Varying Number Of Nodes Research Articles

Channel Bonding Effects of the IEEE802.11n Standard on the WLANs Performance

The evolution of wireless communication technologies has led to the widespread adoption of Wireless Local Area Networks (WLANs). IEEE 802.11n provides many enhancements in physical and MAC layers such as (channel bonding(CB), Multiple Input/Output (MIMO), frame aggregation and block acknowledgment) to achieve higher throughput and improved reliability. As a result, CB is a key technique for enhancing the performance of wireless network. It is frequently used in various fields, such as workplace networks and live streaming. This research paper focuses on analyzing the effect of channel bonding on the performance of the IEEE802.11n WLANs, especially in two terms (throughput and delay). By using the OPNET (Riverbed) Modular version 17.5, five various number of nodes (5, 10, 15, 18 and 30 nodes) uniform topologies are modeled and simulated to investigate the WLANs performance for various MIMO up to 4 SS. Simulation outcomes indicated that applying of CB enhanced both delay and velocity performance. Specifically, in the scenarios (30 nodes), for MIMO (4×4) spatial streams, the average throughput value for channel bonding is (157.28 Mbps) compared to (87.41 Mbps) for no-channel bonding, and the average delay value for channel bonding is (0.0476 Sec) compared to (0.06762 Sec) for no-channel bonding. The enhancement values in the performance of WLANs are 42% and 79.9% for latency and throughput (velocity), respectively.

Heterogeneous Graph Neural Network for Power Allocation in Multicarrier-Division Duplex Cell-Free Massive MIMO Systems

In order to maximize the spectral efficiency (SE) in multicarrier-division duplex (MDD) enabled cell-free massive MIMO (CF-mMIMO), a heterogeneous graph neural network (HGNN), referred to as CF-HGNN, is specifically introduced to optimize the power allocation (PA). To efficiently manage the interference invoked, a meta-path based mechanism is applied in CF-HGNN to enable individual access point (AP) and mobile station (MS) nodes to aggregate information from the interfering and communication paths with different priorities during message passing. Moreover, the proposed CF-HGNN employs the adaptive node embedding layer and adaptive output layer to make it scalable to the various numbers of APs, MSs and subcarriers. For comparison, a quadratic transform and successive convex approximation (QT-SCA) algorithm is proposed to solve the PA problem in classic way. Numerical results show that CF-HGNN is capable of achieving 99% of the SE achievable by QT-SCA but using only 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> times of its operation time, and it can outperform the conventional learning-based and greedy unfair methods in terms of SE performance. Furthermore, CF-HGNN exhibits good scalability to the CF networks with various numbers of nodes and subcarriers, and also to the large-scale CF networks when assisted by user-centric clustering.

Biomimetic Design of a New Semi-Rigid Spatial Mesh Antenna Reflector.

The reflective surface accuracy (RSA) of traditional space mesh antennas typically ranges from 0.2 to 6 mmRMS. To improve the RSA, an active control scheme can be employed, although it presents challenges in determining the installation position of the actuator. In this study, we propose a novel design for a semi-rigid cable mesh that combines rigid members and a flexible woven mesh, drawing inspiration from both rigid ribbed antennas and biomimicry. Initially, we investigate the planar mesh topology of spider webs and determine the bionic cable surface's mesh topology based on the existing hexagonal meshing method, with RSA serving as the evaluation criterion. Subsequently, through motion simulations and careful observation, we establish the offset angle as the key design parameter for the bionic mesh and complete the design of the bionic cable mesh accordingly. Finally, by analyzing the impact of the node quantity on RSA, we determine a layout scheme for the flexible woven mesh with a variable number of nodes, ultimately settling for 26 nodes. Our results demonstrate that the inclusion of numerous rigid components on the bionic cable mesh surface offers viable installation positions for the actuator of the space mesh antenna. The reflector accuracy achieved is 0.196 mmRMS, slightly surpassing the lower limit of reflector accuracy observed in most traditional space-space mesh antennas. This design presents a fresh research perspective on combining active control schemes with reflective surfaces, offering the potential to enhance the RSA of traditional rigid rib antennas to a certain extent.

SERIAL AND DIFFERENT PARALLEL IMPLEMENTATIONS OF LATTICE BOLTZMANN METHOD IN PYTHON: A COMPARATIVE ANALYSIS

The lattice Boltzmann method (LBM) is known for its capability to model complex fluid systems. Python is becoming one of the most valuable tools for scientific programming and prototyping of commercial software. In parallel, there is nearly no information on LBM simulation libraries in Python. The current study addresses the issue of Pythonbased LBM simulations. We have developed and tested the serial and two concurrent approaches (multiprocessing and multithreading) through 7 different versions of the LBM solvers for a range of the various numbers of nodes. Parallelization is also defined for three individual levels of domain decomposition, and RunTime profile data for entire solvers have been discussed comparatively in detail. Apart from the implementation strategy, a preliminary comparison is made between two data storage styles to investigate the effect of data shape on RunTime. In contrast with the literature, serial processing provides the fastest results for task execution of LBM simulation in Python due to the strengths of Python in data manipulation. One version of multithreaded solver also provides the same results with serial implementation; however, in conclusion, and due to the ease of serial programming, serial implementation of LBM in Python is defined as the most practical candidate.

Performance Analysis of MAC Layer Protocols for WSN with Considering the Effects of Hidden Node Problem

In this paper, the effects of the hidden node problem in Wireless sensor networks are studied on three different MAC protocols using various field distances and various numbers of nodes. This study provides the best number of nodes to be disseminated in a specific field distance depending on the needed performance metrics. Six performance metrics are used in this study, which are Goodput, Throughput, Packet delivery ratio (PDR), Residual Energy, Average Delay, and the first and last node dead in the network. IEEE 802.11, IEEE 802.15.4, and time division multiple access (TDMA) protocols are used. Results show that TDMA gives the best energy conservation and high delay time with high PDR, while IEEE 802.11 provides the best throughput and goodput results and low delay time.

Investigation of Performance and Configuration of a Selected IoT System—Middleware Deployment Benchmarking and Recommendations

Nowadays Internet of Things is gaining more and more focus all over the world. As a concept it gives many opportunities for applications for society and it is expected that the number of software services deployed in this area will still grow fast. Especially important in this context are properties connected with deployment such as portability, scalability and balance between software requirements and hardware capabilities. In this article, we present results of practical tests with multiple clients representing sensors sending notifications to an IoT middleware—DeviceHive. Firstly, we investigate performance using two deployment configurations—containerized and bare-metal showing small overhead of the former under different loads by various numbers of IoT clients. We present scaling of the middleware on the server side using various numbers of cores as well as HyperThreading for all aforementioned configurations. Furthermore, we also investigated how containarization affects performance when the system is scaled with various numbers of nodes each using a predefined number of cores, considering memory usage of various configurations. The latter could be found useful when assigning cores to Docker nodes in cloud environments.

Exploring the Dimensionality of Ground-Motion Data by Applying Autoencoder Techniques

ABSTRACTIn this article, we address the question of how observed ground-motion data can most effectively be modeled for engineering seismological purposes. Toward this goal, we use a data-driven method, based on a deep-learning autoencoder with a variable number of nodes in the bottleneck layer, to determine how many parameters are needed to reconstruct synthetic and observed ground-motion data in terms of their median values and scatter. The reconstruction error as a function of the number of nodes in the bottleneck is used as an indicator of the underlying dimensionality of ground-motion data, that is, the minimum number of predictor variables needed in a ground-motion model. Two synthetic and one observed datasets are studied to prove the performance of the proposed method. We find that mapping ground-motion data to a 2D manifold primarily captures magnitude and distance information and is suited for an approximate data reconstruction. The data reconstruction improves with an increasing number of bottleneck nodes of up to three and four, but it saturates if more nodes are added to the bottleneck.

Enhanced Routing Algorithm Based on Reinforcement Machine Learning-A Case of VoIP Service.

The routing algorithm is one of the main factors that directly impact on network performance. However, conventional routing algorithms do not consider the network data history, for instances, overloaded paths or equipment faults. It is expected that routing algorithms based on machine learning present advantages using that network data. Nevertheless, in a routing algorithm based on reinforcement learning (RL) technique, additional control message headers could be required. In this context, this research presents an enhanced routing protocol based on RL, named e-RLRP, in which the overhead is reduced. Specifically, a dynamic adjustment in the Hello message interval is implemented to compensate the overhead generated by the use of RL. Different network scenarios with variable number of nodes, routes, traffic flows and degree of mobility are implemented, in which network parameters, such as packet loss, delay, throughput and overhead are obtained. Additionally, a Voice-over-IP (VoIP) communication scenario is implemented, in which the E-model algorithm is used to predict the communication quality. For performance comparison, the OLSR, BATMAN and RLRP protocols are used. Experimental results show that the e-RLRP reduces network overhead compared to RLRP, and overcomes in most cases all of these protocols, considering both network parameters and VoIP quality.

РАЗРАБОТКА И ХАРАКТЕРИСТИКИ БЛОКЧЕЙН-СИСТЕМЫ НА ЯЗЫКЕ JAVASCRIPT

The paper describes the main features of blockchain technology, provides the main areas of use of this technology. Today, blockchain has evolved into a reliable and secure way to store and record transactions across a wide range of application domains. However, the impact of existing solutions on the current network infrastructure needs to be considered. The authors propose to create a system for generating and storing blockchain traffic based on the JavaScript programming language. This solution cannot be applied to cryptocurrencies, but it allows you to evaluate the work of a distributed database based on blockchain technology. The aim of the work is to analyze the delays in the generation and distribution of traffic between various numbers of nodes and the dependence of the speed of distribution and block generation on the performance of computers. The paper also considered the algorithm for joining a new node to the cluster and sending a new block to the blockchain, as well as the scheme of a node in a blockchain cluster, and presented the results of an experiment with a quantitative assessment of network performance characteristics.

Adapting PBFT for Use With Blockchain-Enabled IoT Systems

This work proposes Practical Byzantine Fault Tolerance (PBFT) ordering service needed for block formation in permissioned blockchain environments. Contrary to current PBFT implementations that only provide a single point of entry to the ordering service, we allow each ordering node to act as an entry point that proposes and conducts the consensus process of including new record in the distributed ledger. To ensure atomicity of record insertion in distributed ledger, we have developed a bandwidth reservation protocol that uses a modification of CSMA/CA protocol to regulate access to the broadcast medium formed by the P2P network of TCP connections between orderers. We have modeled record insertion service time in a cluster where ordering nodes have random position within Cartesian coordinate system. We have also modeled total request access time to the ledger which includes waiting time in the orderer's queue and record insertion time. These models are used to evaluate system performance under variable request rate ordering service, variable number of nodes and variable physical cluster dimensions. Our results show the interaction between decreased request waiting time in orderer's queue and increased contention among orderers when the number of orderers increases for the given total request arrival rate. This interaction is also investigated for two different physical cluster sizes which affect record insertion time. The interplay of request rate, number of orderers and physical cluster size determines system capacity expressed in total request rate. Our model can be used to make the trade-off between the required system capacity, number of orderers, and physical cluster dimensions under constraints on Byzantine fault rate.

Experimental comparison and evaluation of various OpenFlow software defined networking controllers

ABSTRACT In recent years, SDN has gained a lot of popularity. There is a basic principle behind the growth of SDN which states the separation of the control plane from the data plane. In the data plane, all the network devices constitute whereas in the control plane the core element is situated known as SDN controller. The controller is the integral element of SDN based network. It manages the entire network and maintains the overall functionality. In the last years, there are many SDN controllers came into existence. This paper aims to provide the experimental comparison among the seven most used SDN controllers both in research and industry. The comparison and experimentation analysis is carried out in an emulator tool known as Mininet with four different network topologies (single, linear, tree, custom) and the varied number of nodes (10, 50, 100, 500, 1000). The parameters for comparison are Round Trip Time (minimum, maximum, average) and standard deviation. This paper will prove to be beneficial for the researchers and industry people who are making use of these SDN controllers, it will help them to choose a particular controller and analyze their performance against the selected network topologies and number of hosts.

Free vibration of FGM annular sectorial plates with arbitrary boundary supports and large sector angles

An original work is presented for the free vibration analysis of thin functionally graded material (FGM) annular sectorial plates with arbitrary boundary supports using the weak form quadrature element method (QEM). Novel C 1 quadrature annular sectorial plate element is developed based on the physically neutral surface thin plate theory in cylindrical coordinate system. Three displacement functions are used to avoid the introduction of the mixed second order derivative degree of freedom at corner points. The derived explicit formulations with a varying node number can be applied for any type of node. A way to define the elastic spring constants is proposed to ensure the independent of the non-dimensional frequency parameter on the power-law exponent. The convergence and accuracy of the present model are validated by comparing the obtained results with those available in literatures. It is demonstrated that the proposed model is simple, straightforward and has good performance. A wide range of numerical results are reported to demonstrate the effect of the sector angle, ratio of inner/outer radii, and boundary conditions on the vibration behavior of the thin annular sectorial plate. Some tabulated results should be new which may serve as a reference for verifying numerical solutions obtained by other methods.

Performance evaluation of ad-hoc based aerial monitoring system

Recently there is a huge interest in designing and implementing systems that can be used in surveillance and emergency situations. These systems are designed and implemented using two main technologies that are: Mobile Ad-hoc Networks (MANETs) and the Unmanned Aerial Vehicles (UAVs). MANETs with its unique characteristics of rapid deployment, self-organization and cost effectivenes had made it a popular topic for designers and developers to design and implement such systems. In this paper, a prototype system was designed and implemented using MANETs and UAVs; this system can be developed to be used as an aerial monitoring system in surveillance and security issues, the system was used to record and send a real-time video from source to destination node over a multihop path. This system was first implemented and tested using testbed method, then it was simulated using network simulator (NS-3) with two case studies to evaluate the performance of the system using two routing protocols (Ad-hoc On-Demand Destance Vector AODV[1] and Optimised Link State Routing OLSR [2]). The evaluating metrics used here are; delay, average jitter, packet loss ratio (PLR) and packet delivery factor (PDF) against variable number of nodes. The optained results of the test bed method showed the configuration parameters and self-organization characteristics of MANET, the results obtained from the simulation platform illustrated that the OLSR had outperformed the AODV protocol in dense networks and the optimum number of nodes needed to cover the simulation area were 90 nodes.

Link distance-support vector regression (LD-SVR) based device free localization technique in indoor environment

Indoor localization using device free localization (DFL) in wireless sensor networks is gaining momentum nowadays due to the potential benefits of DFL. The techniques used in DFL can be broadly classified as statistical methods, compressive sensing, machine learning, radio tomographic method etc. Whenever loss factor and noise involved in the setup is unpredictable, techniques based on machine learning for target detection improves the result to a greater extend. The adaptability nature of support vector machines eased our choice of machine learning algorithm and support vector machine regression (SVR) is the proposed machine learning approach to address prediction of target position. Proposed link distance-support vector machine (LD-SVR) model uses link distance based DFL of single and multiple targets in indoor environment. Performance of the proposed model using SVR is analysed using parameters mean error and probability distribution function of mean error for various number of nodes and targets by imparting measurement error. The simulation results are found to be very much promising in a 3D room environment. The maximum value of mean error due to measurement error effect on link distance is less than 1 m.

Impact of awareness in metapopulation epidemic model to suppress the infected individuals for different graphs

The metapopulation dynamical model with information spreading in SIS epidemic diffusion model is presented for random walkers for sub-populations to display the effect of awareness. Two-layer SIS-UA (susceptible-infected-susceptible-unaware-aware) epidemic model is considered to reveal the effect of information spreading in a graph, where, each node denoted a sub-population. The individuals migrate by random walk from one node to another node on the graph by themselves or forcefully to escape from contagious disease. Moreover, the individuals in a node are classified into four states as unaware susceptible (US), aware susceptible (AS), unaware infected (UI) and aware infected (AI). Meanwhile, to study the impact of graph topology on individuals in each node (subpopulation), four different graphs: star, cycle, wheel and complete are considered as representing both homogeneous and heterogeneous connections with the various number of nodes. The influence of migration for information spreading is displayed to subdue infected individuals with time steps. Finally, several impressive cases in terms of what attributes of individuals in each subpopulation being allowed (or say, pushed) migration are considered, which is summarized in the form of a full phase diagram.

Performance Analysis of Enhanced Ad-Hoc on-Demand Distance Vector Routing Protocol in Smart Environment

MANETs have specific features that can satisfy the mobility and heterogeneous requirement of the smart environment. Smart applications need high Mobility, Bandwidth, Reliability and less Packet Loss and Delays; therefore, it is important to provide good Quality of Service (QoS) in such applications. So there is a dire need of identifying and exploring the relevant protocols that may be adapted for IoT enabled the smart environment. The routing protocols in smart environments are accountable for connectivity among nodes, fairness, quality of service, etc. Protocol &amp; path selection is the main strategies to design any mobile network. The chosen protocol must have the best in term of data integrity and data delivery. Hence the analysis of the protocols become an essential step. This paper presents various securities and safety-related issues of MANET-IoT system, and also advocate the requirement of enhancing routing protocols in a smart environment. In this research, a new enhanced cache update technique is introduced in MANET protocol to make it enable for the upcoming smart environment. The enhanced algorithm helps to detect the malicious node and remove the stale route present in the network, no matter which traffic mode is used and in which direction nodes are moving. Cache is upgraded in such manner that all nodes in the way are notified about the misbehaving node and its adjacent neighbors’ nodes will not use misbehaving node while searching for the route. Here the analysis has been done taking a various number of nodes. Packet Delivery and Packet Lost are two key parameters taken for analysis purpose.

Minimizing the maximum sender interference by deploying additional nodes in a Wireless Sensor Network

Interference is one of the major challenges faced by the communication networks. Since the interference leads to packet loss, packet collision and data re-transmission, higher the interference, higher is the energy consumption. Several algorithms were proposed for reducing the interference in a Wireless sensor network (WSN). By deploying additional nodes at an appropriate position in a WSN, it is possible to reduce the interference. We propose an algorithm in which, the main objective is to reduce the maximum Sender interference by deploying the additional nodes in the network, while connectivity of the network is preserved. We use the properties of Gabriel graph to achieve the reduction in interference. We present the simulation results which show the number of additional nodes to be deployed. The comparison of the maximum Sender interference obtained by the proposed algorithm with that of the Euclidean minimum spanning tree (MST) of the given network is presented through simulation. We show that the additional number of nodes required for deployment has an upper bound of n/2 , where n is the number of nodes. We also compute the average reduction in Sender interference of the network for a various number of nodes.

Evolutionary vaccination game approach in metapopulation migration model with information spreading on different graphs

The two layer SIR/V-UA epidemic diffusion model is incorporated in metapopulation migration model for random walkers to study the impact of awareness (rumor) for evolutionary vaccination game approach. In metapopulation, each node denoted a sub-population where the individuals migrate from one node to another by random walk following different graphs; star, cycle, wheel and complete. The framework of epidemic migration model in vaccination game with information spreading effect is observed in one single season as well as generation by some strategy update rules for an individual either taking vaccination or not. Furthermore, individuals in each node are divided into seven situations as; unaware susceptible, aware susceptible, unaware vaccinated, aware vaccinated, unaware infected, aware infected and recovered in a single season. Two strategy updating rules: individual based risk assessment (IB-RA) and strategy based risk assessment (SB-RA) are discussed for game theoretical approach for four new states; healthy vaccinated, infected vaccinated, successfully free rider and failed free rider at the end of each season to explore how different graphs of an underlying social network giving impact on the final epidemic size through the effect of information spreading in the complex population network with various number of nodes. Accordingly, the information spreading with migration in metapopulation model can enhance the epidemic threshold effectiveness and help to overcome on controlling disease diffusion.

Efficient Hybrid Emergency Aware MAC Protocol for Wireless Body Sensor Networks.

In Body Sensor Networks (BSNs), two types of events should be addressed: periodic and emergency events. Traffic rate is usually low during periodic observation, and becomes very high upon emergency. One of the main and challenging requirements of BSNs is to design Medium Access Control (MAC) protocols that guarantee immediate and reliable transmission of data in emergency situations, while maintaining high energy efficiency in non-emergency conditions. In this paper, we propose a new emergency aware hybrid DTDMA/DS-CDMA protocol that can accommodate BSN traffic variations by addressing emergency and periodic traffic requirements. It takes advantage of the high delay efficiency of DS-CDMA in traffic burst, and the high energy efficiency of DTDMA in periodic traffic. The proposed scheme is evaluated in terms of delay, packet drop percentage, and energy consumption. Different OPNET simulations are performed for various number of nodes carrying emergency data, and for various payload sizes. The protocol performance is compared to other existing hybrid protocols. Results show that the proposed scheme outperforms the others in terms of delay and packet drop percentage for different number of nodes carrying emergency data, as well as for different payload sizes. It also offers the highest energy efficiency during periodic observation, while adjusting the energy consumption during emergency by assigning spreading codes only to nodes holding emergency data.

Structuring a multi-nodal neural network in vitro within a novel design microfluidic chip.

Neural network formation is a complex process involving axon outgrowth and guidance. Axon guidance is facilitated by structural and molecular cues from the surrounding microenvironment. Micro-fabrication techniques can be employed to produce microfluidic chips with a highly controlled microenvironment for neural cells enabling longitudinal studies of complex processes associated with network formation. In this work, we demonstrate a novel open microfluidic chip design that encompasses a freely variable number of nodes interconnected by axon-permissible tunnels, enabling structuring of multi-nodal neural networks in vitro. The chip employs a partially open design to allow high level of control and reproducibility of cell seeding, while reducing shear stress on the cells. We show that by culturing dorsal root ganglion cells (DRGs) in our microfluidic chip, we were able to structure a neural network in vitro. These neurons were compartmentalized within six nodes interconnected through axon growth tunnels. Furthermore, we demonstrate the additional benefit of open top design by establishing a 3D neural culture in matrigel and a neuronal aggregate 3D culture within the chips. In conclusion, our results demonstrate a novel microfluidic chip design applicable to structuring complex neural networks in vitro, thus providing a versatile, highly relevant platform for the study of neural network dynamics applicable to developmental and regenerative neuroscience.