Black Hole Attacks on MANETs: Analysis and Prevention

Wireless network technically, refers to the category of network in which communication is carried out without using wires. In modern era wireless network has great importance because the communication is taking place with the use of radio waves. Thus, the use of ad-hoc network starts yielding a great importance in variety of applications. The certain research work is carried out in this particular field. MANET is a constructed from various mobility in the form of mobile nodes and anytime without any need of fixed infrastructure. MANET can be made on fly due to lack of fixed infrastructure. MANET is numerous threats types of attacks due to dynamic changing topologies and wireless medium. Security of the MANET becomes one of the challenging tasks. Black hole attacks is the main type of attack that are possible in MANET. Black hole node not forward any data packets to the neighbour node instead it drops all the data packets. Black hole attacks are bit hard to detect due to lack of centralized access. This research work concentrates to enhance the security of MANET by identifying and blocking black hole assaults from occurring. A reactive routing system such as Ad-Hoc on Demand Distance Vector has previously been used to address security problems in the MANET (AODV). Various attack types were investigated, and the consequences of these assaults were detailed by describing how MANET performance was disrupted. Network Simulator 3 (NS3) is used for the simulation process.

Is High Viscosity a Requirement for Fracturing Fluids?

Uniformly distributing proppant inside fractures with low damage on fracture conductivity is the most important index of successful fracturing fluids. However, due to very low proppant suspension capacity of slickwater and friction reducers fracturing fluids and longer fracture closure time in nano & pico darcies formations, proppants settles quickly and accumulates near wellbore resulting in worse-than-expected well performance, as the fracture full capacity is not open and contributing to production. Traditionally, cross-linked polymer fluid systems are capable to suspend and transport high loading of proppants into a hydraulically generated fracture. Nevertheless, amount of unbroken cross-linked polymers is usually left in fractures causing damage to fracture proppant conductivity, depending on polymer loading. To mitigate these challenges, a low viscosity-engineered-fluid with excellent proppantcarrying capacity and suspension-in excess of 30 hours at static formation temperature conditions - has been designed, enhancing proppant placement and distribution within developed fractures, with a 98% plus retained conductivity. In this work experimental and numerical tests are presented together with the path followed in developing a network of packed structures from polymer associations providing low viscosity and maximum proppant suspension. Challenges encountered during field injection with friction are discussed together with the problem understanding characterized via extensive friction loop tests. Suspension tests performed with up to 8-10 PPA of proppant concentration at temperature conditions are shared, together with slot tests performed. Physics-based model results from a 3D Discrete Fracture Network simulator that computes viscosity, and elastic parameters based on shear rate, allows to estimate pressure losses along the flow path from surface lines, tubular goods, perforations, and fracture. This work will demonstrate the advanced capabilities and performance of the engineered fluid over conventional fracturing fluids and its benefits. Additionally, this paper will present field injection pressure analysis performed during the development of this fluid, together with a field case including production results after 8 months of treatment. The field case production decline observed after fracture treatment demonstrates the value of this system in sustaining well production and adding additional reserves.

Intrusion Detection Based on Generative Adversarial Network of Reinforcement Learning Strategy for Wireless Sensor Networks

Due to the wireless nature of wireless sensor networks (WSN), the network can be deployed in most of the unattended environment, which makes the networks more vulnerable for attackers who may listen to the traffic and inject their own nodes in the sensor network. In our work, we research on a novel machine learning algorithm on intrusion detection based on reinforcement learning (RL) strategy using generative adversarial network (GAN) for WSN which can automatically detect intrusion or malicious attacks into the network. We combine Actor-Critic Algorithm in RL with GAN in a simulated WSN. The GAN is employed as part of RL environment to generate fake data with possible attacks, which is similar to the real data generated by the sensor networks. Its main aim is to confuse the adversarial network into differentiating between the real and fake data with possible attacks. The results that is from the experiments are based on environment of GAN and Network Simulator 3 (NS3) illustrate that Actor-Critic&GAN algorithm enhances security of the simulated WSN by protecting the networks data against adversaries and improves on the accuracy of the detection.

Reliable Fault Tolerant-Based Multipath Routing Model for Industrial Wireless Control Systems

Communication in industrial wireless networks necessitates reliability and precision. Besides, the existence of interference or traffic in the network must not affect the estimated network properties. Therefore, data packets have to be sent within a certain time frame and over a reliable connection. However, the working scenarios and the characteristics of the network itself make it vulnerable to node or link faults, which impact the transmission reliability and overall performance. This article aims to introduce a developed multipath routing model, which leads to cost-effective planning, low latency and high reliability of industrial wireless mesh networks, such as the WirelessHART networks. The multipath routing model has three primary paths, and each path has a backup node. The backup node stores the data transmitted by the parent node to grant communication continuity when primary nodes fail. The multipath routing model is developed based on optimal network planning and deployment algorithm. Simulations were conducted on a WirelessHART simulator using Network Simulator (NS2). The performance of the developed model is compared with the state-of-the-art. The obtained results reveal a significant reduction in the average network latency, low power consumption, better improvement in expected network lifetime, and enhanced packet delivery ratio which improve network reliability.

OMNeT++ Framework for Simulation of Centralized and Distributed Algorithms in Multi-Hop Networks

Theoretical applications and practical network algorithms are not very cost-effective, and most of the algorithms in the commercial market are implemented in the cutting-edge devices. Open-source network simulators have gained importance in recent years due to the necessity to implement network algorithms in more realistic scenarios with reasonable costs, especially for educational purposes and scientific researches. Although there have been various simulation tools, NS2 and NS3, OMNeT++ is more suitable to demonstrate network algorithms because it is convenient for the model establishment, modularization, expandability, etc. OMNeT++ network simulator is selected as a testbed in order to verify the correctness of the network algorithms. The study focuses on the algorithms based on centralized and distributed approaches for multi-hop networks in OMNeT++. Two network algorithms, the shortest path algorithm and flooding-based asynchronous spanning tree algorithm, were examined in OMNeT++. The implementation, analysis, and visualization of these algorithms have also been addressed.

Review of Custom Grids for Updated Vehicles on VANET Simulators

VANET deployment and testing is time-consuming and costly. Simulation is a handy and less expensive alternative to real implementation as a workaround. It is required to develop accurate models in order to receive excellent results from a VANET simulation, which difficult operation owes to the complexity of the VANET infrastructure (for example, simulators have to model the navigation models and communication protocols). The network and navigation components, which are the building blocks of contemporary VANET simulators, are described in this section. Simulators are a useful tool for testing VANETs at a minimal cost and without endangering users. However, in order to be helpful and convey trustworthy findings, simulators must be able to simulate new technologies that enter the VANET and enable safety and security procedures. To put it another way, if simulation is a good tool for VANET development it should be enhanced. VANET simulators have been the subject of research since early 2010 [1-4]. They analyze the correctness of VANET's numerous tools like a navigation simulator and network simulator, as well as how these building blocks are connected. The introduction of new network technologies such as 5G, SDN, edge computing, and VANET research as a result of investments in autonomous cars is forcing VANET simulators to re-evaluate their support for these new capabilities. We present an updated evaluation of VANET simulators in this post, highlighting their key features and current support for emerging technologies.

A Novel Optimal Robotized Parking System Using Advanced Wireless Sensor Network

This article addresses the importance of parking system which makes the movement of moving vehicles to be unrestricted thus providing integration between hominid classification and sensing systems. If two distinct systems are combined, then all the vehicles can monitor the parking space, and they can directly move towards the destination end within short span of time. In addition for this type of establishment, rapidity of transportation vehicles is calculated with error minimization technique where all technical hitches will be avoided by sustaining the user constraints. Further, to solve the designed user constraints, a nonlinear optimization which is termed as machine learning algorithm is introduced for avoiding high loss during packet transmission technique, and percentage of efficiency is analyzed using simulated results with network simulator (NS2). Moreover, from simulated results, it is substantiated that the projected method on automatic parking of vehicles provides high efficient operation, and even cost of installation is reduced.

Three Layered Architecture for Driver Behavior Analysis and Personalized Assistance with Alert Message Dissemination in 5G Envisioned Fog-IoCV

The Internet of connected vehicles (IoCV) has made people more comfortable and safer while driving vehicles. This technology has made it possible to reduce road casualties; however, increased traffic and uncertainties in environments seem to be limitations to improving the safety of environments. In this paper, driver behavior is analyzed to provide personalized assistance and to alert surrounding vehicles in case of emergencies. The processes involved in this research are as follows. (i) Initially, the vehicles in an environment are clustered to reduce the complexity in analyzing a large number of vehicles. Multi-criterion-based hierarchical correlation clustering (MCB-HCC) is performed to dynamically cluster vehicles. Vehicular motion is detected by edge-assisted road side units (E-RSUs) by using an attention-based residual neural network (AttResNet). (ii) Driver behavior is analyzed based on the physiological parameters of drivers, vehicle on-board parameters, and environmental parameters, and driver behavior is classified into different classes by implementing a refined asynchronous advantage actor critic (RA3C) algorithm for assistance generation. (iii) If the driver’s current state is found to be an emergency state, an alert message is disseminated to the surrounding vehicles in that area and to the neighboring areas based on traffic flow by using jelly fish search optimization (JSO). If a neighboring area does not have a fog node, a virtual fog node is deployed by executing a constraint-based quantum entropy function to disseminate alert messages at ultra-low latency. (iv) Personalized assistance is provided to the driver based on behavior analysis to assist the driver by using a multi-attribute utility model, thereby preventing road accidents. The proposed driver behavior analysis and personalized assistance model are experimented on with the Network Simulator 3.26 tool, and performance was evaluated in terms of prediction error, number of alerts, number of risk maneuvers, accuracy, latency, energy consumption, false alarm rate, safety score, and alert-message dissemination efficiency.

An Efficient Data-Balancing Cyber-Physical System Paradigm for Quality-of-Service (QoS) Provision over Fog Computing

Cyber-physical systems (CPSs) have greatly contributed to many applications. A CPS is capable of integrating physical and computational capabilities to interact with individuals through various new modalities. However, there is a need for such a paradigm to focus on the human central nervous system to provide faster data access. This paper introduces the CPS paradigm that consists of CPS enabled human brain monitoring (CPS-HBM) and efficient data-balancing for CPS (EDB-CPS). The CPS-HBM provides architectural support to make an efficient and secure transfer and storage of the sensed data over fog cloud computing. The CPS-HBM consists of four components: physical domain and data processing (PDDP), brain sensor network (BSN), Service-oriented architecture (SOA), and data management domain (DMD). The EDB-CPS module aims to balance data flow for obtaining better throughput and lower hop-to-hop delay. The EDB-CPS accomplishes the goal by employing three processes: A node advertisement (NA), A node selection and recruitment (NSR), and optimal distance determination with mid-point (ODDMP). The processes of the EDB-CPS are performed on the PDDP of the CPS-HBM module. Thus, to determine the validity of EDB-CPS, the paradigm was programmed with C++ and implemented on a network simulator-3 (NS3). Finally, the performance of the proposed EDB-CPS was compared with state-of-the-art methods in terms of hop-to-hop delay and throughput. The proposed EDB-CPS produced better throughput between 443.2–445.2 KB/s and 0.05–0.078 ms hop-to-hop delay.