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Designing an efficient routing protocol that opportunistically forwards data to the destination node through nearby sensor nodes or devices is significantly important for an effective incidence response and disaster recovery framework. Existing sensor routing protocols are mostly not effective in such disaster recovery applications as the networks are affected (destroyed or overused) in disasters such as earthquake, flood, Tsunami and wildfire. These protocols require a large number of message transmissions to reestablish the clusters and communications that is not energy efficient and result in packet loss. This paper introduces ODCR - an energy efficient and reliable opportunistic density clustered-based routing protocol for such emergency sensor applications. We perform simulation to measure the performance of ODCR protocol in terms of network energy consumptions, throughput and packet loss ratio. Simulation results demonstrate that the ODCR protocol is much better than the existing TEEN, LEACH and LORA protocols in term of these performance metrics.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

Routing protocol for low-power lossy network (RPL) being the de facto routing protocol used by low power lossy networks needs to provide adequate routing service to mobile nodes (MNs) in the network. As RPL is designed to work under constraint power requirements, its route updating frequency is not sufficient for MNs in the network. The purpose of this study is to ensure that MNs enjoy seamless connection throughout the network with minimal handover delay.

This study proposes a load balancing mobility aware secure hybrid – RPL in which static node (SN) identifies route using metrics like expected transmission count, and path delay and parent selection are further refined by working on remaining energy for identifying the primary route and queue availability for secondary route maintenance. MNs identify route with the help of smart timers and by using received signal strength indicator sampling of parent and neighbor nodes. In this work, MNs are also secured against rank attack in RPL.

This model produces favorable result in terms of packet delivery ratio, delay, energy consumption and number of living nodes in the network when compared with different RPL protocols with mobility support. The proposed model reduces packet retransmission in the network by a large margin by providing load balancing to SNs and seamless connection to MNs.

In this work, a novel algorithm was developed to provide seamless handover for MNs in network. Suitable technique was developed to provide load balancing to SNs in network by maintaining appropriate secondary route.

The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

Using bibliometrics, this study aims to explore the intellectual structure of social segregation research, key contributors, thematic areas and hotspot topics.

A bibliometric analysis was performed for more than 15,000 research papers listed in one of the famous, rich and widely used scientific databases: Web of Science (WoS). This review approach was used to identify social research hotspots on segregation, intellectual structure, borders and development trends. VOSviewer and Gephi software were employed for mapping and analysis.

The study indicates a marked increase in segregation research, particularly from a spatial/urban perspective. The study reveals the interrelationship between segregation and many other social concepts, such as social equality, cohesion, integration and inclusion. In conclusion, addressing the ramifications resulting from the multiple forms of segregation will help in implementing social policies and evaluating their impact on achieving inclusive social development in general and the 2030 agenda of Sustainable Development Goals (SDGs) in specific.

This study remains limited to the precision and thoroughness of the bibliographic data gained from WoS.

This study is valuable for readers to gain rich insights into the state of research on social segregation. It also provides ideas for future research that prospective authors and interested research and academic institutions can investigate.

With the rise in demand and adoption of smart city initiatives, it is imperative to plan the railway infrastructure, as it will have a huge positive impact if adequately integrated into the planning process. Given the complexities involved, a whole systems thinking framework provides a useful platform for rail transport planners.

This paper proposes a simple, adoptable framework utilising systems thinking concepts and techniques taking into cognisance the key stakeholders. Milton Keynes in the United Kingdom is the adopted case study.

Selected systems thinking tools and techniques are adopted to develop a framework for mapping stakeholders and attributes when developing sustainable rail transport systems, taking note of their core functionalities and the complex systems wherein they exist.

The desire to build future (smart) cities is to effectively match infrastructural resources with a rapidly growing population, and the railway sector can play a strategic role in building a much more competitive low-carbon-emission transport system, which is a driving force for sustainable development.

The urban rail service has become vital to urban development as railway stations serve as hubs for sustainable mobility to meet local requirements. Moreover, it takes extra effort to input railway development into smart city plans, as it is a herculean task to get governments to focus on it with clarity of purpose in passing legislation.

The developed framework reduces complexities when planning and designing rail transport systems compared to many of the existing reductionist planning approaches. The simplicity of the framework would also make it easily adoptable by a wide range of users.

Presently, existing electric car sharing platforms are based on a centralized architecture which are faced with inadequate trust and pricing issues as these platforms requires an intermediary to maintain users’ data and handle transactions between participants. Therefore, this article aims to develop a decentralized peer-to-peer electric car sharing prototype framework that offers trustable and cost transparency.

This study employs a systematic review and data were collected from the literature and existing technical report documents after which content analysis is carried out to identify current problems and state-of-the-art electric car sharing. A use case scenario was then presented to preliminarily validate and show how the developed prototype framework addresses the trust-lessness in electric car sharing via distributed ledger technologies (DLTs).

Findings from this study present a use case scenario that depicts how businesses can design and implement a distributed peer-to-peer electric car sharing platforms based on IOTA technology, smart contracts and IOTA eWallet. Main findings from this study unlock the tremendous potential of DLT to foster sustainable road transportation. By employing a token-based approach this study enables electric car sharing that promotes sustainable road transportation.

Practically the developed decentralized prototype framework provides improved cost transparency and fairness guarantees as it is not based on a centralized price management system. The DLT based decentralized prototype framework aids to orchestrate the incentivize monetization and rewarding mechanisms among participants that share their electric cars enabling them to collaborate towards lessening CO₂ emissions.

The findings advocate that electric vehicle sharing has become an essential component of sustainable road transportation by increasing electric car utilization and decreasing the number of vehicles on the road.

The key novelty of the article is introducing a decentralized prototype framework to be employed to develop an electric car sharing solution without a central control or governance, which improves cost transparency. As compared to prior centralized platforms, the prototype framework employs IOTA technology smart contracts and IOTA eWallet to improve mobility related services.

The digital media recording and broadcasting classroom using Internet real-time intelligent image positioning and opinion monitoring in communication teaching is researched and analyzed.

First, spatial grid positioning and monitoring and image intelligent recognition technologies were used to extract and analyze teaching images by mastering Internet of Things (IoT) technology and establishing an intelligent image positioning and opinion monitoring digital media recording and broadcasting system framework. Next, a positioning node algorithm was utilized to measure the image distance, and then a moving node location model under the IoT was established. In addition, a radial basis function (RBF) neural network was used to realize the signal transmission function. The experimental data of the adopted RBF based on the optimization of the adaptive cuckoo search (ACS-RBF) neural network, particle swarm algorithm neural network, and method of least squares optimization were compared and analyzed. In addition, a more efficient RBF neural network was adopted. Finally, the digital media recording and broadcasting classroom scheme of real-time intelligent image positioning and opinion monitoring was designed. In addition, the application environment of digital media actual teacher teaching was detected, and recording and broadcasting pictures were analyzed and researched.

The actual value, predicted value, and the number of predicted samples of the ACS-RBF model were all better than those of the two other neural networks. According to the analysis and comparison of the sampling optimization Monte Carlo localization (SOMCL), Monte Carlo, and genetic algorithm optimization-based Monte Carlo positioning algorithms, the SOMCL algorithm showed better robustness, and its positioning efficiency was superior to that of the two other algorithms. In addition, the SOMCL algorithm greatly reduced the positioning and monitoring energy consumption.

The application of real-time intelligent image positioning and monitoring technology in actual communication teaching was realized in the study.

Cloud computing originated in central data centers that are connected to the backbone of the Internet. The network transport to and from a distant data center incurs long latencies that hinder modern low-latency applications. In order to flexibly support the computing demands of users, cloud computing is evolving toward a continuum of cloud computing resources that are distributed between the end users and a distant data center. The purpose of this review paper is to concisely summarize the state-of-the-art in the evolving cloud computing field and to outline research imperatives.

The authors identify two main dimensions (or axes) of development of cloud computing: the trend toward flexibility of scaling computing resources, which the authors denote as Flex-Cloud, and the trend toward ubiquitous cloud computing, which the authors denote as Ubi-Cloud. Along these two axes of Flex-Cloud and Ubi-Cloud, the authors review the existing research and development and identify pressing open problems.

The authors find that extensive research and development efforts have addressed some Ubi-Cloud and Flex-Cloud challenges resulting in exciting advances to date. However, a wide array of research challenges remains open, thus providing a fertile field for future research and development.

This review paper is the first to define the concept of the Ubi-Flex-Cloud as the two-dimensional research and design space for cloud computing research and development. The Ubi-Flex-Cloud concept can serve as a foundation and reference framework for planning and positioning future cloud computing research and development efforts.

The paper aims to provide an overview of the state-of-the-art of the event industry in the context of digitalization to understand how digital technologies change the event industry and what research topics are the most promising for further exploration.

A bibliometric analysis of the existing body of knowledge on the topic was conducted and the results were visualized using CiteSpace 5.8.R3. A total of 1999 articles and proceeding papers from the Web of Science Core Collection published between 2007 and 2022 were selected for our analysis. Based on the articles and proceeding papers in the Web of Science Core Collection database, we selected a set of publications for our analysis. The data were obtained through specific keywords related to our research topic. The method involves a process of three main stages: data collection, data processing and the bibliometric analysis.

Co-citation analysis indicated that issues of crowd management and tracking human mobility during mass events are important for the event industry and that technologies such as the Internet of Things, special-purpose mobile applications and systems make it easier for an event organizer to handle the issues. The findings demonstrated a weak scientific collaboration between countries in the topic studied and shift of research hotspots to study of satisfaction, motivation and behavioral patterns of events attendees. Based on this analysis, three directions for future research were revealed.

The results should be interpreted in light of our sample, because the analysis was conducted within our sample which has boundaries. We collected data from all categories in the Web of Science Core Collection database, but we considered only articles and proceeding papers as opposed to all possible types of scientific publications and other databases. In the study, we focused on detecting the state-of-the-art of the event industry in the context of digitalization overall. More specific topics that could be analyzed remain, for example, the dependency of digital technologies from the event type, etc.

This study reflects the state-of-the-art of the event industry in the context of digitalization. It provides researchers with key developmental trends in the event industry, which assists them in more deeply understanding the evolution of research hotspots in the field during last 15 years and defining future research agenda. The paper presents an overview of digital technologies used in various types of events and describes the issues and results related to the implementing digital technologies. The results obtained were extremely important, as they can be used by event managers and organizers to enhance customers’ experience during the events.

This study reflects the state-of-the-art of the event industry in the context of digitalization. This is the first attempt to make an overall analysis of scientific papers published in the Web of Science Core Collection on the topic studied without excluding any categories. The search procedure is transparent, and the results can be reproduced in other search fields using the same approach. Based on this analysis, three directions for future research were revealed including technological aspects of online event-based social networks, issues of crowd management and security at mass events and issues of attendees’ acceptance of novel digital technologies.