Search

Routing in vehicular ad hoc networks (VANETs) enables vehicles to communicate for safety and non-safety applications. However, there are limitations in wireless communication that can degrade VANET performance, so it is crucial to optimize the operation of routing protocols to address this. Various routing protocols employed the expected transmission count (ETX) in their operation as one way to achieve the required efficiency and robustness. ETX is used to estimate link quality for improved route selection. While some studies have evaluated the utilization of ETX in specific protocols, they lack a comprehensive analysis across protocols under varied network conditions. This research provides a comprehensive comparative evaluation of ETX-based routing protocols for VANETs using the nomadic community mobility model. It covers a foundational routing protocol, ad hoc on-demand distance vector (AODV), as well as newer variants that utilize ETX, lightweight ETX (LETX), and power-based light reverse ETX (PLR-ETX), which are referred to herein as AODV-ETX, AODV-LETX, and AODV-PLR, respectively. The protocols are thoroughly analyzed via ns-3 simulations under different traffic and mobility scenarios. Our evaluation model considers five performance parameters including throughput, routing overhead, end-to-end delay, packet loss, and underutilization ratio. The analysis provides insight into designing robust and adaptive ETX routing for VANET to better serve emerging intelligent transportation system applications through a better understanding of protocol performance under different network conditions. The key findings show that ETX-optimized routing can provide significant performance enhancements in terms of end-to-end delay, throughput, routing overhead, packet loss and underutilization ratio. The extensive simulations demonstrated that AODV-PLR outperforms its counterparts AODV-ETX and AODV-LETX and the foundational AODV routing protocol across the performance metrics. [ABSTRACT FROM AUTHOR]

Vehicular Ad-hoc Networks (VANET) as the key correspondence organizing innovation has been pulled in by the scholarly world and enterprises with surprising turn of events. With each vehicle acting as a node in an ad hoc network made up of immobile or mobile vehicles, the VANET, which connects vehicles over a wireless connection, is a developing research field that is garnering prominence. The authors of this study examined real-time vehicles and the outcomes of four routing protocols on the basis of three parameters are recorded using network simulator (NS-3) as network simulator and synchronized with simulation on urban mobility (SUMO) as mobility simulator. A dataset is compiled using recorded results with NS-3 and SUMO. For selecting the efficient routing protocol, collection of dataset and selection of different features is done. machine learning (ML) models such as random forest, logistic regression, and k-nearest neighbor (k-NN) are implemented utilizing a set of relevant information regarding the relationship between sender and receiver. The effectiveness of ML models is assessed using a novel dataset and especially in comparison to that with others. The results shows that k-NN outperforms on the basis of evaluation parameters: F-score (75.5%), Accuracy (97.2%), Recall (79.9%) and Precision (75.3%) of classification learning techniques. The purpose of this research is prediction and analysis of ML Models for efficient routing protocol in VANET using different feature information that may be utilized to improve effectiveness of VANET and provided efficient routing protocol for safe, secure, reliable connection between vehicles. [ABSTRACT FROM AUTHOR]

Through the use of Underwater Smart Sensor Networks (USSNs), Marine Observatories (MOs) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of USSN devices' hardware and software when combined with the Internet. Hence, USSNs are regarded as complex distributed systems. As such, USSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed USSNs. Accordingly, during the USSN development and deployment phases, a few Underwater Environmental Constraints (UECs) should be taken into account. These constraints may include the salinity level and the operational depth of every physical component (sensor, server, etc.) that will be utilized throughout the duration of the USSN information systems' development and implementation. To this end, in this article we present how we integrated an Artificial Intelligence (AI) Database, an extended ArchiMO meta-model, and a design tool into our previously proposed Enterprise Architecture Framework. This addition proposes adding new Underwater Environmental Constraints (UECs) to the AI Database, which is accessed by USSN designers when they define models, with the goal of simplifying the USSN design activity. This serves as the basis for generating a new version of our ArchiMO design tool that includes the UECs. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to the handling and controling of the uncertainties and variances of the provided quality of service that may occur during the performance of the USSNs, as well as reducing the design activity's complexity and time. It provides a way to share the different viewpoints of the designers in the domain of USSNs. [ABSTRACT FROM AUTHOR]

Wireless Mesh Networks are gaining traction as a solution for delivering reliable connectivity without centralized infrastructure. They operate through wireless node interconnections, forming self-configuring networks ideal for scenarios where wired networks are impractical. Routing is crucial in Wireless Mesh Networks to ensure efficient communication among nodes. However, the suitability of routing algorithms for Wireless Mesh Network's topology requires further investigation. This paper proposes an investigation into the effectiveness of routing algorithms like AODV, DSDV, and OLSR across various Wireless Mesh Networks topologies using NS-3 simulation. It also aims to determine the optimal number of nodes and protocols to maximize throughput and minimize packet loss within a limited area. Through rigorous NS-3 simulations, the study demonstrates that AODV, DSDV, and OLSR exhibit differing effectiveness across random, mesh grid, and Fruchterman-Reingold topologies. These results emphasize the importance of considering topology-specific factors when selecting and optimizing routing protocols for Wireless Mesh Networks. In summary, Wireless Mesh Networks offer decentralized connectivity, but the effectiveness of routing algorithms in different topologies remains understudied. This investigation addresses this gap by evaluating routing algorithms across various topologies, shedding light on their suitability and performance in Wireless Mesh Networks. [ABSTRACT FROM AUTHOR]

Routing in vehicular ad hoc networks (VANETs) enables vehicles to communicate for safety and non-safety applications. However, there are limitations in wireless communication that can degrade VANET performance, so it is crucial to optimize the operation of routing protocols to address this. Various routing protocols employed the expected transmission count (ETX) in their operation as one way to achieve the required efficiency and robustness. ETX is used to estimate link quality for improved route selection. While some studies have evaluated the utilization of ETX in specific protocols, they lack a comprehensive analysis across protocols under varied network conditions. This research provides a comprehensive comparative evaluation of ETX-based routing protocols for VANETs using the nomadic community mobility model. It covers a foundational routing protocol, ad hoc on-demand distance vector (AODV), as well as newer variants that utilize ETX, lightweight ETX (LETX), and power-based light reverse ETX (PLR-ETX), which are referred to herein as AODV-ETX, AODV-LETX, and AODV-PLR, respectively. The protocols are thoroughly analyzed via ns-3 simulations under different traffic and mobility scenarios. Our evaluation model considers five performance parameters including throughput, routing overhead, end-to-end delay, packet loss, and underutilization ratio. The analysis provides insight into designing robust and adaptive ETX routing for VANET to better serve emerging intelligent transportation system applications through a better understanding of protocol performance under different network conditions. The key findings show that ETX-optimized routing can provide significant performance enhancements in terms of end-to-end delay, throughput, routing overhead, packet loss and underutilization ratio. The extensive simulations demonstrated that AODV-PLR outperforms its counterparts AODV-ETX and AODV-LETX and the foundational AODV routing protocol across the performance metrics.

The new generation mobile network 5G has become the main technology foundation in the architecture of the Internet of Things (IoT). In particular, millimeter wave communication technology in 5G is the core technology of the new generation network. Research on 5G networks faces many challenges in deploying real-life models to evaluate effectiveness. To resolve those issues, the article introduced the mmWave module integrated in the NS-3 network simulation toolkit to simulate and evaluate 5G network performance. The mmWave module is applied to simulate 5G network scenarios with the signal-to-noise ratio parameter SINR (Signal Interference + Noise Ration), thereby evaluating the wave quality from the base station to the terminal users to determine the most optimal location to build the base station.

Unmanned aerial vehicles (UAVs) have gained prominence across various sectors for their versatile applications. While their advantages are evident, addressing concerns associated with their deployment is essential to ensure reliability. This study presents an innovative approach for coordinating a group of UAVs in aerial survey missions. The decentralized strategy presented in this article allow UAVs to self-organize into linear formation, optimize their coverage paths, and adapt to agent failures, thereby ensuring efficient and adaptive mission execution. The strategy has been tested and validated on two different platforms: the inter-UAV communication performance is evaluated on NS-3 simulator to measure metrices such as packet delivery ratio, throughput, delay, and routing overhead within the UAV swarms, while mission efficiency and fault tolerance is analyzed on robot operating system framework, and visualized on Gazebo simulator with real-time parameters. Through experimental results, we show that, after proper tuning of control parameters, the approach succeeds in flock formation with high level of fault tolerance, offering higher efficiency in terms of mission time, transmission delay, packet delivery rate, and control overhead, when compared to the benchmark approaches.

Wireless Sensor Networks (WSNs) serve as the backbone for the Internet of Things (IoT) and smart cities, enabling the gathering of essential data and vital information. The widespread deployment of sensors created new scenarios that presented new domains for various applications. Due to their numerous advantages, WSN’s simulators are still gaining considerable attention as the primary method for testing and evaluating new protocols and approaches for WSN. The scientific community has developed various simulators, some tailored explicitly for WSNs and others for general use. In addition, an old but renovated direction has been enormously grown recently, representing the researcher’s attention to building its own simulator. However, many researchers struggle to select the most appropriate tool for performance analysis, which requires extensive research into available options. Choosing a suitable simulator to meet the necessary simulation criteria necessitates exhaustive research into the available options. The published studies on WSN’s simulators have limitations, such as the limited number of simulators under examination, ignoring the essential functions of the simulators, and inadequate performance criteria for precise comparison. To get beyond these restrictions in previous studies and offer a fresh study that compares the simulation tools comprehensively, an analysis of thirty-three different simulators was conducted based on a new taxonomy. Furthermore, this study examines the advantages and constraints of each simulator regarding many specific academic areas in WSNs. Moreover, the study presented a detailed comparison among the performance analysis tools according to many famous performance metrics.

The Multi-Point Relay (MPR) is one of the core technologies for Optimizing Link State Routing (OLSR) protocols, offering significant advantages in reducing network overhead, enhancing throughput, maintaining network scalability, and adaptability. However, due to the restriction that only MPR nodes can forward control messages in the network, the current evaluation criteria for selecting MPR nodes are relatively limited, making it challenging to flexibly choose MPR nodes based on current link states in dynamic networks. Therefore, the selection of MPR nodes is crucial in dynamic networks. To address issues such as unstable links, poor transmission accuracy, and lack of real-time performance caused by mobility in dynamic networks, we propose a comprehensive evaluation algorithm of MPR based on link-state awareness. This algorithm defines five state evaluation parameters from the perspectives of node mobility and load. Subsequently, we use the entropy weight method to determine weight coefficients and employing the method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for comprehensive evaluation to select MPR nodes. Finally, the Comprehensive Evaluation based on Link-state awareness of OLSR (CEL-OLSR) protocol is proposed, and simulated experiments are conducted using NS-3. The results indicate that, compared to PM-OLSR, ML-OLSR, LD-OLSR, and OLSR, CEL-OLSR significantly improves network performance in terms of packet delivery rate, average end-to-end delay, network throughput, and control overhead. [ABSTRACT FROM AUTHOR]

Recently, the use of traffic monitoring applications is very common. Many of these, for example, have algorithms that seek the fastest way for the driver to complete the journey. Vehicular networks can be used to collect information in real time, such as traffic flow, accidents and congestion, helping to decongest the already chaotic traffic in cities. Thus, the use of vehicular ad-hoc networks (VANETs) in this case adds greater reliability, robustness and automation to traffic control systems. Practical experiments using VANETs are scarce; therefore, it is of great importance to validate simulations and ensure that they are explored and studied by researchers in this area. According to our surveys, works that address real measurements are fewer in number compared to software simulations. One of these factors, for example, is the development of drivers and software for the equipment and the high complexity of making such experiments available. Another point that also justifies the low number of actual measurements is the high cost of the equipment that supports the IEEE 802.11p standard, as it is still not widespread in the market. The main objective of this work is to carry out a study on vehicle ad-hoc network simulators and identify the advantages and disadvantages of each simulator covered. Particularly, a VANET network capable of operating in the IEEE 802.11p standard is simulated, evaluating performance in certain traffic characteristics. [ABSTRACT FROM AUTHOR]

One promising paradigm for content-centric communication is Named Data Networking (NDN), which revolutionizes data delivery and retrieval. A crucial component of NDN, producer mobility, presents new difficulties and opportunities for network optimization. This article reviews simulation strategies designed to improve NDN producer mobility. Producer mobility strategies have developed due to NDN data access needs, and these methods optimize data retrieval in dynamic networks. However, assessing their performance in different situations is difficult. Moreover, simulation approaches offer a cost-effective and controlled setting for experimentation, making them useful for testing these technologies. This review analyzes cutting-edge simulation methodologies for NDN producer mobility evaluation. These methodologies fall into three categories: simulation frameworks, mobility models, and performance metrics. Popular simulation platforms, including ns-3, OMNeT++, and ndnSIM, and mobility models that simulate producer movement are discussed. We also examine producer mobility performance indicators, such as handover data latency, signaling cost, and total packet loss. In conclusion, this comprehensive evaluation will help researchers, network engineers, and practitioners understand NDN producer mobility modeling approaches. By knowing these methodologies' strengths and weaknesses, network stakeholders may make informed NDN solution development and deployment decisions, improving content-centric communication in dynamic network environments. [ABSTRACT FROM AUTHOR]

The integration of communication infrastructures into traditional power systems, transforming them into cyber-physical power systems (CPPS), accentuates the significance of communication in influencing system performance and sustainability. This paper presents a versatile, innovative cyber-physical co-simulation framework that integrates the physical power system and communication networks, uniting OPAL-RT, a network simulator (ns3), and Docker containers into a sophisticated platform, facilitating intensive studies into CPPS dynamics. The proposed experimental study provides an innovative way to assess the frequency control response of a cyber-physical inverter-based microgrid (MG), addressing the MG sustainability challenges. We consider diverse real-world scenarios, focusing on communication delays and distributed denial of service (DDoS) attacks within the communication channels. We propose a precise ns3-based communication model that bridges the MG's primary and secondary control layers, an aspect often overlooked in previous studies; this is a noteworthy contribution to elucidating the adverse impacts of communication latency on MG frequency performance. The experimental results demonstrate the effectiveness of the centralized secondary controller in eliminating the frequency deviations. Furthermore, the findings offer insights into stable and unstable regions, revealing how the communication delay value affects the frequency stability under different operating conditions. In addition, the developed real-time DDoS attacks model within the proposed communication surface unveils crucial insights into the MG's resilience to cyber threats. This work's revelations offer a foundational awareness of MG vulnerabilities, paving the way for designing robust and resilient communication networks and control strategies within the cyber-physical inverter-based microgrids. [ABSTRACT FROM AUTHOR]

The IoT encompasses objects, sensors, and everyday items not typically considered computers. IoT devices are subject to severe energy, memory, and computation power constraints. Employing NDN for the IoT is a recent approach to accommodate these issues. To gain a deeper insight into how different network parameters affect energy consumption, analyzing a range of parameters using hyperparameter optimization seems reasonable. The experiments from this work's ndnSIM-based hyperparameter setup indicate that the data packet size has the most significant impact on energy consumption, followed by the caching scheme, caching strategy, and finally, the forwarding strategy. The energy footprint of these parameters is orders of magnitude apart. Surprisingly, the packet request sequence influences the caching parameters' energy footprint more than the graph size and topology. Regarding energy consumption, the results indicate that data compression may be more relevant than expected, and caching may be more significant than the forwarding strategy. The framework for ndnSIM developed in this work can be used to simulate NDN networks more efficiently. Furthermore, the work presents a valuable basis for further research on the effect of specific parameter combinations not examined before. [ABSTRACT FROM AUTHOR]

The recent emerging trend to promote the harmonious interactions between human and smart objects in Internet of Things (IoT) applications has led to the rising demand for the comprehensive exploration of associated IoT design spaces, considering system-, network-, and human-level perspectives. The traditional design approach of networked smart objects tends to ignore the effects caused by human interactions so that the existing approach has the limited capability in joint system/network/human multi-level exploration. In this paper, we propose a high-level system modeling and multi-level simulation approach for microsystem models to interoperate with high-level models in the human-level perspective and to provide comprehensive co-exploration. The high-level system modeling enables one to abstract the detailed operations of hardware platforms using power and timing data obtained by the proposed high-level state-based profiling method and using the event-driven modeling concept. For the event-driven system modeling, we utilize the discrete-event system specification (DEVS) to support scalable model-driven prototyping. To represent the coupled relationship of network-level system activity and human-level interactions between node systems and humans, we employ a general-purpose network simulator to model the operation and communication of network modules in smart objects and developed agent-based human behavioral models. For the co-simulation of multi-level models, we designed a distributed simulation platform to enable the interoperation between the DEVS simulator and the network simulator using a runtime infrastructure. The proposed modeling and simulation approach is applied for the multi-level evaluation of a smart museum application to estimate the effect of energy-efficiency policies. [ABSTRACT FROM AUTHOR]

The first Quantum Key Distribution (QKD) networks are currently being deployed, but the implementation cost is still prohibitive for most researchers. As such, there is a need for realistic QKD network simulators. The QKDNetSim module for the network simulator NS-3 focuses on the representation of packets and the management of key material in a QKD network at the application layer. Although QKDNetSim’s representation of a QKD network is insightful, some its components lack the depth that would allow the simulator to faithfully represent the behaviour of a real quantum network. In this work, we analyse QKDNetSim’s architecture to identify its limitations, and we present an enhanced version of QKDNetSim in which some of its components have been modified to provide a more realistic simulation environment.

With the deployment of numerous innovative smart grid technologies in modern power systems, more real-time communication and control are required due to the complexity and proliferation of grid-connected systems, making a power system a typical cyber-physical system (CPS). However, these systems are also exposed to new cyber vulnerabilities. Therefore, understanding the intricate interplay between the cyber and physical domains and the potential effects on the power system of successful attacks is essential. For cybersecurity experimentation and impact analysis, developing a comprehensive testbed is needed. This paper presents a state-of-the-art Hybrid Physical Co-simulation SG testbed at FIU developed for in-depth studies on the impact of communication system latency and failures, physical events, and cyber-attacks on the grid. The Hybrid SGTB is designed to take full advantage of the benefits of both co-simulation-based and physical-based testbeds. Based on this testbed, various attack strategies are tested, including man-in-the-middle (MitM), denial-of-service (DoS), data manipulation (DM), and setting tampering (change) on various power system topologies to analyze their impacts on grid stability, power flow, and protection reliability. Our research, which is based on extensive testing on several testbeds, shows that using hybrid testbeds is justified as both practical and effective. [ABSTRACT FROM AUTHOR]

A common medium access control (MAC) protocol used in Wi-Fi networks is the distributed coordination function (DCF). In the past few decades, a number of network simulators have been developed to validate their analytical models for DCF and other MAC protocols, among which OMNET has gained popularity. NS3 and OMNET provide fundamental modeling framework for the IEEE 802.11 MAC and PHY layers. In this paper, we conducted a comparative study of a unified IEEE 802.11 DCF analytical model with NS3 and OMNET for performance evaluation. Various access modes and different topologies were examined for comparing the theoretical study with the simulators. This study provided a basis that the results obtained from NS3 and OMNET Wi-Fi modules are also credible just like in the theory. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are becoming more common in wireless communication networks. Using UAVs can lead to network problems. An issue arises when the UAVs function in a network-access-limited environment with nodes causing interference. This issue could potentially hinder UAV network connectivity. This paper introduces an intelligent packet priority module (IPPM) to minimize network latency. This study analyzed Network Simulator–3 (NS-3) network modules utilizing Manhattan long short-term memory (MaLSTM) for packet classification of critical UAV, ground control station (GCS), or interfering nodes. To minimize network latency and packet delivery ratio (PDR) issues caused by interfering nodes, packets from prioritized nodes are transmitted first. Simulation results and evaluation show that our proposed intelligent packet priority module (IPPM) method outperformed previous approaches. The proposed IPPM based on MaLSTM implementation for the priority packet module led to a lower network delay and a higher packet delivery ratio. The performance of the IPPM averaged 62.2 ms network delay and 0.97 packet delivery ratio (PDR). The MaLSTM peaked at 97.5% accuracy. Upon further evaluation, the stability of LSTM Siamese models was observed to be consistent across diverse similarity functions, including cosine and Euclidean distances.

The proliferation of technology has led to numerous advancements in various fields, including the field of simulation. Simulators, in particular, have proven to be a valuable tool for researchers and students as they eliminate the need for physical hardware, reduce costs, and increase accessibility for conducting experiments. One of the most significant innovations in this realm is the use of simulators, which are specially designed software programs that mimic real-world scenarios. However, with hundreds of simulators available for various fields, the selection of the appropriate one can be a daunting task. This work presents a systematic literature review on wireless sensor network (WSN) simulators and their selection methodology. A total of 31 literature works since 2016 were reviewed, with the majority of the works conducted in the past 4 years. The study found 52 unique simulators studied about 182 times with repetitive sets in different literatures. Most of the works presented basic and general information about the simulators which does not assist readers in selecting the appropriate and best suitable simulator for their work. Additionally, about 55% of the works did not define any selection criteria or present comparisons among the studied simulators. The majority of literature work either selected simulators based on their frequency of appearance in their studied literature subset or based on their popularity. The results of this study can aid researchers in selecting the appropriate WSN simulator for their experimental work.

The IEEE 802.11 standard provides multi-rate support for different versions. As there is no specification on the dynamic strategy to adjust the rate, different rate adaptation algorithms are applied according to different manufacturers. Therefore, it is often hard to interpret the performance discrepancy of various devices. Moreover, the ever-changing channels always challenge the rate adaptation, especially in the scenario with scarce spectrum and low SNR. As a result, it is important to sense the radio environment cognitively and reduce the unnecessary oscillation of the transmission rate. In this paper, we propose an environment-aware robust (EAR) algorithm. This algorithm employs an occasional small packet, designs a rate scheme adaptive to the environment, and enhances the robustness. We verify the throughput of EAR using network simulator NS-3 in terms of station number, motion speed and node distance. We also compare the proposed algorithm with three benchmark methods: AARF, RBAR and CHARM. Simulation results demonstrate that EAR outperforms other algorithms in several wireless environments, greatly improving the system robustness and throughput. [ABSTRACT FROM AUTHOR]

In urban Vehicular Ad Hoc Network (VANET) environments, buildings play a crucial role as they can act as obstacles that attenuate the transmission signal between vehicles. Such obstacles lead to multipath effects, which could substantially impact data transmission due to fading. Therefore, quantifying the impact of buildings on transmission quality is a key parameter of the propagation model, especially in critical scenarios involving emergency vehicles where reliable communication is of utmost importance. In this research, we propose a supervised learning approach based on Artificial Neural Networks (ANNs) to develop a predictive model capable of estimating the level of signal degradation, represented by the Bit Error Rate (BER), based on the obstacles perceived by moving emergency vehicles. By establishing a relationship between the level of signal degradation and the encountered obstacles, our proposed mechanism enables efficient routing decisions being made prior to the transmission process. Consequently, data packets are routed through paths that exhibit the lowest BER. To collect the training data, we employed Network Simulator 3 (NS-3) in conjunction with the Simulation of Urban MObility (SUMO) simulator, leveraging real-world data sourced from the OpenStreetMap (OSM) geographic database. OSM enabled us to gather geospatial data related to the Two-Dimensional (2D) geometric structure of buildings, which served as input for our Artificial Neural Network (ANN). To determine the most suitable algorithm for our ANN, we assessed the accuracy of ten learning algorithms in MATLAB, utilizing five key metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Correlation Coefficient (R), and Maximum Prediction Error (MaxPE). For each algorithm, we conducted fifteen iterations based on ten hidden neurons and gauged its accuracy against the aforementioned metrics. Our analysis highlighted that the ANN underpinned by the Conjugate Gradient With Powell/Beale Restarts (CGB) learning algorithm exhibited superior performance in terms of MSE, RMSE, MAE, R, and MaxPE compared to other algorithms such as Levenberg–Marquardt (LM), Bayesian Regularization (BR), BFGS Quasi-Newton (BFG), Resilient Backpropagation (RP), Scaled Conjugate Gradient (SCG), Fletcher–Powell Conjugate Gradient (CGF), Polak–Ribiére Conjugate Gradient (CGP), One-Step Secant (OSS), and Variable Learning Rate Backpropagation (GDX). The BER prediction by our ANN incorporates the TWO-RAY Ground (TRG) propagation model, an adjustable parameter within NS-3. When subjected to 300 new samples, the trained ANN's simulation outcomes illustrated its capability to learn, generalize, and successfully predict the BER for a new data instance. Overall, our research contributes to enhancing the performance and reliability of communication in urban VANET environments, especially in critical scenarios involving emergency vehicles, by leveraging supervised learning and artificial neural networks to predict signal degradation levels and optimize routing decisions accordingly. [ABSTRACT FROM AUTHOR]

Wireless mesh networks (WMNs) offer a pragmatic solution with a cost-effective ratio when provisioning ubiquitous broadband internet access and diverse telecommunication systems. The conceptual underpinning of mesh networks finds application not only in IEEE networks, but also in 3GPP networks like LTE and the low-power wide area network (LPWAN) tailored for the burgeoning Internet of Things (IoT) landscape. IEEE 802.11s is well known for its facto standard for WMN, which defines the hybrid wireless mesh protocol (HWMP) as a layer-2 routing protocol and airtime link (ALM) as a metric. In this intricate landscape, artificial intelligence (AI) plays a prominent role in the industry, particularly within the technology and telecommunication realms. This study presents a novel methodology for the computation of routing metrics, specifically the ALM. This methodology implements the network simulator ns-3 and the RStudio as a statistical computing environment for data analysis. The former has enabled for the creation of scripts that elicit a variety of scenarios for WMN where information is gathered and stored in databases. The latter (RStudio) takes this information, and at this point, two linear predictions are supported. The first uses linear models (lm) and the second employs general linear models (glm). To conclude this process, statistical tests are applied to the original model, as well as to the new suggested ones. This work substantially contributes in two ways: first, through the methodological tool for the metric calculation of the HWMP protocol that belongs to the IEEE 802.11s standard, using lm and glm for the selection and validation of the model regressors. At this stage the ANOVA and STEPWIZE tools of RStudio are used. The second contribution is a linear predictor that improves the WMN's performance as a priori mechanism before the use of the ns-3 simulator. The ANCOVA tool of RStudio is employed in the latter. [ABSTRACT FROM AUTHOR]

Herein, we propose the use of the logarithmic values of data transmission rates for multi-armed bandit (MAB) algorithms that adjust the modulation and coding scheme (MCS) levels of data packets in carrier-sensing multiple access/collision avoidance (CSMA/CA) wireless networks. We argue that the utilities of the data transmission rates of the MCS levels may not be proportional to their nominal values and suggest using their logarithmic values instead of directly using their data transmission rates when MAB algorithms compute the expected throughputs of the MCS levels. To demonstrate the effectiveness of the proposal, we introduce two MAB algorithms that adopt the logarithmic rates of the transmission rates. The proposed MAB algorithms also support frame aggregations available in wireless network standards that aim for a high throughput. In addition, the proposed MAB algorithms use a sliding window over time to adapt to rapidly changing wireless channel environments. To evaluate the performance of the proposed MAB algorithms, we used the event-driven network simulator, ns-3. We evaluated their performance using various scenarios of stationary and non-stationary wireless network environments including multiple spatial streams and frame aggregations. The experiment results show that the proposed MAB algorithms outperform the MAB algorithms that do not adopt the logarithmic transmission rates in both the stationary and non-stationary scenarios. [ABSTRACT FROM AUTHOR]

According to the rising number of users and the application development that needs fast transfer rates. The main objective behind the development of IEEE 802.11ac was to deliver WLANs with exceptionally very high throughput rates. Significant improvements were incorporated into the PHY and MAC layers to achieve this, leading to enhanced data rates and overall network performance. These enhancements have enabled the standard 802.11ac to support channel bonding schemes. This paper looks at how channel bonding affects the performance of system, especially in terms of delay and amount of throughput. The research paper looks at four different scenarios with different numbers of channel BW 40,80 & 160MHz, and various spatial streams (SS) from 1 to 8. The network simulator (NS-3) version 3.37 is used to simulate these scenarios. The results of the simulation indicate that when Dynamic Channel Bonding (DCB) is applied, the highest throughput and least amount of delay values are acquired. Specifically, for MIMO (8×8) SS and with respect to the Static Channel Bonding (SCB), the best improvement of throughput and delay are obtained with DCB in the highest (48 node number) scenario. The throughput development values are (90.21%, 87.3%, and 42.91%) and the delay improvement values are (47.43%, 46.61%, and 30.03%) for channel BWs 40,80, &160 MHz, respectively. [ABSTRACT FROM AUTHOR]

The Tactile Internet (TI) can be regarded as the next evolution in the world of communication. With its envisioned purpose and potential in shaping up the economy, industry and society, this paradigm aims to bring a new dimension to life by enabling humans to interact with machines remotely and in real-time with haptic and kinesthetic feedback. However, to translate this into reality, Tactile Internet will need to meet the stringent requirements of extremely low latency in conjunction with ultra-high reliability, availability, and security. This poses a challenge on the available communication systems to achieve a round-trip delay within 1 to 10 milliseconds time bound that enables the timely delivery of critical tactile and haptic sensations. This paper aims to evaluate the Real-Time Transport Protocol (RTP) through an emulation framework. It integrates containerization using Linux-based Docker Containers with NS-3 Network Simulator to conceptualize a haptic teleoperation system. The framework is then used to test the protocol’s feasibility for delivering texture haptic data between master and slave domains in accordance with the end-to-end delay requirements specified by IEEE 1918.1 standards. The results have shown that the timely provision of haptic data is achievable by obtaining an average roundtrip delay of 17.8493 ms from the emulation experiment. As such, the results satisfy the expected IEEE 1918.1 standards constraints for medium-dynamic environment use cases. [ABSTRACT FROM AUTHOR]

The proliferation of technology has led to numerous advancements in various fields, including the field of simulation. Simulators, in particular, have proven to be a valuable tool for researchers and students as they eliminate the need for physical hardware, reduce costs, and increase accessibility for conducting experiments. One of the most significant innovations in this realm is the use of simulators, which are specially designed software programs that mimic realworld scenarios. However, with hundreds of simulators available for various fields, the selection of the appropriate one can be a daunting task. This work presents a systematic literature review on wireless sensor network (WSN) simulators and their selection methodology. A total of 31 literature works since 2016 were reviewed, with the majority of the works conducted in the past 4 years. The study found 52 unique simulators studied about 182 times with repetitive sets in different literatures. Most of the works presented basic and general information about the simulators which does not assist readers in selecting the appropriate and best suitable simulator for their work. Additionally, about 55% of the works did not define any selection criteria or present comparisons among the studied simulators. The majority of literature work either selected simulators based on their frequency of appearance in their studied literature subset or based on their popularity. The results of this study can aid researchers in selecting the appropriate WSN simulator for their experimental work. [ABSTRACT FROM AUTHOR]

In the paper, the BTS (Background Traffic Simulator) tool is proposed to capture network traffic and then reproduce it in a simulations using the ns-3 simulator extension module. This new method of generating background traffic allows for repetitive testing of simulation scenarios under real network conditions. The authors described the differences between the previously available methods and the proposed solution. The operation of all the most important elements of the proposed tool has been described. The influence of the generated background traffic on the simulation scenario was presented as well as the results of the operation.

Emerging applications in the context of smart cities pursue a decentralized design that often involves numerous networked components. To validate such a design, the scientific community has resorted to software based simulators to find a way around the complexity of building large scale physical network test-beds. Network Simulator-3 (ns-3) is one of the most popular platforms for this purpose where communication-related performance metrics, e.g., latency and throughput, can be evaluated. Yet, concerns exist about the viability of such a simulated approach when assessing dependability metrics, e.g., trust and resilience to cyberattacks, since the misbehavior is mainly defined by the evaluator. Incorporating physical nodes within the simulated network would be advantageous in that regard. Advances have been made to connect network simulators, e.g., ns-3, to virtual machines to emulate communication with real devices. However, all efforts in the literature so far have been limited to a single physical host. This paper presents a framework where many external physical devices can act as a part of the ns-3 simulator and interact seamlessly with the nodes within the simulated network via Docker containers. Hence, our framework enables scalable and cost effective experimentation to validate dependability metrics like fault-tolerance and attack resilience. We demonstrate the utility of the proposed framework in evaluating performance under a set of attack scenarios.

The extensive availability of spectrum resources and the remarkably high data transmission rate of millimeter-wave (mmWave) technology have propelled its significance as a vital component in the advancement of mobile communications, including fifth generation (5G) networks. However, the intermittent nature of mmWave links and their interaction with transport layer protocols pose several challenges, which bring inadequate performance, due to fluctuations in high-frequency channels. Consequently, although these features of mmWave might be advantageous, they can actually hinder the performance. Although these issues have been studied in the literature with TCP, there are few works that have studied how QUIC behaves over this kind of channels. This paper aims to compare the performance of TCP and QUIC over mmWave channels, studying the impact at the application level. We conduct extensive performance evaluations, based on traces that are obtained by means of a detailed simulation of different mmWave scenarios, using the ns-3 simulator. We analyze key performance indicators, such as delay, throughput, and bottleneck buffer. The results evince that QUIC outperforms TCP in highly fluctuating mmWave channels, showing better performance for both throughput and delay.

Mobile data network is featured by long delay and moving terminals, which affect the user service quality performance of transmission control protocol’s (TCP) congestion control algorithm Vegas. To solve this problem, this paper first proposed to optimise the congestion control algorithm using a genetic algorithm, build ns-3 network topology structure and adopt mobile data network trace for optimisation and simulation; and the Vegas optimisation problem as a multivariate dual-objective problem was solved with Non-dominated Sorting Genetic Algorithm II (NSGA-II). The ns-3 simulation results indicate that Vegas with optimised parameters have high throughput and short delay, which significantly promotes TCP Vegas’s QoS under a mobile scene.

Summary: With their high flexibility and versatility, unmanned aerial vehicles (UAVs) have maneuvered their way into many applications. Thanks to their ability to plan and coordinate, multiple UAVs complete tasks more effectively, which boosts their popularity in battlefield surveys, formation performances, and targeted searches. However, the risk of security threats also rises alongside their popularity. The UAV ad hoc network (UANET) has endeavored to contend with such risks through the optimized link state routing (OLSR) protocol. To test the security and strength of this effort, we present a sky black hole attack (SBHA) algorithm for OLSR, which is undetectable, based on the UANET's multi‐hop routing and the OLSR's known topology. This algorithm obtains the network's maximum profits by approaching and then replacing the calculated topology center and traffic center in UANET. Because of the ever‐changing topology, SBHA aims at UANET's single central node that cannot be detected in advance. This attack is difficult to detect by UANET and therefore difficult to defend. The simulation results show that SBHA can cause greater damage to UANET compared to a traditional black hole attack, and ordinary defense algorithms cannot reduce the negative impact of SBHA on UANET. In addition, SBHA also gains UANET control, and leads to drastic changes in UAVs' movement trajectory, which has more intuitive effects. [ABSTRACT FROM AUTHOR]

Flying Ad-Hoc Networks (FANETs) consist of multi-Unmanned Aerial Vehicle (UAV) nodes with ad-hoc networking capabilities. FANETs are increasingly gaining popularity in real-world applications where communication infrastructure is lacking. In this work, an application of FANET in monitoring the geographical spread of a certain type of disaster event has been showcased. For this task, suitable network topology construction algorithms have been developed. Additionally, various protocols of the network protocol stack have been implemented for this FANET. A bespoke co-simulator platform has been developed to simulate this network. The co-simulator platform makes use of a network simulator (NS-3), and robot simulator (Gazebo) interfaced with each other using an interlinking framework of Robot Operating System (ROS). This platform has been used to simulate network topology construction algorithms as well as networking protocols. The proposed FANET has been analyzed for the deployment of an optimum number of drones in the varying profile of disaster event. Also, the temporal analysis has been conducted to showcase the time-effectiveness of the FANET deployment in such cases. For example, if the disaster event is located at 250 m from the Base Station (BS), with a spread of around 70 m radius, the total number of drones required is 16, and the deployment time is merely 4.25 mins. Along with this, a link analysis of the network also has been conducted for calculating throughput. It indicates that the FANET can be utilized for multimedia streaming as there is ample scope for throughput enhancement. [ABSTRACT FROM AUTHOR]