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This paper aims to survey the need for full capacity utilisation of transmission lines in power systems network operations. It proposes a review of the N-1 security criterion that does not ensure reliable dispatch of optimum power flow during outage contingency. The survey aims to enlarge the network capacity utilisation to rely on the entire transmission lines network operation.

The paper suggests transmission line switching (TLS) approach as a viable corrective mechanism for power dispatch. The TLS process is incorporated into a constraint programming language extension optimisation solver that selects the switchable line candidates as integer variables in the mixed integer programming problem.

The paper provides a practical awareness of reserve capacity in the lines that provide network security in outage contingency. At optimum power flow dispatch, the TLS is extended to optimal transmission line switching (OTLS) that indicates optimal capacity utilisation (OCU) of the available reserve capacity (ARC) in the network lines.

Computational efficiency influenced the extension of the OTLS to optimal transmission switching of power flow (OTSPF). The application of OTSPF helps reduce the use of flexible AC transmission systems (FACTS) and construction of new transmission lines..

The paper surveys TLS efforts in network capacity utilisation. The suggested ARC fulfils the need for an index with which the dispatchable lines may be identified for the optimal capacity utilisation of transmission lines network.

This article provides a broad overview of telecommunications and network‐related technologies. Topics covered include identification and review of network elements, analog and digital signals, synchronous and asynchronous transmission formats, transmission media and equipment, transmission techniques and characteristics, multiplexing, network types, access technologies, network architectures and topologies, local‐area network technologies and attributes, protocols and protocol issues, gateways, internetworking, local networking alternatives, equipment certification, and various aspects of network management. It is intended to provide the practicing professional in the field of library and information science with a broad, up‐to‐date technical review that might serve to support and facilitate further investigation of current developments in networks and networking. Although the broad range of topics is not treated in depth, numerous references are provided for further investigation.

This study aims to the information about consumer product quality and safety that can easily attract public attention and become the focus of public opinion. In recent years, the fast-growing social media have become an import platform for firms for releasing product quality and safety information and for firms and governments to hear public opinion.

To explore how information about consumer product quality and safety gets disseminated and a public opinion is formed in social media, this paper proposes two information transmission models, one with government intervention and the other without government intervention, based on the theory of complex network. A simulation case study in MATLAB is conducted to verify the proposed models.

Information transmission models were constructed, one without government intervention and one with government intervention. The influence of information transmission with government intervention was analyzed. MATLAB was used to simulate the Barabasi and Albert (BA)-based model to consider event information level, government information level and possible panic population proportion. The government intervention effect was evaluated.

Based on a complex network, the derived transmission rule can provide decision-making support for monitoring and managing Web information of consumer product quality and safety.

Time slot allocation in world interoperability for microwave access (WiMax) mesh networks is controlled by a centralized scheduling algorithm, as specified in the IEEE standard 802.16. The scheduling algorithm should be able to minimize the total transmission time for all traffic flows. The purpose of this paper is to investigate the multi‐channel scheduling problem in WiMax mesh networks, in order to explore the potential of simultaneous transmissions and thus minimize the total transmission time.

The paper first analyzes how many channels are sufficient for the avoidance of interference, then presents an efficient scheduling algorithm along with the channel assignment strategy for time slot allocation. Particularly, for networks with chain topology, the paper provides an optimal solution to minimize the total transmission time.

The simulation results show that this scheme can improve the system performance substantially as compared with the single‐channel system. Also, it is observed that double‐channel settings may provide a performance similar to the multiple channels.

The algorithm presented in this paper is conformed to the IEEE standard 802.16‐2004; so it is suitable for WiMax mesh networks.

The paper is of value in presenting a scheduling and channel assignment schema for multi‐channel WiMax mesh networks. The work is also important for the study of time division multiple access (TDMA)‐based multi‐channel wireless mesh networks.

With the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network and by reducing the latency of transmitted data. The communications in IIoT and Industry 4.0 requires handshaking of multiple technologies for supporting heterogeneous networks and diverse protocols. IIoT applications may gather and analyse sensor data, allowing operators to monitor and manage production systems, resulting in considerable performance gains in automated processes. All IIoT applications are responsible for generating a vast set of data based on diverse characteristics. To obtain an optimum throughput in an IIoT environment requires efficiently processing of IIoT applications over communication channels. Because computing resources in the IIoT are limited, equitable resource allocation with the least amount of delay is the need of the IIoT applications. Although some existing scheduling strategies address delay concerns, faster transmission of data and optimal throughput should also be addressed along with the handling of transmission delay. Hence, this study aims to focus on a fair mechanism to handle throughput, transmission delay and faster transmission of data. The proposed work provides a link-scheduling algorithm termed as delay-aware resource allocation that allocates computing resources to computational-sensitive tasks by reducing overall latency and by increasing the overall throughput of the network. First of all, a multi-hop delay model is developed with multistep delay prediction using AI-federated neural network long–short-term memory (LSTM), which serves as a foundation for future design. Then, link-scheduling algorithm is designed for data routing in an efficient manner. The extensive experimental results reveal that the average end-to-end delay by considering processing, propagation, queueing and transmission delays is minimized with the proposed strategy. Experiments show that advances in machine learning have led to developing a smart, collaborative link scheduling algorithm for fairness-driven resource allocation with minimal delay and optimal throughput. The prediction performance of AI-federated LSTM is compared with the existing approaches and it outperforms over other techniques by achieving 98.2% accuracy.

With an increase of IoT devices, the demand for more IoT gateways has increased, which increases the cost of network infrastructure. As a result, the proposed system uses low-cost intermediate gateways in this study. Each gateway may use a different communication technology for data transmission within an IoT network. As a result, gateways are heterogeneous, with hardware support limited to the technologies associated with the wireless sensor networks. Data communication fairness at each gateway is achieved in an IoT network by considering dynamic IoT traffic and link-scheduling problems to achieve effective resource allocation in an IoT network. The two-phased solution is provided to solve these problems for improved data communication in heterogeneous networks achieving fairness. In the first phase, traffic is predicted using the LSTM network model to predict the dynamic traffic. In the second phase, efficient link selection per technology and link scheduling are achieved based on predicted load, the distance between gateways, link capacity and time required as per different technologies supported such as Bluetooth, Wi-Fi and Zigbee. It enhances data transmission fairness for all gateways, resulting in more data transmission achieving maximum throughput. Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation.

Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. It also shows that AI- and IoT-federated devices can communicate seamlessly over IoT networks in Industry 4.0.

The concept is a part of the original research work and can be adopted by Industry 4.0 for easy and seamless connectivity of AI and IoT-federated devices.

Social media, especially microblog, has become one of the most popular platforms for public opinion dissemination. However, so far few studies have been conducted to explore information dissemination under the mobile environment. This paper aims to introduce the approach to analyze the public opinion information dissemination in mobile social networks.

This paper chooses “network attack” as the research topic and extracts 23,567 relevant messages from Sina Microblogs to study the structure of nodes for public opinion dissemination and the characteristics of propagation paths on mobile internet. Public opinion dissemination is compared on both mobile and non-mobile terminals.

The results reveal the characteristics of public opinion dissemination in mobile environment and identify three patterns of information propagation path. This study concludes that public opinion on mobile internet propagates more widely and efficiently and generates more impact than that on the non-mobile internet.

The methods used in this study can be useful for the government and other organizations to analyze and identify problems in online information dissemination.

This paper explores the mechanism of public opinion dissemination on mobile internet in China and further investigates how to improve public opinion management through a case study related to “network attack.”

This paper aims to study the competition problems and market failures in the Canary Islands and propose an alternative management model for the telecommunication transmission network. This model is based on a wholesale-only open-access transmission network, available to all the retail service providers of this region, and managed by a unique entity subject to regulation with cost-based prices. The proposal hopefully will help to debate about the implementation of certain regulatory models in the network industries, concerning telecommunication submarine cables connecting archipelagos.

An empirical approach has been used, based on the observation and analysis of the regulatory policies applied to the wholesale transmission networks in the Canary Islands, Azores and Madeira archipelagos.

Results show a persistent margin squeeze situation on the retail broadband market in the Canary Islands, due to the pricing strategy on the Spanish mainland-Canaries wholesale market, which is, in turn, delaying the entry of alternatives and the level of development and efficiency of competition. The risk of duopoly collusion is also present on this wholesale market. Additionally, public aids will be needed to replace the systems connecting with the non-capital islands and to provide redundancy to El Hierro. The alternative proposal might help preventing the above. Eventually, several insights are considered for further investigation.

Little attention has been paid to this topic in the literature, regarding the analysis of regulatory policies applied over fiber optic submarine cable infrastructures in fragmented territories like archipelagos. Consequently, an empirical analysis has been accomplished to emphasize this research work, based on the regulatory policies adopted.

With the increasing acclaim of Wireless Sensor Networks and its diverse applications, research has been directed into optimising and prolonging the network lifetime. Energy efficiency has been a critical factor due to the energy resource impediment of batteries in sensor nodes. The proposed routing algorithm therefore aims at extending lifetime of sensors by enhancing load distribution in the network. The scheme is based on the chain-based routing technique of the PEGASIS (Power Energy GAthering in Sensor Information Systems) protocol and uses Ant Colony Optimisation to obtain the optimal chain. The contribution of the proposed work is the integration of the clustering method to PEGASIS with Ant Colony Optimisation to reduce redundancy of data, neighbour nodes distance and transmission delay associated with long links, and the employment an appropriate cluster head selection method. Simulation results indicates proposed method’s superiority in terms of residual energy along with considerable improvement regarding network lifetime, and significant reduction in delay when compared with existing PEGASIS protocol and optimised PEG-ACO chain respectively.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

Underwater shuttle is widely used in scenarios of deep sea transportation and observation. As messages are transmitted via the limited network, high transmission time-delay often leads to information congestion, worse control performance and even system crash. Moreover, due to the nonlinear issues with respect to shuttle’s heading motion, the delayed transmission also brings extra challenges. Hence, this paper aims to propose a co-designed method, for the purpose of network scheduling and motion controlling.

First, the message transmission scheduling is modeled as an optimization problem via adaptive genetic algorithm. The initial transmission time and the genetic operators are jointly encoded and adjusted to balance the payload in network. Then, the heading dynamic model is compensated for the delayed transmission, in which the parameters are unknown. Therefore, the adaptive sliding mode controller is designed to online estimate the parameters, for enhancing control precision and anti-interference ability. Finally, the method is evaluated by simulation.

The messages in network are well scheduled and the time delay is thus reduced, which increases the quality of service in network. The unknown parameters are estimated online, and the quality of control is enhanced. The control performance of the shuttle control system is thus increased.

The paper is the first to apply co-design method of message scheduling and attitude controlling for the underwater unmanned vehicle, which enhaces the control performance of the network control system.