Wireless Internet

Along with the flourishing development of Internet of Things, vehicles which assist move goods are developed as well, for example, automatic guided vehicle applied in manufacturing plants. Vehicles vary with pattern of goods to be moved. If it moves along magnetic tapes, it would lose its flexibility in moving directions. To make vehicles more dynamic and convenient, this study designs and implements automatic following technology of vehicles. Through relative position between vehicles and objects to be followed positioned by satellite and laser radar installed on vehicles which can detect relative distance, vehicles are able to automatically follow objects to be followed.

Multi-hop Wireless Sensor networks are designed for various real-time applications, and it should be appropriately designed to avoid delivery congestion between linked nodes. For efficient transmission with minimum energy, our proposed work introduces a novel optimized method based on the congestion management algorithm. In our approach based congestion control algorithm was based on the cluster-based routing, since the energy consumption was effectively reduced throughout the network. Since it has to improve network lifetime for a plentiful simulation period, the delivery control process also reduces the access delay. Initially, cluster the nodes with the k means algorithm. After that focusing on the delivery control using Kalman Filter strategy, and this is suitable for minimum access-delay prediction. Finally, the delivery with high efficiency using optimized routing. The experimental results are implemented on the Windows platform, and the performances outperform average throughput, average packet loss, packet delivery ratio, energy-consuming, and system reliability.

In this paper, a new network invulnerability evaluation model based on routing path and node importance is proposed. The core of the invulnerability algorithm lies in two levels, comprehensive consideration of the influencing factors of network to point-to-line network invulnerability. The algorithm considers the influence of the proportion of important nodes of the network on the invulnerability of the network, and considers the influence of the number of paths between the communication nodes on the invulnerability of the path. Through simulation comparison, it is found that this algorithm improves the sensitivity of network invulnerability to the number of paths, and is suitable for communication networks in the case of multiple routing paths.

In order to implement an effective directed medium access control and routing protocol in a directed ad hoc network, the node in the network should know the state of the neighboring nodes. However, it is difficult to sense signals in other directions, due to the strong directivity of the directional antenna. It will result in problems such as link collision. In order to solve the above problems, this paper proposes an orthogonal frequency division multiple access (OFDMA) based neighbor discover and tracking protocol for directional ad-hoc network. Then this paper discusses the neighboring state partitioning method based on discovery time and multiple resource unit access and frame format design based on OFDMA. The simulation results show that compared with the directional transmission and reception algorithms protocol, the protocol proposed in this paper increases the number of neighbor discovered nodes by 200\(\%\) when the number of neighbor nodes is about 30. The nodes can connect neighbor nodes frequently, and it improves accuracy of neighbor nodes position.

Device-to-device (D2D) communication allows a direct transmission between two devices. In this way, cellular user equipment’s are not always obliged to route the data conventionally through a cellular base station. This paper focuses on multi-hop D2D communication, where D2D relays are exploited to delivery of data from a source to a destination. We propose a novel algorithm that finds the most suitable path between the D2D source and destination so that the capacity of multi-hop communication is maximized. The appropriate route is found via Genetic Algorithm (GA) with an ordered crossover. The simulation results show that the proposed algorithm improves the capacity of multi-hop D2D communication from a source to a destination compared to an existing relay selection algorithm by 20–61%. We also show that the proposed solution converges fast enough to be beneficial even in realistic mobile networks.

Many modern infrastructures incorporate a number of sensors and actuators interconnected via wireless links using Wireless Sensor Network (WSN) and Internet of Things (IoT) technology. With a number of mission-critical infrastructures embracing these technologies, the security of such infrastructures assumes paramount importance. A motivated malicious adversary, if not kept in check by a strong defense, can cause much damage in such settings by taking actions that compromise the availability, integrity, confidentiality of network services as well as the privacy of users. This motivates the development of a strong Intrusion Detection System (IDS). In this paper, we have proposed a new Deep Reinforcement Learning (DRL)-based IDS for WSNs and IoTs that uses the formalism of Markov decision process (MDP) to improve the IDS decision performance. To evaluate the performance of our scheme, we compare our scheme against the baseline benchmark of standard reinforcement learning (RL) and the supervised algorithm of machine learning K-Nearest Neighbors (KNN). Through our a thorough simulation-based performance analysis, we demonstrate that our model DRL-IDS returns superior performance in terms of improved detection rate and enhancement the production of accuracy with reduced number of false alarms compared with this current approaches.

In unmanned stores, automated checkout is an integral part of the process, and the checkout is usually completed by expensive identification machines. Some unmanned stores lacking banknotes and coins only provide credit cards, EasyCard, or QR code payment methods, sometimes that cause the difficulty of payment when they check out. This research is aimed at the coin recognition for images. It processes the images using OpenCV, and substitutes into the trained convolutional neural network (CNN) for identification. The result of the research shows that the accuracy of the model identification is 94%, and it can be used to identify more than one coin.

This study aimed at finding out the similarity to create a movie recommendation system and grouping based on the user. The purpose of the recommendation system as information for customers in selecting films according to features. The recommendation system can be performed with several algorithms as a grouping such as K-Means, K-Means Mini Batch, Birch Algorithm, Affinity Propagation Algorithm and Mean Shift Algorithm. We recommend methods to optimize K as a precaution in increasing variance. We use clustering based on Movie ratings, Tags, and Genre. This study would find a better method and way to evaluate the clustering algorithm. To check the recommendation system, we utilize social network analysis and mean squared error to explore the relationships between clusters. We also utilize average similarity, computation time, and clustering performance evaluation in getting an evaluation as a comparison of the recommendation system. Clustering Performance Evaluation with Silhouette Coefficient, Calinski-Harabasz, Davies-Bouldin.

Blockchain-based mobile edge computing (BMEC) is a promising architecture in the fifth-generation (5G) networks. BMEC solves the problem of limited computing resources of devices in the mobile blockchain environment while ensuring the distributed deployment of computing resources and the traceable of transaction data. However, some consensus-level security threats exist in the mobile blockchain environment, i.e., double-spend attacks, long-range attacks, selfish mining. All of these threats can break the integrity of BMEC, allowing the correct block record to be overwritten with a false one. In this paper, we propose a group signature scheme on blocks of blockchain for addressing such issues. Each new block will be regarded as a valid block if it obtains a valid group aggregate signature of the group which the block creator belongs to. We describe in detail the process of authentication and key changes when nodes join and leave BMEC. We also show the role of our proposed group signature scheme in validating blocks. Lastly, the security analysis is also presented to prove that our proposed group signature scheme is effective.

In recent years, the emergence of blockchain-based and privately issued digital currencies has raised a lot of concerns, including: infringement of privacy rights, the danger of such currencies being used as money laundering tools or in a way that harms consumer protection and financial stability. However, central banks have already started their research on the Central Bank Digital Currency (CBDC). To study the subject of CBDC development in China, this paper first presents a detailed introduction of the concept of private digital currency and the issues that come with it. Secondly, this paper advocates the method of establishing an easy-to-regulate CBDC system based on the two chains scheme of blockchain and making sure the complete transaction information and those used for verification are stored and accessed separately, therefore realizing a balance between protection of user privacy and facilitating regulation. At the same time, the consortium blockchain should be anchored in the public chain to ensure data credibility. Furthermore, although China has begun its CBDC development, it has yet to develop adequate laws and regulations. To this end, in addition to presenting a summary of China’s CBDC system, this paper also explains the rights and obligations of the central bank, the commercial banks and the public with regards to the currency, in the hope that such contents can be of some help to the revision of relevant laws in the future.

Smart contracts have recently been considered one of the two columns of blockchain applications. The first column is the cryptocurrency funded by the decentralized system, and the second column is the smart contracts, which are an automatic self-execution contractual program. This article provides a legal analysis of smart contracts and concludes that the application of the blockchain technology in smart contracts should be considered a guarantee to the contractual performance. Furthermore, the regulations that apply to smart contracts should focus on the codes inserted in, rather than the performance.

The wireless sensor network is the core of the Internet of Things. However, wireless sensors have some limitations and challenges, such as limited power and computing power, data storage, and network bandwidth, especially power requirements. How to find a way to program more flexible and faster according to the state of each sensing node in the network becomes an important issue. The software-defined network separates the control functions from the hardware devices, such as switches or routers, so that these hardware devices only have the data forwarding function, and the control software dynamically controls the flow of the network and data packets according to the network state and application requirements. In order to provide flexibility and adaptability, software-defined networks require a dynamic approach to solving and optimizing routing planning problems. This study will use the artificial bee colony algorithm to monitor the state of the sensor nodes in the software-defined network through the controller and take the best decision dynamically. Artificial bee colony algorithms are used to optimize wireless sensor networks and improve sensor node energy usage and data packets routing issues. The contribution of this research is to dynamically find the optimal routing path for the sensing nodes through the artificial bee colony algorithm, and improve the overall practicability and reliability of the wireless sensor network.

The aim of the paper is to compare different network protocols which are available for Internet of Things (IoT) systems in different industries and also to define the best practices for using these protocols in different IoT applications. IoT is a huge ecosystem of connected smart devices and objects which gathers enormous amount of data that needs to be captured, processed and communicated to and from the cloud system. The network protocols are compared based on the different IoT systems architecture and connections including smart object to object (O2O), smart object to gateway, gateway to data centers and between data centers. Furthermore, they are grouped based upon different network ranges and network topologies. Selecting the best protocol for IoT application is centered upon the proposed three-dimensional network design model which equates each of the communication protocols against the three axes of the model which are the battery life, device duty cycle and device to gateway range.

In the past, we studied the activities of Asian parti-colored (APC) bats through visual observation, which is very labor intensive. This paper develops an IoT platform called BatTalk to continuously monitor the APC bats population, understand its compositional changes, life history, and environmental factors. With BatTalk, the above visual observations can be achieved with reduced man power and minimal interference to the bat activities. The most important task is to use BatTalk to automate the process to understand APC bats’ regular annual cycle of life history and estimate the percentage of the baby bats born and raised there would return to their original habitat in the coming year. Also, we proposed an inexpensive manner to identify the bat habitats and bat movement paths by identifying the bat’s ultrasonic signal strength and GPS position, and then show the information in a map.

Owing to the issue of silver tsunami, the number of widow and widower arises day by day. Patient’s families couldn’t accompany elders due to the job. Thus, the elders’ self-care ability becomes an ordeal in daily lives. Even if the advanced medical tech allows elders to have a perfect medical service or to enhance his/her self-care ability, the medical institution is still facing the heavy-burden predicament because of the short of medical manpower and the restriction of medical resource while most caring services are concentrated in hospital or institution, and fail to decentralize them to various home environments. Whereas the target of “Aging in place” sets in the Long-term Care 2.0, we extend the professional care to individual resident through Long-term Care A, B, and C, and to relieve the pressure of Chinese-type treatment and the hardship of long journey. Nevertheless, the popularizing performance is confined due to lack of self-care environment and professional integrating care platform for elders.

We intend to use the module of medical internet to conduct clinical field simulation and deployment, through multiple transit technique and fog-computing environment to produce an appropriate aging-care module. It is livable for patients’ health, and can save the unnecessarily medical resource and the manpower cost expenditure. Such a module can be extended to broaden the range of medical service, introduction of smart high-tech, create a livable environment for elders’ healthcare and life.

The evaluation mechanism of land expropriation policy has contributed a lot for land acquisition in Taiwan. The purpose of this study is to investigate the result of Internet application to evaluation of land expropriation by means of evaluating land expropriation policy, interviewing professional experts, employing Analytical hierarchy process (AHP), ranking of different factor weight, and prioritizing various factors and dimensions in order to provide relevant information and reference for further development.

Edge computing services are contingent on several constraints. There is a requirement needed to provide a proper function, such as low latency, low energy consumption, and high performance. Object detection analysis involves high power resources, it is because of the need to process the images or videos. In this paper, the architecture of edge computing for object recognition is proposed, and the performance of the edge node is examined. The resources performance comparison on Raspberry Pi and Neural Compute Stick are inspected. This study combined the Neural Compute Stick (NCS) to enhance the ability of image processing on Raspberry Pi. Through the aid of NCS, the Raspberry Pi’s frames per second (FPS) is increased by four times when the object detection program is executed, and the energy consumption of the Raspberry Pi is also recorded.

Cloud computing enables a user to access and analysis the data at any time, anywhere, and any devices with internet access. However, the need for faster and more reliable cannot adequately be handled by cloud computing. By combining cloud computing and edge computing along with low power wide area networks (LoRaWAN), it can provide excellent services. In this paper, a campus air quality using edge computing monitoring system and integrated Arduino and LoRaWAN air quality sensor was proposed. The air quality monitoring data collected by the LoRaWAN sensor is visualized using a web page to monitor and analyze the real-time air pollution data. The air quality data obtained from the open government data and LoRaWAN sensors.

The use of OFDM modulation has become a priority in recent years as it is an ideal platform for wireless data transmissions. Its implementation can be seen in most of the newer broadband and high bit rate wireless systems, including Wi-Fi, cellular telecommunications and more. This is due to the many benefits this technology provides. These include immunity to selective fading, intersymbol interference resistance, intercarrier interference resistance, more efficient spectrum utilization and simpler channel equalization.

But with the increasing demand from users, the scarcity of the radio spectrum and the use of OFDM for a large number of recent wireless applications, the optimization of bandwidth and signal quality must be a major concern.

Thus, in this paper, we propose in a multipath Additive White Gaussian Noise environment, a more efficient wireless transmission system that combines OFDM and CDMA techniques. It is a 4-QAM OFDM-CDMA synchronous multiuser system that uses OVSF codes to differentiate users. It can be applied on the downlink of a wireless cellular system based on a simple OFDM access and even be a system for 5th generation mobiles where OFDM is considered in combination with a multiple access technique.

It turns out that, compared to a 4-QAM OFDM single-user system, a 4-QAM OFDM-CDMA synchronous multi-user system offers better performances that increase with SF the length of the OVSF codes used to differenciate users.

Thus with SF = 32 and in the case of a six paths Additive White Gaussian Noise channel, a user of a 4-QAM OFDM-CDMA system can share the same OFDM subcarriers with twenty (20) other users of the same system and have a lower BER than a user of a 4-QAM OFDM single-user system having the same power profiles.

It is therefore possible with values of SF greater than or equal to 32, to optimize bandwidth and signal quality in systems based on an OFDM access.

With the rapid development of wireless local area network (WLAN) and the proliferation of intelligent terminals, the current WLAN protocol is no longer able to meet the needs of users. Therefore, the next generation WLAN: IEEE 802.11ax has emerged to meet the growing demand for user traffic. Orthogonal Frequency Division Multiple Access (OFDMA), which enables simultaneous transmission of data by different User Equipment (UEs), is considered to be one of the key technologies of IEEE 802.11ax. In order to achieve high throughput rates and low access latency to ensure quality of service (QoS), IEEE 802.11ax supports two uplink access modes: scheduling access and random access. However, how to adaptively and efficiently switch these two access mechanisms in the process of real-time operation of the system, and effectively reduce the drawbacks caused by these two mechanisms is a thorny problem. This paper proposes an evaluation mechanism of network traffic load based on OFDMA-MAC protocol, and its performance is verified by simulation. The simulation results show that the traffic load assessment mechanism effectively improves the network throughput and quality of service (QoS), and also adapts to the dynamic changes in network traffic.

Wireless LAN (WLAN) developed quite fast over the last two decades, and the next generation WLAN standard: IEEE 802.11ax will be released in 2020. IEEE 802.11ax needs to improve the performance and user experience under the ultra-high-dense deployment of cells. Thus, the concept of spatial reuse (SR) is introduced in IEEE 802.11ax by enabling more communication links to simultaneously transmit. This paper proposes an environment sensing based link adaptation algorithm (ESBLA). ESBLA introduces intelligent environment sensing and identifies the environment into several types: nice environment, serious collision, and severe channel fading. After that, ESBLA adjust the media access control (MAC) layer transmission strategy according to the sensed environment type. The simulation results show that ESBLA can reduce the impact of intensive deployment interference as much as possible while guaranteeing high throughput.

Wireless LAN (WLAN) based on IEEE 802.11 protocol standard is widely used due to its advantages of low cost, fast speed, flexibility and convenience. Among them, the coverage distance of the millimeter wave (mmWave) WiFi such as IEEE 802.11ay is relatively short. In order to meet the needs of Virtual Reality (VR), high definition (HD) video and other emerging services, mmWave WiFi often adopts high-dense deployment. The mobility of nodes often causes multi-BSS handoff. MmWave WiFi handoff process is complex and consumes a lot of network signaling and time. Based on the advantages of multi-BSS association and cooperation, this paper designs a handoff protocol for mmWave WiFi to complete multi-BSS handoff without interruption of business continuity. Through simulation verification and comparison with other multi-BSS handoff technologies, proposed protocol improves the throughput and reduces the time delay.

The great variety of modern networked applications, e.g., online computer games, cloud host backups, video conferencing, etc. bring significant differences in their usage scenarios. Therefore, they impose very different QoS (Quality of Service) requirements on network communication. In particular, traditional multicast implementations cannot react adequately to the potentially very dynamic application requirements at run time. In this paper, we suggest a novel Plug-in Multicast Framework (PiMF) placed on top of an existing multicast framework. PiMF can modify the topology of the multicast tree during the application’s run time, thus providing QoS guarantees for multicast communication. We design our plug-in framework using the emerging SDN (Software-Defined Networking) technology, and we especially address the challenge of non-interfering behavior of PiMF with respect to the underlying multicast implementation. We evaluate the correctness and performance of our plug-in framework in detailed simulation experiments.

Along with the fast development of Internet technology, cross-border E-commerce is also exhibiting an extremely strong growth trend. Among the many problems derived from this new type of cross-border trade, the intellectual property issue is even more complex, and there are many difficulties emerging in governance and rights protection. These difficulties lie in the fact that the conflict between E-commerce and regional intellectual property protection also comes from the lag of technological innovation and legal regulation, with conflicts arising from inadequate international coordination and other realistic causes. The snags in intellectual property protection are also due to the conceptual factor of the conflict between efficiency and fairness. Thus, in order to effectively solve these difficulties, this paper holds that the government, cross-border E-commerce enterprises, intellectual property holders, civil collective forces, and governance bodies at home and abroad should conduct diversified collaboration with one another. In addition, relevant data and an expert talent database should be established, a framework for cross-border E-commerce intellectual property governance and protection must be jointly built, and greater efforts can be made for the sound development of cross-border E-commerce.

With the advancement of Internet technology and the rise of e-commerce, Big Data Analytics can be applied to assess service quality for e-commerce industry achieving customer relationship improvement and reflecting the service quality of transaction. Online bookstore is a form of electronic commerce which allows consumers to directly buy books or services from a seller over the Internet using a web browser or a app program. Most researches are focus on expert opinion or few sample to measure the critical criteria. The goal of this study is to explore and demonstrate the utility of big data analytics by using it to study core online bookstore service quality variables that have been extensively studied in past decades. Text analysis method to extract a large number of consumer reviews from Amazon to deconstruct the bookstore customer experience and examine its relationship with satisfaction. This paper proposed a framework that integration of big data analytic and SERVQUAL model to measure the importance and relationship of service quality criteria. How to provide a level of service quality that satisfies consumers is an important issue for operators of online bookstores. Further research will apply Amazon data set to evaluate the criteria.