Network Simulation Tool Research Articles

Extending the VEF traces framework to model data center network workloads

Data centers are a fundamental infrastructure in the Big-Data era, where applications and services demand a high amount of data and minimum response times. The interconnection network is an essential subsystem in the data center, as it must guarantee high communication bandwidth and low latency to the communication operations of applications, otherwise becoming the system bottleneck. Simulation is widely used to model the network functionality and to evaluate its performance under specific workloads. Apart from the network modeling, it is essential to characterize the end-nodes communication pattern, which will help identify bottlenecks and flaws in the network architecture. In previous works, we proposed the VEF traces framework: a set of tools to capture communication traffic of MPI-based applications and generate traffic traces used to feed network simulator tools. In this paper, we extend the VEF traces framework with new communication workloads such as deep-learning training applications and online data-intensive workloads.

OQR-SC: An Optimal QoS Aware Routing Technique for Smart Cities Using IoT Enabled Wireless Sensor Networks

Internet of things (IoT) makes a machines optimization in everyday which processing the data by very intelligently and make communication more effectively and efficiently. In smart city environments, the data collection and communication play an important role in defining quality. Since the research period, it has been recommending a new data acquisition and data communication software framework for IoT smart applications. For further improvements, we recommend an optimal QoS aware routing technique for smart cities using IoT enabled wireless sensor networks (OQR-SC). In data gathering phase, the proposed system introduce chaotic bird swarm optimization (CBSO) algorithm for IoT sensor cluster formation; the improved differential search (IDS) algorithm used to estimate the faith degree of each sensor node, the highest trust node act as cluster head (CH). In data transferring phase, first illustrates lightweight signcryption technique for data encryption between two IoT sensors. Then, we use optimal decision making (ODM) algorithm to compute the optimal path between source–destination in IoT platform. Finally, the proposed OQR-SC technique is implemented using network simulation (NS2) tool and analyzes the performance of proposed technique with existing state-of-art techniques. The result summarizes that average energy consumption of proposed OQR-SC technique is 12.39% lower than the existing techniques; the average network lifetime of proposed OQR-SC technique is 15.96% higher than the existing techniques; the average delay of proposed OQR-SC technique is 21.08% lower than the existing techniques; and the average throughput of proposed OQR-SC technique is 17.89% higher than the existing techniques.

A Mathematical-Based Model for Estimating the Path Duration of the DSDV Routing Protocol in MANETs

Mobile Ad Hoc Networks (MANETs) are kind of wireless networks where the nodes move in decentralized environments with a highly dynamic infrastructure. Many well-known routing protocols have been proposed, with each having its own design mechanism and its own strengths and weaknesses and most importantly, each protocol being mainly designed for specific applications and scenarios. Most of the research studies in this field used simulation testbeds to analyze routing protocols. Very few contributions suggested the use of analytical studies and mathematical approaches to model some of the existing routing protocols. In this research, we have built a comprehensive mathematical-based model to analyze the Destination-Sequenced Distance Vector protocol (DSDV), one of the main widely deployed proactive protocols and studied its performance on estimating the path duration based on the concepts of the probability density function and the expected values to find the best approximation values in real scenarios. We have tested the validity of the proposed model using simulation scenarios implemented by the Network Simulator tool (NS3). The results extracted from both the mathematical model and the simulation have shown that the path duration is inversely proportional to both the speed of the node and the hop count. Furthermore, it had shown that the path duration estimated from the DSDV protocol is less than the actual path duration, due to the implementation of the settling time concept and keeping the “periodic routes’ update” parameter at a constant level, despite the fact that the node’s speed reduces the effective path utilization.

Multi-objective Optimization Model for Clustering Based Secure Routing with Congestion Avoidance in Mobile ADHOC Networks

Introduction: In Mobile Ad-Hoc Network (MANET), some of the major design issues are clustering, routing, and security. Clustering and routing techniques distribute the load to many network correlations so as to attain better utilization of resources, improved throughput and reduction in response time and workload. Besides, trust-based schemes help in sending messages in a secured manner and prevent the data from attackers by integrating authorized sender and receiver inside the network. Aim: The aim of the research article is to propose a new Multi-Objective Optimization (MOO) technique which intends to allocate the available networking resources properly, and balance the load in network, security, and effective data transmission. Method: The projected model operates on three major processes such as clustering, secured routing and data aggregation-based transmission scheme. MOO model involves different processes such as Fuzzy Logic (FL)-based clustering process, Lion Whale optimization algorithm with Congestion Avoidance (LW-CA) technique for routing process and integrated XOR and Huffman (IXH)-based data transmission process. So, the proposed model is collectively called FCAXH technique which achieves energy efficiency, proper load balancing and security. Results: Simulations were carried out using network simulator tool and the model was verified with and without the presence of attackers. The proposed method attained the maximum results in terms of throughput, Packet Delivery Ratio (PDR) and energy efficiency. Conclusion: The projected FCAXH model achieved energy efficiency, proper load balancing and security over other compared approaches even under the presence of attackers in the network.

Labelled Dataset on Distributed Denial-of-Service (DDoS) Attacks Based on Internet Control Message Protocol Version 6 (ICMPv6)

The most dangerous attack against IPv6 networks today is a distributed denial-of-service (DDoS) attack using Internet Control Message Protocol version 6 (ICMPv6) messages. Many ICMPv6-DDoS attack detection mechanisms rely on self-created datasets because very few suitable ICMPv6-DDoS attack datasets are publicly available due to privacy and security concerns. When implemented in a real network, however, a detection system that relies on a dataset with incorrect packet or flow representation and contains unqualified features generates a large number of false alerts. The goal of this work is to create a comprehensive ICMPv6-DDoS attack dataset that can be used for tuning, benchmarking, and evaluating any detection systems designed to detect ICMPv6-DDoS attacks. The proposed datasets met the criteria for a good dataset, ensuring their usefulness to other researchers. A GNS3 network simulation tool is used to simulate an IPv6 network and generate ICMPv6 traffic for the dataset. The generated traffic contains both normal and abnormal ICMPv6 traffic, with the abnormal traffic containing ten different ICMPv6-DDoS attacks based on RA and NS message flooding. Five classifiers were chosen, varying in terms of type, classification performance, and the number of features used, and the results were as follows: decision tree 80%, support vector machine 78%, naïve Bayes 80%, k -nearest neighbours 81%, and neural networks 81%. The proposed dataset has been shown to accurately represent attack traffic in tests, with a high detection accuracy and a low false-positive rate.

Performance Evaluation of VANET Routing Protocols in Madinah City

Traffic management challenges in peak seasons for popular destinations such as Madinah city have accelerated the need for and introduction of autonomous vehicles and Vehicular ad hoc networks (VANETs) to assist in communication and alleviation of traffic congestions. The primary goal of this study is to evaluate the performance of communication routing protocols in VANETs between autonomous and human-driven vehicles in Madinah city in varying traffic conditions. A simulation of assorted traffic distributions and densities were modeled in an extracted map of Madinah city and then tested in two application scenarios with three ad hoc routing protocols using a combination of traffic and network simulation tools working in tandem. The results measured for the average trip time show that opting for a fully autonomous vehicle scenario reduces the trip time of vehicles by approximately 7.1% in high traffic densities and that the reactive ad hoc routing protocols induce the least delay for network packets to reach neighboring VANET vehicles. From these observations, it can be asserted that autonomous vehicles provide a significant reduction in travel time and that either of the two reactive ad hoc routing protocols could be implemented for the VANET implementation in Madinah city. Furthermore, we perform an ANOVA test to examine the effects of the factors that are considered in our study on the variation of the results.

NetSeekR: a network analysis pipeline for RNA-Seq time series data

BackgroundRecent development of bioinformatics tools for Next Generation Sequencing data has facilitated complex analyses and prompted large scale experimental designs for comparative genomics. When combined with the advances in network inference tools, this can lead to powerful methodologies for mining genomics data, allowing development of pipelines that stretch from sequence reads mapping to network inference. However, integrating various methods and tools available over different platforms requires a programmatic framework to fully exploit their analytic capabilities. Integrating multiple genomic analysis tools faces challenges from standardization of input and output formats, normalization of results for performing comparative analyses, to developing intuitive and easy to control scripts and interfaces for the genomic analysis pipeline.ResultsWe describe here NetSeekR, a network analysis R package that includes the capacity to analyze time series of RNA-Seq data, to perform correlation and regulatory network inferences and to use network analysis methods to summarize the results of a comparative genomics study. The software pipeline includes alignment of reads, differential gene expression analysis, correlation network analysis, regulatory network analysis, gene ontology enrichment analysis and network visualization of differentially expressed genes. The implementation provides support for multiple RNA-Seq read mapping methods and allows comparative analysis of the results obtained by different bioinformatics methods.ConclusionOur methodology increases the level of integration of genomics data analysis tools to network inference, facilitating hypothesis building, functional analysis and genomics discovery from large scale NGS data. When combined with network analysis and simulation tools, the pipeline allows for developing systems biology methods using large scale genomics data.

Design and implementation of energy-aware cross-layer routing protocol for wearable body area network

PurposeA wireless body area network (WBAN) plays a crucial role in the health-care domain. With the emergence of technologies like the internet of things, there is increased usage of WBAN for providing quality health services. With wearable devices and sensors associated with human body, patient’s vital signs are captured and sent to doctor. The WBAN has number of sensor nodes that are resource constrained. The communications among the nodes are very crucial as human health information is exchanged. The purpose of this paper aims to have Quality of Service (QoS) with energy aware and control overhead aware. Maximizing network lifetime is also essential for the improved quality in services. There are many existing studies on QoS communications in WBAN.Design/methodology/approachIn this paper, with the aim of energy-efficient WBAN for QoS, a cross-layer routing protocol is designed and implemented. A cross-layer routing protocol that is ad hoc on-demand distance vector (AODV)-based, energy and control overhead-aware (AODV-ECOA) is designed and implemented for energy-efficient routing in WBAN. The cross-layer design that involves multiple layers of open systems interconnection reference model, which will improve energy efficiency and thus QoS.FindingsImplementation is simulated using the network simulator tool, i.e. NS-2. The proposed cross-layer routing protocol AODV-ECOA shows least bandwidth requirement by control packets, leading to less control overhead, highest packet delivery ratio and energy efficiency. The experimental results revealed that AODV-ECOA shows better performance over existing protocols such as AODV and POLITIC.Originality/valueAn efficient control overhead reduction algorithm is proposed for reducing energy consumption further and improves performance of WBAN communications to realize desired QoS.

Fuzzy Based Reliable Load Balanced Routing Approach for Ad hoc Sensor Networks

Energy management and packet delivery rate are the important factors in ad hoc networks. It is the major network where nodes share the information without administration. Due to the mobility of nodes, maximum energy is spent on transmission of packets. Mostly energy is wasted on packet dropping and false route discovery. In this research work, Fuzzy Based Reliable Load Balanced Routing Approach (RLRA) is proposed to provide high energy efficiency and more network lifetime using optimal multicast route discovery mechanism. It contains three phases. In first phase, optimal multicast route discovery is initiated to resolve the link failures. In second phase, the link quality is estimated and set to threshold value to meet the requirements of high energy efficiency. In third phase, energy model is shown to obtain total energy of network after transmission of packets. A multicast routing is established Based on path reliability and fault tolerant calculation is done and integrated with multicast routing. The routes can withstand the malicious issues. Fuzzy decision model is integrated with propose protocol to decide the performance of network lifetime. The network simulation tool is used for evaluating the RLRA with existing schemes and performance of RLRA is good compared to others.

Adaptive DSR routing caching strategy based on local connection mechanism

An optimisation solution for DSR routing protocol cache management strategy based on local connection mechanism is proposed to solve the problem that DSR routing protocol can easily cause incorrect routing and cause network performance degradation when dealing with dynamically changing network topology. A local connection mechanism is introduced to ensure the reachability of links between nodes and improve the accuracy of cached routing entries. Finally, using the network simulation tool NS-3 to test the improved DSR routing protocol after the cache strategy, compare the packet delivery rate of the nodes before and after the optimisation, the route initiation frequency and the average delay. Simulation results show that the proposed scheme can effectively improve the packet data delivery rate of the DSR routing protocol and reduce the average delay and enhance the overall performance of the protocol.

Radio Optical Network Simulation Tool (RONST)

This paper presents a radio optical network simulation tool (RONST) for modeling optical-wireless systems. For a typical optical and electrical chain environment, performance should be optimized concurrently before system implementation. As a result, simulating such systems turns out to be a multidisciplinary problem. The governing equations are incompatible with co-simulation in the traditional environments of existing software (SW) packages. The ultra-wideband (UWB) technology is an ideal candidate for providing high-speed short-range access for wireless services. The limited wireless reach of this technology is a significant limitation. A feasible solution to the problem of extending UWB signals is to transmit these signals to end-users via optical fibers. This concept implies the need for the establishment of a dependable environment for studying such systems. Therefore, the essential novelty of the proposed SW is that it provides designers, engineers, and researchers with a dependable simulation framework that can accurately and efficiently predict and/or optimize the behavior of such systems in a single optical-electronic simulation package. Furthermore, it is supported by a strong mathematical foundation with integrated algorithms to achieve broad flexibility and low computational cost. To validate the proposed tool, RONST was deployed on an ultra-wideband over fiber (UWBoF) system. The bit error rate (BER) has been calculated over a UWBoF system, and there is good agreement between the experimental and simulated results.

An approach to detect black hole attack for congestion control utilizing mobile nodes in wireless sensor network

Mobile ad-hoc Network (MANET) is temporary and dynamic network topology, wherein nodes are mobile in nature with bandwidth and resource constraint. Applications of MANET’s are widely used in different areas. Provisioning of quality of service (QoS) for routing in MANET’s is a challenging issue. Packet drop occurs due to congestion related issues like limited bandwidth, link failure and interference also misbehaving node drops the packet to harm the network. Differentiating packet loss due to congestion or malicious node is a tedious job. Securing the mobile nodes from attacker has become one of the crucial aspects of providing QoS, since nodes are weak to different kinds of attacks and threats that impact network connectivity and functionality. The black-hole attack is examined to be epidemic and popular active attack that degrades overall reliability and network performance by dropping all the incoming packets. In Black-hole node pretends that it has a shortest route to destination and intent to deceive every node in the network. In this paper we differentiate packet loss due to congestion or by malicious node, our scheme utilises on-demand link and energy aware dynamic multipath (O-LEADM) routing scheme for MANET’s to detect black-hole node by integrating bait method, the behaviour of node is analysed using control messages destination-sequence (des-Seq) and reply-sequence (rep-Seq) while accessing the channel. During route discovery each intermediated node in the network sends the des-Seq message to all its neighbour nodes, and then neighbour nodes intern replies to intermediate node by sending rep-Seq message. If des-Seq and req-Seq from the neighbours does not match, then node is said to be malicious. Connection to the network layer is allowed to intermediate node if des-Seq and rep-Seq matches. Channel availability and link quality parameter estimates the link stability thus nodes select forwarding based on their behaviour and capable of achieving QoS parameters such as link quality, residual energy and higher packet delivery. Simulation under various network conditions is experimented using Network simulator tool (NS2) and using parameters the performance metric is in terms of delay, packet delivery ratio, overhead and energy are evaluated.

Research on Emergency Logistics Model of Agricultural Products Based on Coupling of Petri Net and Blockchain

In this COVID-19 epidemic, due to insufficient awareness of the impact of sudden public health emergencies on agricultural logistics at this stage, agricultural products were left unsold, stocks were backlogged, and losses were severe. In the process of distribution, we should not only ensure a short time cycle and avoid the contamination of agricultural products by foreign bacteria, but also pay attention to the waste of human, material, and financial resources. Therefore, this study mainly adopts the combination of the petrochemical network and block chain to build an agricultural products emergency logistics model. This paper first shows the operation mechanism of the petri dish network and blockchain coupling in the form of a graph and then uses the culture network modelling and simulation tool PIPE to directly verify the construction model. It is proved that the structure and overall business process of the agricultural products logistics system constructed by combining the Petri net and block chain are reasonable, reliable, and feasible in practical application and development. It is hoped that this study can provide a reference direction for agricultural emergency logistics.

Construction of Modularized English Teaching Platform for Multimedia Wireless Network Based on NS2 Simulation Software

Using the NS2 network simulation tool to teach the “wireless network” course can enhance students’ understanding of wireless network protocols through visualization and can also improve students’ ability to analyze problems hands on. We built a multimedia wireless network modularized English teaching platform based on NS2 simulation software; made full use of the rich components and network resources provided by NS2 to achieve a high degree of code reuse and reduce the time for developing simulation codes; designed the overall framework of this multimedia wireless network modular English teaching platform based on the B/S structure; and solved the weight coefficient and importance value of the learning input evaluation index, based on the feedback elite teaching optimization algorithm, the improved teaching formula, the increase in the number of exchanges, and the improvement in the learner’s performance. The experimental results show that the LEACH and LEACH-C protocols of the clustered NS2 simulation software have more surviving nodes most of the time, which indicates that the clustering routing protocol has better performance.

Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks

The exponential growth of the internet of things and united applications have renewed the scholarly world to grow progressively proficient routing strategies. Quality of service (QoS) and reduced power consumption are the major requirements for effective data transmission. The larger part of the applications nowadays including internet of things (IoT) communication request power effective and QoS-driven WSN configuration. In this paper, an exceptionally strong and effective evolutionary computing allied WSN routing convention is designed for QoS and power effectiveness. The proposed routing convention includes proficient capacity called network condition-based malicious node detection. It adventures or mines the dynamic node/network parameters to recognize malignant nodes. Experimentation is done using network simulator tool NS2. Results ensure that the proposed routing model accomplishes higher throughput, low energy utilization, and low delay that sustains its suitability for real-time WSN.

Fusion of ACO and PSO Technique Based Optimized Routing for Intellectual Routing in Wireless Ad hoc Networks

Wireless Ad hoc network (WANET) is an assortment of mobile nodes, which energetically custom a provisional network lacking the dependence of any infrastructure. In Dijkstra-Ant Colony Optimization Algorithm (ACO) forStraightas well asHarmlessEmigrationis applied to finding the shortest and safest path. However, this method cannot work perform when nodes are movable. In addition, ACO algorithm increases the power consumption and execution time. To solve the above problem in this work, Fusion of ACO and PSO technique based Optimized Routing (FAPO) for Intellectual Routing in WANET. This approachACOand Particle Swarm Optimization (PSO) technique is proposed to provide optimized routing and reduces link failures. The ACO and PSO techniquesinitiates with creating a greatquantity of mobile nodes in the search space and selects the route with high quality link. The function of the introducedtechnique is measured using the network simulator tool NS-2.

Cluster based Optimal Energy Efficient Routing Protocol for Wireless Sensor Networks

Balancing the energy consumption and location accuracy is one of the critical tasks in WSN. Energy consumption of sensor nodes is measured in terms of route discovery, packet forwarding and data transmission. In this research work, it is proposed that scheduling based Optimal Energy Clustering Scheme (SOECS) to attain the maximum location accuracy and energy efficiency during route maintenance. It contains three major modules. In first module, the node deployment is done using Gaussian distribution function to route the packets effectively. In second module, Cluster heads are chosen and energy is estimated for optimal cluster heads. In third module, TDMA scheduling algorithm is introduced to improve the energy efficiency using stable routes and scheduling table. The work is evaluated using network simulation tool. The proposed scheme produces high performance than existing schemes.

Performance Analysis of TCP Variants Using AODV and DSDV Routing Protocols in MANETs

Background: TCP is the most reliable transport layer protocol that provides reliable data delivery from source to destination node. The background of TCP suggests that it works well in wired networks but it is assumed that TCP is less preferred for ad-hoc networks. However, for application in ad-hoc networks, TCP can be modified to improve its performance. Various researchers have proposed improvised variants of TCP by only one or two measures. Objective: These one or two measures do not seem to be sufficient for proper analysis of improvised version of TCP. Therefore, in this paper, our objective is to evaluate the performance of different TCP variants and their results are investigated with DSDV and AODV routing protocols. Methods: Our methodology includes the analysis of various performance measures such as throughput, delay, packet drop, packet delivery ratio and number of acknowledgements. The simulation results are carried out by varying number of nodes in network simulator tool NS2. Results: It is observed in results that TCP Newreno achieved higher throughput and packet delivery ratio with both AODV and DSDV routing protocols. Whereas TCP Vegas achieved minimum delay and packet loss with both DSDV and AODV protocol. However TCP sack achieved minimum acknowledgment with both AODV and DSDV routing protocols. Conclusion: The comparison of all these TCP variants helps in drawing conclusion that, TCP Newreno provides better performance with both AODV and DSDV protocols.

Research and application of node fuzzy identification and localization in wireless sensor networks

SummaryIn recent years, sensor technology has attracted the attention of countries all over the world because of its potential huge application value, and it has played an important role in people's daily life and social production activities. This paper mainly studies the location algorithm based on ranging in the location algorithm and analyzes the advantages and disadvantages of the algorithm. In order to optimize the positioning of wireless sensor networks, a fuzzy controller is designed to fuzzify the input information of sensor nodes. Using Matlab network simulation tool, the congestion control algorithm proposed in this paper was simulated and compared with several typical congestion control protocols in wireless sensor networks. Experimental results show that the algorithm can improve network throughput, reduce network packet loss, and have a significant impact on network performance. The network throughput of the congestion control algorithm based on fuzzy logs is stable at 180 packets per second. Compared with CODA, the congestion control algorithm based on fuzzy logarithm increases the packet loss rate by 55–66%, and the SenTCP algorithm increases by 37–40%. It can be seen that congestion control algorithms based on fuzzy logic can play an important role in wireless sensor networks.

A comparative study of different network simulation tools and experimentation platforms for underwater communication

Study of computer networks and their performance parameters like delay, bandwidth utilization, throughput, latency, jittering, and packet loss. have gained significant importance in the recent times. Simulation studies have been preferred for these parameters in computer networks, which in a real time is a difficult task. A network consists of many networking devices as gateways, routers, bridges, wireless access points and hub connected to it. To implement any new protocol or algorithm in a network is costlier and time consuming. Recently lot of research is going on underwater wireless sensor networks (UWSNs). Conducting real time experiments for underwater applications are overpriced, so as an alternative solution for this, we can conduct simulation studies to reduce the cost and quicken the research activities.In this paper we explore the different experimentation platforms and simulation tools available that help the network architects to develop new protocols or do changes to the existing protocol in a productive manner. We classify the tools based on various parameters and provide guidelines for researchers to choose a suitable platform based on their requirements.