NS2 Software Research Articles

Crowd Monitoring System Based on Unmanned Aerial Vehicles: Secure Key Agreement Scheme

Unmanned Arial Vehicles (UAVs) can be applied to survey or for monitoring huge crowd where conventional monitoring systems fail. Even though UAVs is proven to be effective way for monitoring and surveying there present a threat of data getting leaked when it is being transferred to the user’s device. To lessen these dangers a secure channel amid the user and the UAVs needs to be determined. There are multiple key agreement methods which is already present but they are either heavy authentication type or less secure to the attacks from the unscrupulous parties. In this paper, we provide an approach to mitigate such threats using a public key cryptographic method with a session-based authentication. The above-mentioned method is simulated using NS2 software and it’s efficiency will be recorded at the end.

An efficient cluster head selection in WSNs using transient search optimization (TSO) algorithm

SummaryIn this manuscript, a nature‐inspired optimization method, named transient search optimization (TSO), is proposed. Energy‐based monetary custom is a serious issue on the wireless sensor network (WSN). Here, the network clustering is an effectual technique to reduce node energy depletion and increased network lifetime. The proposed method aims to improve the efficiency of sensor nodes (SNs) by reducing their detachment, minimizing energy transmission, and protecting excessive energy stored in the nodes. This approach helps decrease delays, reduce traffic flow, and optimize network performance. The execution is implemented on the NS2 software. The experimental outcomes exhibit that the proposed system performs better based on two wireless sensor architectures, such as 50 nodes and 100 nodes. The parameter produces 52.24%, 54.38%, and 56.37% better network lifetime; 44.71%, 46.24%, and 49.45% higher alive node; and 39.26%, 36.26%, and 28.65% lesser dead SNs compared with existing techniques like multi‐objective cluster head (CH)–based energy‐aware optimized routing approach in wireless sensor network (MOCH‐ORR‐WSN), energy effective CH selection with improved sparrow search algorithm in WSN (ECH‐ISS‐WSN), and energy effectual cluster basis routing protocol under butterfly optimization along ant colony optimization algorithms for WSN (EEC‐BOA‐ACO‐WSN).

An energy‐efficient method using PSO clustering and fuzzy routing to reduce energy consumption in IoT

SummaryIn “Internet of Things” (IoT) technology, all objects can connect to the Internet with a unique Internet address. The sensors have limited energy resources due to their use of batteries in supplying energy, and since battery replacement in these sensors is not usually feasible, the longevity of wireless sensor networks is limited. Therefore, reducing the energy consumption of the used sensors in IoT networks to increase the network lifetime is one of the crucial challenges and parameters in such networks. These networks are subject to a variety of errors. Errors in wireless communication channels, network dynamics due to the mobility of nodes, and the potential for mistakes in mobile nodes are among the causes of errors in these networks. Despite the above failures, the development of routing algorithms in IoT‐based networks has become a significant challenge for researchers, so it is essential to provide routing algorithms to increase network lifespan and reduce energy consumption. In this study, a two‐dimensional network‐based architecture for the Internet of Things is presented. The proposed algorithm first organizes the nodes into logical cells and selects nodes in each cell as the cluster head. The cluster head is selected based on the binary Particle Swarm Optimization algorithm. Then, each node sends its collected data to the cluster head. The cluster heads first aggregate the received data and then use a fuzzy method to send the data to the base station. The proposed algorithm uses the remaining energy level parameter, cluster density, and location of each cell using fuzzy system capabilities and the particle swarm algorithm to try to route data with less energy consumption and increase network lifespan. The proposed method is simulated in ns2 software, and for a more accurate evaluation, we compare it with LEACH, Ant‐C, PSO, EABC, and SOA‐CH algorithms. We see that the proposed method performs better than other methods in terms of energy consumption and network lifespan.

Performance and QoS Assessment in WSN: Comparative Analysis of MBC, ECHERP, and PDCH Routing Methods

Objective: The objective of this research is to assess the performance and Quality of Service (QoS) provided by PDCH when compared with ECHERP and MBC routing protocols(RPs) within Wireless Sensor Networks (WSNs). Methods: Utilizing the NS2 Simulator, this paper provides an in-depth exploration of three hierarchical RPs viz. Equalized Cluster Head Election RP (ECHERP), Mobility Based Clustering (MBC), and PDCH (PEGASIS with Double Cluster head). A thorough examination of each protocol's performance is conducted, focusing on a range of QoS metrics such as Energy Consumption, Packet Drop Ratio, Throughput, and Delay. Findings: A comparative assessment is conducted between PDCH, ECHERP, and MBC, extracting QoS parameters. The examination and findings reveal that PDCH exhibits superior performance over ECHERP by 26.15%, 20%, 15.71%, and 37.73%. Similarly, PDCH outperforms MBC by 23.19%, 14.29%, 4.87%, and 15.13% across the mentioned parameters. Novelty: In this simulation, the NS2 software is utilized, with a specific emphasis on the suggested parameters. These metrics are crucial for evaluating the overall performance of different RPs in Wireless Sensor Networks (WSNs).

Secured Routing Protocol for Improving the Energy Efficiency in WSN Applications

A staggering number of applications rely on the network architecture to carry out their tasks, which has led to a fast growth in wireless sensor networks (WSN). The possibility of harmful activity and data theft is growing as a result of the growth in devices and data. Thus, the network’s regular users have an impact on legitimate data delivery, which lowers customer happiness and worsens network standards. The data have been saved using a variety of security procedures that have been developed in past research studies. However, harmful activity continues to engage in its illegal operations despite their efforts to safeguard data transmission in the network. As a result, a number of recent research projects have concentrated on predicting innovative techniques and processes to offer security in WSN. In comparison to existing methods, this work attempted to offer an effective tighter security for WSN and suggested an ML‐Based Secured Routing Protocol (MLSRP) for WSN with improved energy efficiency and overall performance. Energy efficiency is the main requirement of WSNs, hence a clustered network is proposed where the data are routed through the cluster head nodes. In this paper, a multicriteria based decision‐making (MCDM) model is used by the MLSRP to perform data routing, clustering, and cluster head election while also analyzing a number of network characteristics that might affect the quality of a node, route, and data. In NS2 software, the suggested framework is put into practice and simulated. The results are then validated to gauge performance. The observed quantitative results reveal that the proposed MLSRP method attains an improved network lifetime by 5% and network throughput of 6%. It reduces energy consumption by 40%, curtails overhead to 37%, and minimizes end‐to‐end delay by 30% than the other conventional methods. The suggested framework performs better than others when its total performance is compared to that of older methods.

Secure and Energy-Based STEERA Routing Protocol for Wireless Sensor Networks

In wireless sensor networks (WSN), the multifunctional low-power sensor nodes are linked to base stations and are highly responsible for sensing various information. However, maintaining the network’s lifespan is a major issue because of limited battery capacity and node failures. Thus, the proposed study introduced a new Scalable Trust-based Energy Efficient Routing Algorithm (STEERA) with Adaptive Grasshopper Algorithm (AGA) to enhance the network lifespan. At first, the trust values (Tv) are generated for each node to eliminate the malicious node with the help of penalty factor and volatilization. To make efficient routing process, the nodes are formed into cluster groups. A suitable cluster head is selected for each cluster to mitigate the energy consumption problem through the AGA approach by optimizing the parameters like Tv, distance and residual energy. Finally, the data packets are effectively transmitted through a multi-hop routing process by selecting an appropriate path and satisfying certain parameters through Fire Hawks Optimization (FHO). To simulate the proposed techniques, NS2 software is employed, and the performance is measured over various metrics like energy consumption, residual energy, the lifespan of a network, packet loss ratio and average end-to-end delay. The performance analysis shows that the proposed protocol design has obtained higher results than conventional routing protocols.

DoS Attack Detection Mechanism in Wireless Sensor Networks

Wireless sensor networks (WSNs) are not like traditional networks in terms of their characteristics. Unlike WSN, in classic networks, networking mechanisms have decision-making power with reference to the management of an incoming packet only based on its internet protocol (IP) destination address. Assailant nodes can activate a denial of service (DoS) attack after entering the network. This research work focuses on tracing these collusive nodes by applying a trust-based scheme. The trust-based scheme includes measuring the degree of trust among all nodes. Nodes with minimum trust are designated as malicious nodes. Trust is measured based on the overall packets transferred during the time slot allotted. The node forwarding maximal packets and exploiting minimal assists will be tagged as malicious. The nascent architecture was deployed in NS2, and the outcomes were analysed based on particular performance metrics. To calculate trust, the overall packets forwarded by nodes in the allotted slot were considered. The node that transmits the largest number of packets and uses negligible assets was declared a vindictive node. This task implementation presents the approach in the NS2 software and analyses the results based on certain metrics.

An Intersection-Based Routing Scheme Using Q-Learning in Vehicular Ad Hoc Networks for Traffic Management in the Intelligent Transportation System

Vehicular ad hoc networks (VANETs) create an advanced framework to support the intelligent transportation system and increase road safety by managing traffic flow and avoiding accidents. These networks have specific characteristics, including the high mobility of vehicles, dynamic topology, and frequent link failures. For this reason, providing an efficient and stable routing approach for VANET is a challenging issue. Reinforcement learning (RL) can solve the various challenges and issues of vehicular ad hoc networks, including routing. Most of the existing reinforcement learning-based routing methods are incompatible with the dynamic network environment and cannot prevent congestion in the network. Network congestion can be controlled by managing traffic flow. For this purpose, roadside units (RSUs) must monitor the road status to be informed about traffic conditions. In this paper, an intersection-based routing method using Q-learning (IRQ) is presented for VANETs. IRQ uses both global and local views in the routing process. For this reason, a dissemination mechanism of traffic information is introduced to create these global and local views. According to the global view, a Q-learning-based routing technique is designed for discovering the best routes between intersections. The central server continuously evaluates the created paths between intersections to penalize road segments with high congestion and improve the packet delivery rate. Finally, IRQ uses a greedy strategy based on a local view to find the best next-hop node in each road segment. NS2 software is used for analyzing the performance of the proposed routing approach. Then, IRQ is compared with three methods, including IV2XQ, QGrid, and GPSR. The simulation results demonstrate that IRQ has an acceptable performance in terms of packet delivery rate and delay. However, its communication overhead is higher than IV2XQ.

An Authentication-Based Secure Data Aggregation Method in Internet of Things.

Internet of Things (IoT) means connecting different devices through the Internet. The Internet of things enables humans to remotely manage and control the objects they use with the Internet infrastructure. After the advent of the Internet of Things in homes, organizations, and private companies, privacy and information security are the biggest concern. This issue has challenged the spread of the Internet of things as news of the user’s theft of information by hackers intensified. The proposed method in this paper consists of three phases. In the first phase, a star structure is constructed within each cluster, and a unique key is shared between each child and parent to encrypt and secure subsequent communications. The second phase is for intra-cluster communications, in which members of the cluster send their data to the cluster head in a multi-hop manner. Also, in this phase, the data is encrypted with different keys in each hop, and at the end of each connection, the keys are updated to ensure data security. The third phase is to improve the security of inter-cluster communications using an authentication protocol. In this way, the cluster heads are authenticated before sending information to prevent malicious nodes in the network. The proposed method is also simulated using NS2 software. The results showed that the proposed method has improved in terms of energy consumption, end-to-end delay, flexibility, packet delivery rate, and the number of alive nodes compared to other methods.

A hierarchical congestion control method in clustered internet of things

Internet of things (IoT) is a modern technology where data can be transmitted to any things (human, animal, or object) over communications networks, whether internet or intranet. Congestion occurs when the input data rate to the node was higher than the output data rate of node. Congestion control in computer network modulates traffic entry into a network in order to avoid congestive. This paper suggests a method for congestion control in the internet of things in two phases. The first phase is intra-cluster congestion control, which uses two parameters, congestion score (CS) and buffer empty space (BES), to congestion avoidance. In this phase based on these two parameters, nine states are defined to determine the congestion status of each node, and based on these 9 states the appropriate decision is made to the node. The second phase is inter-cluster congestion control. In this phase, after determining cluster head priority, the parameters of back-off timer (BFT), waiting time to receive acknowledgment \(({\text {WTTR}}_{\text {ACK}})\), sequence number (SEQ) and retransmission counter (RC) are used for congestion control. The proposed congestion control method is simulated by NS-2 software. A comparison between the performance of proposed method and conventional methods shows that applying proposed method results in a significant improvement in average congestion score (CS), packet lost rate, energy consumption and end-to-end delay.

A QoS Aware Cluster Head Selection and Hybrid Cryptography Routing Protocol for Enhancing Efficiency and Security of VANETs

Nowadays, VANET (vehicular ad hoc network) is one of the key aspects of developing advanced intelligent transportation systems. Due to its huge mobility and rapid topology alteration, the network exposes to link failure that affects the firmness of the network and causes delay and congestion. Additionally, the dynamic change in the network routing affects the network’s security, makes it vulnerable to various attacks, and causes data loss. In order to overcome these drawbacks an efficient and highly secured routing protocol is needed. Subsequently, in this research, a new routing protocol is proposed that has the combination of quality of service (QoS)-aware cluster head (CH) selection and hybrid cryptography, which is named QoS+. The QoS+ protocol is mainly divided into QoS-based CH selection and hybrid cryptography modules. The CH selection module performs based on QoS parameters attempt to provide reliable and stable clusters and improve the firmness and connectivity during the communication process of the network. The hybrid cryptography module contains advanced encryption standard (AES) and elliptic curve cryptosystems (ECC) algorithms. It attempts to improve the security and privacy of the network. The QoS+ protocol is evaluated by a developed VANET simulator using NS2 software. The simulator consists of a network model, a load model, and an attack model. Various speed and transmission ranges and gray hole and wormhole attacks are used in the simulator. The outcome calculated from the performance analysis shows that the proposed QoS+ protocol has 7% to 24% higher message success rate, 500 to 800 higher packets normalized routing load, 350 to 550 Kbps higher throughput, 5% to 17% higher efficiency and 50ms to 12ms lower end to end delay when compared with the earlier works of ECHS and KMSUNET. The proposed QoS+ protocol also achieves superior performance in terms of CH efficiency, cluster member efficiency, and average cluster number with various speeds and transmission ranges.

A dynamic source routing protocol based on path reliability and link monitoring repair.

The two most essential factors for mobile self-organizing networks applicable to drones are reliability and stability. In harsh communication environments, such as mountainous regions and natural disasters, the use of satellites and terrestrial communication stations has severe time delays due to the high speed of UAVs, resulting in frequent communication interruptions with UAVs. Therefore, UAVs need to establish self-organizing networks for communication and information sharing. High-speed movement will lead to rapid changes in the network topology, resulting in established links being in an unstable connection state and even frequent routing errors, thus preventing the establishment of stable communication links. In order to improve the communication quality of UAVs under high-speed movement, we propose a dynamic source routing protocol based on path reliability and monitoring repair mechanism (DSR-PM). The model performs data transmission by filtering the best reliability path. The link state information is monitored during transmission and broken links are repaired in time to ensure the communication stability and reliability of the links and improve the data transmission efficiency. We simulated the approach in NS2 software and the simulation results show that the DSR-PM protocol effectively reduces parameters such as overhead, packet loss and delay, improves network throughput, and provides better communication performance.

Energy-Efficient Fuzzy Management System for Internet of Things Connected Vehicular Ad Hoc Networks

Many algorithms use clustering to improve vehicular ad hoc network performance. The expected points of many of these approaches support multiple rounds of data to the roadside unit and constantly include clustering in every round of single-hop data transmission towards the road side unit; however, the clustering in every round maximizes the number of control messages and there could be the possibility of collision and decreases in network energy. Multi-hop transmission prolongs the cluster head node’s lifetime and boosts the network’s efficiency. Accordingly, this article proposes a new fuzzy-clustering-based routing algorithm to benefit from multi-hop transmission clustering simultaneously. This research has analyzed the limitation of clustering in each round, different algorithms were used to perform the clustering, and multi-hop routing was used to transfer the data of every cluster to the road side unit. The fuzzy logic was used to choose the head node of each cluster. Three parameters, (1) distance of each node, (2) remaining energy, and (3) number of neighbors of every node, were considered as fuzzy criteria. The results of this research were compared to various other algorithms in relation to parameters like dead node in every round, first node expire, half node expire, last node expire, and the network lifetime. The simulation results show that the proposed approach outperforms other methods. On the other hand, the vehicular ad hoc network (VANET) environment is vulnerable at the time of data transmission. The NS-2 software tool was used to simulate and evaluate the proposed fuzzy logic opportunistic routing’s performance results concerning end-to-end delay, packet delivery, and network throughput. We compare to the existing protocols, such as fuzzy Internet of Things (IoT), two fuzzy, and Fuzzy-Based Driver Monitoring System (FDMS). The performance comparison also emphasizes an effective utilization of the resources. Simulations on the highway environment show that the suggested protocol has an improved Quality of Service (QoS) efficiency compared to the above published methods in the literature.

Modified Energy Efficient with ACO Routing Protocol for MANET

Due to the specific design of the network upon the requirements of the demands as well as the situation at which the setting up of a physical network is impossible, a significant role is played by mobile ad-hoc network (MANET) in the applications of military. Various critical tasks like robust & dynamic military workstations, devices as well as smaller sub-networks within the battle field are handled by the presented network type controls the infrastructure less communication. A highly demand of the efficient routing protocol’s design is existing which ensures safety as well as reliability to transmit the extremely vulnerable as well as the secret military data within the defense networks. The designing of an energy efficient layer routing protocol within the network on behalf of the military applications is done in this method and the simulation is done with the help of a novel cross layer approach of design for increasing the reliability as well as the lifetime of the network. However, the optimum path selection is not allowed by PDO-AODV technique. Therefore, a novel ACO-DAEE (Ant colony optimization with delay aware energy efficient) to select an optimum path as well as to mitigate the delay time within the network system is proposed. Maintaining the optimum paths within the network while transmitting the data effectively is the major objective. With respect to packet delivery ratio, end to end delay, and throughput, it is indicated by the simulation outputs that the performance of ACO-ADEE is quite good. The efficiency of this technique is verified in the simulation outcomes using NS2 software.

SSOPS based Solution to Improve QoS in VANET

Vehicular Ad-hoc Networks (VANETs) is an emerging network technology derived from ad-hoc networks. This paper provides the state-of-the-art of VANETs and provides optimum proposal by improving Quality of Service (QoS.) Today, wireless systems are preferred over wired systems and these are gaining popularity as it provides wireless connectivity to the users irrespective of their geographic position, VANET is one of them. VANETs are installed to minimize the risk of road accidents and to improve passenger comfort by permitting the vehicles to exchange various types of data. In this paper, the Signal Strength based Optimum Path Selection (SSOPS) based solution on how to mitigate the QoS issues that exists while using the existing methods are discussed. Moreover, the solution has been tested using NS2 software using various parameters.

Improved hybrid cuckoo black widow optimization with interval type 2 fuzzy logic system for energy‐efficient clustering protocol

SummaryRecently, due to its excellent performance with the limited resources the wireless sensor network (WSN) is a challenging research area. The WSN consists of the number of nodes and power resources with limited energy parameters, but it comprises few difficulties. The energy‐efficient distributed clustering (HEED) is an efficient routing protocol in recent years. This paper proposes IHCBW with interval type 2 fuzzy logic system‐based HEED (IIT2FLS‐HEED) method. We used the combination of cuckoo search (CS) and improved black widow optimization (IBWO) algorithms (IHCBW) for the selection of optimal residual energy selection. The optimal cluster heads (CHs) are chosen with the help of the interval type 2 fuzzy logic system (IT2FLS). Experimentally, the NS2 software handles the entire proposed work and its performance is evaluated with different kinds of performance evaluation. Moreover, 20 benchmark functions are used to validate the performance of the IHCBW algorithm. Finally, the proposed IIT2FLS‐HEED demonstrates better performance results in terms of homogenous, second, and third stage heterogeneous WSN.

Performance Improvements of AODV by Black Hole Attack Detection Using IDS and Digital Signature

In mobile ad hoc networks (MANETs), mobile devices connect with other devices wirelessly, where there is no central administration. They are prone to different types of attacks such as the black hole, insider, gray hole, wormhole, faulty node, and packet drop, which considerably interrupt to perform secure communication. This paper has implemented the denial‐of‐service attacks like black hole attacks on general‐purpose ad hoc on‐demand distance vector (AODV) protocol. It uses three approaches: normal AODV, black hole AODV (BH_AODV), and detected black hole AODV (D_BH_AODV), wherein we observe that black holes acutely degrade the performance of networks. We have detected the black hole attacks within the networks using two techniques: (1) intrusion detection system (IDS) and (2) encryption technique (digital signature) with the concept of prevention. Moreover, normal AODV, BH_AODV, and D_BH_AODV protocols are investigated for various quality of service (QoS) parameters, i.e., packet delivery ratio (PDR), delay, and overhead with varying the number of nodes, packet sizes, and simulation times. The NS2 software has been used as a simulation tool to simulate existing network topologies, but it does not contain any mechanism to simulate malicious protocols by itself; therefore, we have developed and implemented a D_BH_AODV routing protocol. The outcomes show that the proposed D_BH_AODV approach for the PDR value delivers around 40 to 50% for varying nodes and packets. In contrast, the delay decreases from 300 to 100 ms and 150 to 50 ms with an increase in the number of nodes and packets, respectively. Furthermore, the overhead changes from 1 to 3 for various nodes and packet values. The outcome of this research proves that the black hole attack degrades the overall performance of the network, while the D_BH_AODV enhances the QoS performance since it detects the black hole nodes and avoids them to establish the communication between nodes.

Nelder Mead-Based Spider Monkey Optimization for Optimal Power and Channel Allocation in MANET

The Mobile Ad-hoc Network (MANET) includes both the optimal allocation of shared channels and power in a network. Hence, obtaining the trade-off between energy consumption and delay is the major challenge. The source-constrained and maximizing lifetime of the unreliable wireless network includes optimal power allocation. We proposed an Integrated Spider Monkey Optimization Algorithm (ISMOA) for the minimization of energy consumption and the enhancement of throughput in MANET. The Nelder Mead Model (NMM) is used to improve the performance of the local leader stage in the spider monkey optimization algorithm. In this work, the novel approach is used to improve the performance of total energy consumption, throughput, and delay. The experimental works are executed in NS-2 software. The experimental results demonstrate the low delay, energy consumption with high throughput performance. Moreover, the proposed method outperforms the optimal performance compared to state-of-the-art methods.

Hybrid Optimal Energy Management for Clustering in Wireless Sensor Network

Energy optimization is the most important to improve the lifetime of a wireless sensor network. Nodes in sensor networks require to have an optimal mechanism for utilizing energy A new technique named Hybrid Optimization Algorithm, presented in this paper, is based on Lagrangian relaxation and entropy for reducing the energy consumption. The proposed model helps to maintain multi-hop connectivity with dynamic action. The nodes are allowed to communicate based on energy, bandwidth, neighbor connectivity, hop count, to maintain high QoS energy parameters. The simulations are in NS2 software. The proposed approach evaluates total consumed energy, average remaining energy, packets received rate, drop rate, normalized routing overhead, delay, throughput, goodput, jitter, and network lifetime. The comparison results show that the nodes' lifetime improved with a Hybrid Optimal Based Cluster Formation (HOBCF) algorithm.

An energy-aware clustering and two-level routing method in wireless sensor networks

Wireless sensor networks (WSN) are consisted of several sensor nodes scattered in an area to gather data from their ambient environment and send it to base station (BS). The energy of nodes in WSNs is limited. One of the most significant issues in WSNs is reducing the energy consumption of nodes, which leads to increased network lifetime. One method to reduce energy consumption in WSNs is energy-efficient routing. In energy-efficient routing, gathered data is sent to the sink in a way to save the energy of nodes. This paper proposed a cluster-based two-level routing method. In the proposed method, we seek to improve packet delivery rate and reduce energy consumption through clustering, selecting backup cluster head (BCH), layering cluster heads (CH), and dividing each cluster into four sections. The method is consisted of two phases. In the first phase, CHs and BCHs are selected, and nodes are clustered based on their residual energy, distance to BS, and centrality. To perform intra-cluster routing, each cluster is divided into four sections so that nodes directly deliver their data to CH or through the most proper node in their sections. To perform inter-cluster routing, CHs are layered based on their distance to BS. Since CHs are layered, the source CH selects the next hop from CHs in the upper layer based on their residual energy and distance to BS. The proposed method has been simulated by NS-2 software and compared with CFPT (Yarinezhad and Hashemi in J Syst Softw 155:145–161, 2019), FBCFP (Thangaramya et al. in Comput Netw 151:211–223, 2019) and DFCR (Azharuddin et al. in Comput Electr Eng, 41:177–190, 2015) methods. The results reveal that the proposed method leads to reduced end-to-end delay, number of total hops, energy consumption as well as increased packet delivery rate and network lifetime.