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Fog computing has become an attractive computing method for different IoT (Internet of Things) applications that require low latency and location awareness. It provides low latency by bringing computational power closer to the network edge, working as a complement to cloud computing. Despite its advantages, fog computing faces challenges due to the limited resources (CPU processing capacity, network bandwidth, memory, and power backup) of fog nodes. This work introduces a novel optimization model for a cooperative fog-cloud environment dealing with dynamic traffic. We analyze how different arrival rates impact bandwidth costs, link utilization, and server resource utilization. Our results show that fog resource utilization is greater than cloud resource utilization under varying traffic conditions, with blocking rates remaining within an acceptable range (0-15%). The key contributions include the formulation of an optimization model that optimizes resource allocation, addresses blocking factors in fog networks, and offers valuable insights for managing dynamic traffic in fog computing networks.

Low-Earth Orbit Satellite Constellations (LEO-SCs) provide global, high-speed, and low latency Internet access services, which bridges the digital divide in the remote areas. As inter-satellite links are not supported in initial deployment (i.e. the Starlink), the communication between satellites is based on ground stations with radio frequency signals. Due to the rapid movement of satellites, this hybrid topology of LEO-SCs and ground stations is time-varying, which imposes a major challenge to uninterrupted service provisioning and network management. In this paper, we focus on solving two notable problems in such a ground station-assisted LEO-SC topology, i.e., traffic engineering and fast reroute, to guarantee that the packets are forwarded in a balanced and uninterrupted manner. Specifically, we employ segment routing to support the arbitrary path routing in LEO-SCs. To solve the traffic engineering problem, we proposed two source routings with traffic splitting algorithms, Delay-Bounded Traffic Splitting (DBTS) and DBTS+, where DBTS equally splits a flow and DBTS ​+ ​favors shorter paths. Simulation results show that DBTS ​+ ​can achieve about 30% lower maximum satellite load at the cost of about 10% more delay. To guarantee the fast recovery of failures, two fast reroute mechanisms, Loop-Free Alternate (LFA) and LFA+, are studied, where LFA pre-computes an alternate next-hop as a backup while LFA ​+ ​finds a 2-segment backup path. We show that LFA ​+ ​can increase the percentage of protection coverage by about 15%.

An important technique to optimize a network and improve network robustness is traffic engineering. As traffic demand increases, traffic engineering can reduce service degradation and failure in the network. To allow a network to adapt to changes in the traffic pattern, the research community proposed several traffic engineering techniques for the traditional networking architecture. However, the traditional network architecture is difficult to manage. Software Defined Networking (SDN) is a new networking model, which decouples the control plane and data plane of the networking devices. It promises to simplify network management, introduces network programmability, and provides a global view of network state. To exploit the potential of SDN, new traffic engineering methods are required. This paper surveys the state of the art in traffic engineering techniques with an emphasis on traffic engineering for SDN. It focuses on some of the traffic engineering methods for the traditional network architecture and the lessons that can be learned from them for better traffic engineering methods for SDN-based networks. This paper also explores the research challenges and future directions for SDN traffic engineering solutions. [ABSTRACT FROM AUTHOR]

Abstract Software-defined networking (SDN) revolutionizes network administration by centralizing control and decoupling the data plane from the control plane. Despite its advantages, the escalating volume of network traffic induces congestion at nodes, adversely affecting routing quality and overall performance. Addressing congestion has become imperative due to its emergence as a fundamental challenge in network management. Previous strategies often faced drawbacks in handling congestion, with issues arising from the inability to efficiently manage heavy packet surges in specific network regions. In response, this research introduces a novel approach integrating a multiplicative gated recurrent neural network with a congestion-aware hunter prey optimization (HPO) algorithm for effective traffic management in SDN. The framework leverages machine learning and deep learning techniques, acknowledged for their proficiency in processing traffic data. Comparative simulations showcase the congestion-aware HPO algorithm's superiority, achieving a normalized throughput 3.4–7.6% higher than genetic algorithm (GA) and particle swarm optimization (PSO) alternatives. Notably, the proposed framework significantly reduces data transmission delays by 58–65% compared to the GA and PSO algorithms. This research not only contributes a state-of-the-art solution but also addresses drawbacks observed in existing methodologies, thereby advancing the field of traffic engineering and congestion management in SDN. The proposed framework demonstrates notable enhancements in both throughput and latency, providing a more robust foundation for future SDN implementations.

As a result of the ubiquitous network applications and services, exacerbated by the overarching digital revolution the need and demand for efficient and dependable connectivity solutions have surged to unprecedented levels. Quality of Service (QoS)-based routing has emerged as a critical solution, enabling service differentiation, efficient resource allocation, and improved network performance. In this study, we introduce a novel Genetic Algorithm-powered QoS-aware Cross-Network Traffic Engineering framework, GATE-BC, at the confluence of Software Defined Networking (SDN) and Blockchain (BC) technologies. GATE-BC orchestrates end-to-end (E2E) QoS traffic, providing resource-efficient, reliable, and latency-tolerant delivery of intelligent network services in BC-enabled SDNs. Leveraging BC features such as decentralization, transparency, and immutability, GATE-BC eliminates the need for centralized entities in QoS-supported cross-network routing models. We compare GATE-BC framework with three other traffic management and engineering approaches: QoSChain (QC), Hierarchical Routing Approach (HRA), and Distributed Routing Approach (DRA). The extensive simulations reveal that GATE-BC outperforms the other routing strategies in terms of Path Setup Time (PST), Network Message Overhead (NMO), Request Acceptance Ratio (RAR), Network Bandwidth Consumption (NBC), Average Path Length (APL), and Average Network Length (ANL) metrics under various network topologies. Furthermore, GATE-BC employs three different feasible path selection strategies based on bandwidth (GATE-BC_BW), delay (GATE-BC_D), and reliability (GATE-BC_R) QoS parameters to satisfy the service levels requested.

This article embarks on a detailed examination of the square Dolní Náměstí in the town of Odolená Voda, concentrating on the implications of implementing shared spaces from perspectives of safety and traffic management. In the study advanced surveillance technologies were employed to systematically document the movements of a variety of road users, serving to pinpoint potential conflict zones. This designation underscores the necessity to reassess urban design and traffic control strategies to meet modern safety standards. Efforts were directed towards aligning urban infrastructure with pedestrian movement patterns, aiming to diminish safety risks and augment accessibility. The study hypothesizes that certain strategic alterations in urban design, such as the realignment of pedestrian pathways and the imposition of vehicle speed controls, could considerably improve the quality of shared spaces. Central to this research is the ambition to forge a new methodological framework for assessing the capacity of shared spaces mathematically. This initiative seeks to fill a significant research gap by quantitatively evaluating the capacity of shared spaces to fulfil a varied set of urban mobility requirements. This framework aims to establish a foundation for the systematic appraisal and enhancement of shared spaces. Recommendations for urban planners and traffic engineers are presented, promoting a design strategy that merges pedestrian preferences with traffic management objectives to cultivate safer, more efficient, and universally accessible urban areas. These recommendations endeavor to steer the evolution of shared spaces towards a harmonious balance of user needs. This work aims to make a substantive contribution to urban planning, traffic management, and pedestrian safety domains, paving the way for future exploratory studies and practical deployments in shared space advancements. It emphasizes the critical need to integrate both vehicular and pedestrian considerations into urban design processes, striving to create urban spaces conducive to sustainable mobility and improved urban living standards.

Lane changing behavior, a pivotal aspect of vehicular dynamics, significantly influences traffic flow, safety, and overall road network efficiency. This review article synthesizes the current body of knowledge surrounding lane changing behavior, encompassing both mandatory and discretionary lane changes. The intricate interplay between various factors, including speed differentials, driver characteristics, road geometry, and external stimuli, shape the decision-making processes underlying lane changes. The article explores the underlying psychological, cognitive, and socio-demographic influences on lane changing behavior, highlighting the role of emerging technologies such as advanced driver assistance systems (ADAS) and vehicle-to-vehicle (V2V) communication. Furthermore, the review delves into existing models and methodologies employed to analyze lane changing behavior, addressing their limitations and potential for advancement. Real-world applications, such as work zones and incident management, are examined to underline the practical implications of understanding and predicting lane changing behavior. By presenting a comprehensive overview of the subject, this review aims to deepen the understanding of the complexities inherent in lane changing behavior, facilitating informed decision-making for traffic management, safety enhancement, and future research endeavors.

This research aims to examine the traffic road safety curriculum, which is the extraordinary curriculum for children in Thailand. This educates about traffic road safety to children based on traffic engineering knowledge. The entire content of the curriculum is based on case studies that depict both hazardous and safe situations. It covers all road users, including pedestrians, intersection rules, private vehicle users, and public transportation users. In this research, animations are used instead of actual crash recordings to minimize the negative impact of severity. As this curriculum is new and not a part of the standard curriculum for children in Thailand, ensuring an effective curriculum and learning processes is crucial. Therefore, assessing the curriculum from actual users is one of the approaches to check and maintain the effectiveness of the curriculum. Direct assessments, both formative and summative, are conducted to evaluate children's learning abilities regarding traffic safety before and after training. Statistical analysis of the data reveals that the fundamental knowledge of traffic safety in children increases by 20.28 percent after training. The study shows that students are more likely to change their behaviors towards increased safety, with an average change of 34.30 percent. When evaluating satisfaction with the traffic safety training activities, most participating students express a high level of satisfaction with the teaching materials and lesson contents. It is evident that the curriculum is highly effective in enhancing learning skills while providing an enjoyable and participatory experience. Ultimately, the ones who benefit from this curriculum are the teachers who implement it and the children who will come to learn and absorb the knowledge and practices related to safety. The hope is that this curriculum will help increase awareness of safety among children and have a positive impact on their road usage behavior, making it safer in the future. [ABSTRACT FROM AUTHOR]

Traffic Engineering (TE) enables management of traffic in a manner that optimizes utilization of network resources in an efficient and balanced manner. However, existing TE solutions face issues relating to scalability and complexity. In recent years, Segment Routing (SR) has emerged as a promising source routing paradigm. As one of the most important applications of SR, Segment Routing Traffic Engineering (SR-TE), which enables a headend to steer traffic along specific paths represented as ordered lists of instructions called segment lists, has the capability to overcome the above challenges due to its flexibility and scalability. In this paper, we conduct a comprehensive survey on SR-TE. A thorough review of SR-TE architecture is provided in the first place, reviewing the core components and implementation of SR-TE such as SR Policy, Flexible Algorithm and SR-native algorithm. Strengths of SR-TE are also discussed, as well as its major challenges. Next, we dwell on the recent SR-TE researches on routing optimization with various intents, e.g., optimization on link utilization, throughput, QoE (Quality of Experience) and energy consumption. Afterwards, node management for SR-TE are investigated, including SR node deployment and candidate node selection. Finally, we discuss the existing challenges of current research activities and propose several research directions worth of future exploration.

Perkembangan penggunaan internet di Indonesia saat ini mengalami peningkatan yang sangat pesat. Dilihat dari peningkatan jumlah pengguna internet tersebut maka secara tidak langsung fitur dan layanan yang disediakan turut berkembang. Salah satu fitur tersebut adalah layanan video dan audio. Layanan video dan audio termasuk dalam layanan multimedia streaming. Pertukaran informasi yang begitu cepat dan beragam menjadi alasan bahwa jenis file video lebih banyak dinikmati karena sudah mengandung informasi gambar bergerak dan audio. Namun terdapat beberapa permasalahan yang mempengaruhi performansi dari video streaming, seperti laju transmisi yang lambat, sehingga diperlukan QoS (Quality of Service) yang baik pada sisi streaming server. Maka dari itu dikembangkan sebuah jaringan MPLS Traffic Engineering yang menggabungkan metode Differentiated Service untuk menjawab permasalahan tersebut. Pada penelitian ini diimplementasikan jaringan MPLS TE dan jaringan MPLS TE Diffserv pengujian dilakukan pada layanan video streaming. Hasil dari penelitian didapatkan bahwa nilai delay,jitter,throughput dan packet loss mengalami perbaikan setelah ditambahkan metode Differentiated Service. Untuk nilai delay berkisar pada rentang 150 ms, nilai throughput berkisar pada rentang 55000 bits/s hingga 56000 bits/s,nilai standar deviasi jitter pada rentang 300 ms dan untuk packet loss 0%.