and computing performance, our protocol is superior to the other two related protocols. As a result, the enhanced protocol will be efficient and secure in distributed cloud computing architecture for smart city.