Minimize Packet Loss Research Articles

Probit Cryptographic Blockchain for Secure Data Transmission in Intelligent Transportation Systems

<p>To address the current security challenges, Digital Twin (DT) models and strategies are to be applied to improve security, privacy, and safety in intelligent transportation systems. However, the existing algorithm was failed to address the security and privacy issues for data between the vehicles. To enhance the security of data transmission, a novel Probit Regressive Davis Mayer Kupyna Cryptographic Hash Blockchain (PRDMKCHB) technique is proposed. Initially, the source vehicle finds the nearest vehicle to transmit the data based on the trust value using the probit regression function. After finding the neighboring nodes, the Blockchain is constructed to improve the security of data transmission from the source to the destination. The Blockchain uses the Kupyna Cryptography to generate the hash value for each data. Davis Mayer compression function is to improve the security of data delivery and to minimize packet loss. The comprehensive simulation is carried out to validate the performance of the proposed PRDMKCHB technique and existing Blockchain technology in terms of packet delivery ratio, packet loss rate, and execution time. Simulation results show the performance improvement of the proposed PRDMKCHB technique compared to the previous Blockchain technology in terms of higher packet delivery ratio, minimum packet loss, and execution time with respect to the number of data packets.</p> <p> </p>

Energy Management in Mobile Ad Hoc Networks with Innovative Protocol TDQR CNFPQR and Bird Optimization Technique

It is impossible to stress the importance of a Dynamic Wireless Ad Hoc Network (MANET) for message path dependability and permanence. Data sharing is a vital activity in a mobile ad hoc network because packet loss occurs when nodes fail or are missing during data transfer. When a packet is lost, it can be subject to various infractions. To overcome this problem, a new algorithm was created known as TDQR CNFPQR (Trigger-Based Distributed QoS Clustered Node Failure Prediction QoS) Protocol. The MBO method analyses node state to minimize packet losses. In comparison to existing methodologies, our suggested methodology uses less energy, delivers more packets, and has a lower routing burden and higher end-to-end latency. Mobile station users can receive stationary network services offered via numerous jump links even if the network is not immediately available to them. Because wireless networks have limited route capacity, it is critical to react to user requests as rapidly as feasible. Because network nodes have limited energy resources, it is critical to spend as little energy as possible when transferring data across the network. Ad hoc wireless networks are hampered by limited battery power, making energy management a critical concern. Knowledge-based algorithm rule analyses the node's monitoring capabilities at the same time. We can then predict node failure, node longevity, and data exchange along the ideal path without packet loss using Migrating Birds Optimization (MBO).

Self-healing and optimal fault tolerant routing in wireless sensor networks using genetical swarm optimization

A wireless sensor network (WSN) is used in area monitoring, surveillance, virtual reality, artificial intelligence, etc. The interaction between sensor nodes (SNs) and base station (BS) play a major role in WSN. SNs use more energy to transmit data, and the occurrence of faults in these nodes may lead to complete network failure. To ensure enhanced network performance, the incorporation of an efficient fault detection mechanism becomes essential in WSN. The major aim of the work is to improve the self-healing capacity of the network. To meet the above requirement, a fault-tolerant routing path identification with genetical swarm optimization (FTGSO) is introduced in this work. Genetical swarm optimization (GSO) is the integration of the two optimizations like Genetic Algorithm (GA) and Particle swarm optimization (PSO). The cluster head (CH) selection carried out on the basis of residual energy, coverage, communication cost and proximity. Further, a fault-free routing path is introduced by GSO, and a self-healing method is employed to resolve any network connectivity issues and resume the normal system operation. The analysis and simulation outcomes are compared with other optimization algorithms to verify the effectiveness. The evaluation results verify the enhanced performance of the introduced scheme with a higher PDR (packet delivery ratio) of 96.8%, lower energy consumption of 0.19 J with a minimum packet loss ratio of 3.2% and 30 ms of E2E (end-to-end delay) compared to other existing routing protocols. Also, the performance of the proposed method is compared on the basis of E2E, energy efficiency, (PLR) packet loss ratio and PDR.

Energy Aware Talented Clustering with Compressive Sensing (TCCS) for Wireless Sensor Networks

Wireless sensor networks (WSNs) are networks of sensor nodes that interact wirelessly to gather information about the surrounding environment. Nodes are often low-powered and dispersed in an ad hoc, decentralized manner. Although WSNs have gained in popularity, they still have several serious shortcomings, like limited battery life and bandwidth. In this paper, the cluster head (CH) selection, the Compressive Sensing (CS) theory, the Connection-based Decentralized Clustering (CDC), the relay node selection, and the Multi Objective Genetic Algorithm (MOGA)are all taken into account The initial stage provided a theoretical revision to the concepts of network construction, compressive sensing, and MOGA, which impacted the improvement of network lifetime. In the second stage developed a novel model such as Energy Aware Talented Clustering with Compressive Sensing (TCCS) for the sensor network. This approach considers increasing longevity but also raises the network's overall quality of service (QoS). In the analysis, the TCCS model is applied to both the centralized and distributed networks and compared with the existing methods. When compared to the previous methods, the simulation results show that the proposed work performs better in terms of the calculation of maximum packet delivery ratio of 93.93 percent, minimum energy consumption of 8.04J, maximum energy efficiency of 91.04 percent, maximum network throughput of 465.51kbps, minimum packet loss of 282 packets, and minimum delay of 63.82 msec.

Fast Finite Frame Length IRSA Optimization Based on Bayesian Optimization

Simplified packet reception models such as collision model are usually adopted for optimizing irregular repetition slotted ALOHA (IRSA), which may lead to performance penalty due to its poor accuracy. In this letter, we consider the problem of online IRSA optimization in the finite frame length regime using a more accurate reception model. In order to allow a fast optimization of IRSA, we present a new method based on Bayesian optimization with Gaussian processes. Our method finds the optimal user degree distribution minimizing packet loss rate (PLR) in an iterative way. At each iteration, a surrogate is built to model the unknown IRSA PLR performance function using Gaussian process (GP) regression, and then an acquisition function defined from the surrogate is utilized to choose the next degree distribution, whose PLR is evaluated by the more accurate model. The proposed method is able to infer the PLR of an untested degree distribution, thus converging quickly within only tens of iterations. Simulation results show that IRSA schemes optimized using our method can achieve lower PLR compared with those optimized based on the collision model.

A Routing Delay Predication Based on Packet Loss and Explicit Delay Acknowledgement for Congestion Control in MANET

In Mobile Ad hoc Networks congestion control and prevention are demanding because of network node mobility and dynamic topology. Congestion occurs primarily due to the large traffic volume in the case of data flow because the rate of inflow of data traffic is higher than the rate of data packets on the node. This alteration in sending rate results in routing delays and low throughput. The Rate control is a significant concern in streaming applications, especially in wireless networks. The TCP friendly rate control method is extensively recognized as a rate control mechanism for wired networks, which is effective in minimizing packet loss (PL) in the event of congestion. In this paper, we propose a routing delay prediction based on PL and Explicit Delay Acknowledgement (EDA) mechanism for data rate and congestion control in MANET to control data rate to minimize the loss of packets and improve the throughput. The experiment is performed over a reactive routing protocol to reduce the packet loss, jitter, and improvisation of throughput.

Towards the optimal orchestration of steerable mmWave backhaul reconfiguration

Future generations of mobile networks will require increased backhaul capacity to connect a massive amount of small cells (SCs) to the network. Since having an optical connection to each SC might be infeasible, mmWave links are an interesting alternative due to their large available bandwidth. An advantage of a wireless backhaul is that the topology can be reconfigured to adapt to changing traffic demands, new operator policies, or to rapidly overcome network failures. In this work, we investigate the problem of orchestrating the reconfiguration of mmWave wireless backhaul networks with mechanically steerable antennas assuming green backhaul operation where nodes are turned off when not in use. The orchestration involves scheduling and coordinating the powering on/off of nodes, the rotation of antennas to achieve alignment for link establishment, and setting up and tearing down links to minimize packet loss during the reconfiguration. We model the problem as a Mixed Integer Linear Program (MILP) for optimal orchestration and propose a sub-optimal reduced MILP for larger instances. Numerical results for different topologies using a realistic traffic trace indicate that optimizing reconfiguration orchestration can significantly reduce packet loss in comparison to a straightforward reconfiguration approach, enabling a smooth transition between target mmWave backhaul topologies.

Gray-Hole Attack Minimization in IoMT with 5G Based D2D Networks

Reliable transmission is vital to the success of the next generation of communications technologies and Fifth Generation (5G) networks. Many sensitive applications, such as eHealth and medical services, can benefit from a 5G network. The Internet of Medical Things (IoMT) is a new field that fosters the maintenance of trust among various IoMT Device to Device (D2D) modern technologies. In IoMT the medical devices have to be connected through a wireless network and constantly needs to be self-configured to provide consistent and efficient data transmission. The medical devices need to be connected with sophisticated protocols and architecture to handle the synergy of the monitoring devices. Today, one of the commonly used algorithms in D2D communication is the Optimized Link State Routing protocol (OLSR). The OLSR is considerably good at effectively utilizing the bandwidth and reserving the paths. One of the major attack against the OLSR is the Node isolation attack, also known as the Gray hole denial of service attack. The Gray hole attack exploits the vulnerabilities present with sharing the topological information of the network. The attackers may use this topological information to maliciously disconnect the target nodes from the existing network and stops rendering the communication services to the victim node. Hence, considering the sensitivity and security concerns of the data used in e-Health applications, these types of attacks must be detected and disabled proactively. In this work, a novel Node Authentication (NA) with OLSR is proposed. The simulation experiments illustrated that the proposed protocol has an excellent Packet Delivery Ratio, minimal End-End delay, and minimal Packet loss when compared to the Ad-hoc On-Demand Distance Victor (AODV) protocol and the proposed authentication scheme was able to protect the OLSR protocol from a node isolation attack.

An Efficient Path Planning Strategy in Mobile Sink Wireless Sensor Networks

Wireless sensor networks (WSNs) are considered the backbone of the Internet of Things (IoT), which enables sensor nodes (SNs) to achieve applications similarly to human intelligence. However, integrating a WSN with the IoT is challenging and causes issues that require careful exploration. Prolonging the lifetime of a network through appropriately utilising energy consumption is among the essential challenges due to the limited resources of SNs. Thus, recent research has examined mobile sinks (MSs), which have been introduced to improve the overall efficiency of WSNs. MSs bear the burden of data collection instead of consuming energy at the routeing by SNs. In a network, some areas generate more data through SNs that contain frequent, urgent messages. These messages carry sensitive data that must be delivered immediately to user applications. Collecting such messages via MSs, especially on a large scale, increases delays, which are not tolerable in some real applications. This issue has not been studied much. Thus, the present study utilises the advantages of the priority parameter to concentrate on these areas and proposes a new model named ‘energy efficient path planning of MS-based area priority’ (EEPP-BAP). This method involves non-urgent and urgent messages. It is comprised of four procedures. Initially, after SNs are distributed randomly in a wide monitoring field, the monitoring field is partitioned into equal zones according to priority, either differently or equally. Next is clustering based on the cluster head (CH) selected to perform the particle swarm optimisation algorithm (PSO). Then, the MS moves first to the zones with higher priority and less distance to perform the brain storm optimisation algorithm. Finally, for urgent messages from the other zones at which the MS continues, the proposed approach establishes a routeing technique using multi-hop communication based on the MS position and using PSO. The proposed solution is aimed at delivering urgent messages to MSs free of latency and with minimal packet loss. The simulation results proved that the EEPP-BAP method can improve network performance compared with other models based on different parameters that have been used to construct the controlled movement of MSs in large-scale environments involving urgent messages. The proposed method increased the average lifetime of SNs to 206.6% on average, reduced the average end-to-end delay to 7.1%, and increased the average packet delivery ratio to 36.9%.

Adaptive Quality-of-Service Allocation Scheme for Improving Video Quality over a Wireless Network

The need to ensure the quality of video streaming transmitted over wireless networks is growing every day. Video streaming is typically used for applications that are sensitive to poor quality of service (QoS) due to insufficient bandwidth, packet loss, or delay. These challenges hurt video streaming quality since they affect throughput and packet delivery of the transmitted video. To achieve better video streaming quality, throughput must be high, with minimal packet delay and loss ratios. A current study, however, found that the adoption of the adaptive multiple TCP connections (AM-TCP), as a transport layer protocol, improves the quality of video streaming by increasing throughput and lowering packet delay and loss on high QoS wireless networks. The main objective of this study is to develop a Quality of Service (QoS) method for enhancing video streaming quality over wireless networks. For that, this paper proposes a bandwidth aggregation adaptive multiple TCP-connection (BAM-TCP) scheme to enhance the video streaming quality. BAM-TCP combines AM-TCP with a bandwidth aggregation (BAG) method to aggregate bandwidth from numerous connections. Simulation experiments demonstrate that the BAM-TCP method enhances throughput while minimizing packet loss ratio and end-to-end delay.

SWAP: Smart WAter Protocol for the Irrigation of Urban Gardens in Smart Cities

The implementation of Smart City projects has experimented a surge in the recent years with examples such as Smart Santander or Barcelona Smart City. Among the different domains that comprise the Smart City, water management has a great importance, more so in areas with water scarcity. Furthermore, water from different sources such as treated sewage water or collected rainwater can be utilized to address water needs where the use of potable water is not necessary. Therefore, the implementation of smart systems for the irrigation of urban gardens and other urban vegetated areas is of great importance to manage both water needs and the available resources. In this paper, a communication protocol for smart irrigation systems designed within the context of the Smart City is presented. The protocol enables the communication among devices with both LoRa and WiFi wireless technologies. Tests were performed with low-cost devices in an urban area. The results demonstrate the good performance of the proposal, obtaining the minimum packet loss by adding a 500 ms delay at the CH node when transmitting messages from WiFi to LoRa and vice versa.

Applying switching and multiple access model for reducing packet loss and network overheads in watm

As an effectual simple wireless equivalent created in the telecommunications (telephone) industry, Wireless Asynchronous Transfer Mode (WATM) is utilized to stream unified traffics like video, data, and voice data. In the asynchronous data transfer mode, voice data transfer a packet with the same medium, and data share the networks and burst data. Effective WATM data transmission requires an extensive array of designs, techniques used for control, and simulation methodologies. The congestion of the network is among the key challenges that lower the entire WATM performance during this procedure, in addition to the delay in cell and the overload of traffic. The congestions cause cell loss, and it requires expensive switches compared to the LAN. Consequently, in this current study, the application of an effectual switching model together with a control mechanism that possesses multiple accesses is employed. The multiple access process and switching model are utilized to establish an effective data sharing process with minimum complexity. The switching model uses the synchronous inputs and output ports with buffering to ensure the data sharing process. The traffic in the network is decreased, and the loss of packets in the cells is efficiently kept to a minimum by the proposed technique. The system being discussed is employed through the utilization of software employed using OPNET 10.5 simulation, with the valuation of the WATM along with the investigational outcomes accordingly. The system's efficiency is assessed by throughput, latency, cell loss probability value (CLP), overhead network, and packet loss. Thus, the system ensures the minimum packet loss (0.1 %) and high data transmission rate (96.6 %)

RM-ADR: Resource Management Adaptive Data Rate for Mobile Application in LoRaWAN.

LoRaWAN is renowned and a mostly supported technology for the Internet of Things, using an energy-efficient Adaptive Data Rate (ADR) to allocate resources (e.g., Spreading Factor (SF)) and Transmit Power (TP) to a large number of End Devices (EDs). When these EDs are mobile, the fixed SF allocation is not efficient owing to the sudden changes caused in the link conditions between the ED and the gateway. As a result of this situation, significant packet loss occurs, increasing the retransmissions from EDs. Therefore, we propose a Resource Management ADR (RM-ADR) at both ED and Network Sides (NS) by considering the packet transmission information and received power to address this issue. Through simulation results, RM-ADR showed improved performance compared to the state-of-the-art ADR techniques. The findings indicate a faster convergence time by minimizing packet loss ratio and retransmission in a mobile LoRaWAN network environment.

Optimizing Energy Consumption in IoT-Based Scalable Wireless Sensor Networks

In recent era of IoT, energy ingesting by sensor nodes in Wireless Sensor Networks (WSN) is one of the key challenges. It is decisive to diminish energy ingesting due to restricted battery lifespan of sensor nodes, Objective of this research is to develop efficient routing protocol/algorithm in IoT based scenario to enhance network performance with QoS parameters. Therefore, keeping this objective in mind, a QoS based Optimized Energy Clustering Routing (QOECR) protocol for IoT based WSN is proposed and evaluated. QOECR discovers optimal path for sink node and provides better selection for sub-sink nodes. Simulation has been done in MATLAB to assess the performance of QOECR with pre-existing routing protocols. Simulation outcomes represent that QOECR reduces E2E delay 30%-35%, enhances throughput 25%-30%, minimizes energy consumption 35%-40%, minimizes packet loss 28%-32%, improves PDR and prolongs network lifetime 32%-38% than CBCCP, HCSM and ZEAL routing protocols.

Optimizing Energy Consumption in IoT based Scalable Wireless Sensor Networks

In recent era of IoT, energy ingesting by sensor nodes in Wireless Sensor Networks (WSN) is one of the key challenges. It is decisive to diminish energy ingesting due to restricted battery lifespan of sensor nodes, Objective of this research is to develop efficient routing protocol/algorithm in IoT based scenario to enhance network performance with QoS parameters. Therefore, keeping this objective in mind, a QoS based Optimized Energy Clustering Routing (QOECR) protocol for IoT based WSN is proposed and evaluated. QOECR discovers optimal path for sink node and provides better selection for sub-sink nodes. Simulation has been done in MATLAB to assess the performance of QOECR with pre-existing routing protocols. Simulation outcomes represent that QOECR reduces E2E delay 30%-35%, enhances throughput 25%-30%, minimizes energy consumption 35%-40%, minimizes packet loss 28%-32%, improves PDR and prolongs network lifetime 32%-38% than CBCCP, HCSM and ZEAL routing protocols.

Block chain-based access control protocol in Internet of Drones

The Internet of Drones (IoD) is an emerging domain due to its capability of being deployed in several domains. The drones in IoD are capable of exploring the platform and transfer commodities with embedded sensors. However, the data accumulated by drone sensors face privacy and security issues due to advanced technologies. This paper devises a blockchain-based access control scheme for initiating secure communication among the drones in IoD. The system has four different entities that involve the Drone, server, user, and control room. The proposed Blockchain-based access control scheme involves two phases: the authentication and access control phases. The authentication phase is performed considering sender drone credentials, and the access control phase is done using four methods. In the access control phase, four kinds of access control mechanisms are considered: Drone to drone access control, Drone to server access control, Emergency access control if drone failure and Control set up with blockchain technology. Both the communicating entities can establish the secret key for secure communication at the end of access control. The proposed Blockchain-based access control scheme provided superior performance concerning classical methods with a minimal end-to-end delay of 0.870sec, a minimal packet loss rate of 2%, and maximal throughput of 70.493bps.

An intellectual procurement innovation of smart grid power system with wireless communication networks based on machine learning

The phased array antenna is one of the most significant applications in fifth-generation mobile networks. It is one of the most important applications in fifth-generation networks. An electric power source that powers the whole application, including the antenna's root, is required. Even with the most outstanding design, if the programme does not have a sound power supply system with minimal packet loss and can't Path find performance, it will be rendered ineffective. When seen from the perspective of the multiplex information, Machine Learning comprises a communication network based on the Internet that transmits information to the control centre via the objects (IOT). To put it another way, the proposed communication infrastructure, via the provision of, and the chance micro-grid state to collect, analyze, and two-way communication link control information, offers the chance to resolve the voltage regulation issues. This cutting-edge communication infrastructure, as well as a suggested state estimation filter focused on improving speed and performance in renewable energy production, are both examples of creative communication infrastructure. Current research is focused on analyzing and enumerating a range of energy abundances in the context of smart grids, which are now in their fifth generation. Rather than concentrating on the future development plan, which should be a problem of illusion, it should concentrate on the composition of the future potential of smart grid communications framework. An in-depth investigation to give evidence to the Machine learning will help intelligent networks in the future conduct a thorough evaluation.

Fuzzy Like Pid Controller Based on Sso Design for Congestion Avoidance in Internet Router

today The topic of contention is the quality of computer network service. Efficient data handling is important. Each router offers a buffer space where packets can be held before being sent until they are processed. The theory of packet congestion control is TCP (Transmission Control Protocol) .(AQM) is a mechanism proposed for gateways to improve congestion management. AQM (active queue management) is a crucial to minimize packet loss in TCP/IP networks and improving network efficiency. This paper offers a hybrid intelligent (PID) with type1 fuzzy logic controller which is designed to decrease network congestion. As a router (AQM), social spider optimization (SSO) is used to tune the control parameters used to reduce queue size error. The designed controller based on SSO algorithm provides a good tracking performance for AQM desired value.The observational findings indicated a high-performance increase in the proposed process. In MATLAB(R2020a), a simulation of a linearized TCP/AQM model is presented. NS2 is used to perform verification for the fuzzy logic controllers for the nonlinear TCP/AQM model under a more practical simulation and to analyze and examine network behavior in different scenarios. Index Terms—AQM controller, congestion control, fuzzy logic control, PID Controller; SSO.

An adaptive QoS supportive approach for user based services using Krill Herd Approach over Internet of Things (KHAI)

The demand for a providing QoS adaptive routing over IoT networks is always a challenge among current research community. This research work KHAI proposes a framework for QoS-adaptive routing approach, which incorporates Krill Herd optimization model over IoT network. Variable QoS user preference and handling differential service types over a scalable IoT network shows that challenge for designing an adaptive QoS is a must. Research survey suggest that major works have been carried out on bandwidth appreciable services and route management approaches. Hence QoS adaptive user defined services, which adapt to variable service priority levels based on user demand and network resource utilization is proposed in this research work. The performance analysis of proposed approach shows an improved throughput of 97.51 Mbps and minimal packet loss of 37.29% over a session in comparison to traditional computational approaches. Considering large scale of interconnected IoT devices, proposed approach delivers near optimal solution of throughput and adaptive utilization of network resources.

WITHDRAWN: Energy efficient node Positioned Learning Automaton and Multilateration data delivery in MANET

Abstract Mobile Ad Hoc network (MANET) is a self-organizing and battery constrained network. The design of energy efficient routing has been an active research area. In conventional routing algorithms, the node positioning is varying with time, constrained energy does not ensure route firmness. Moreover, with node movement it becomes very hard to predict and ensuring significant data delivery in MANET is another major concern. To resolve these issues, this paper proposes an energy efficient routing depends on node positioning and Learning Automaton for MANET. Initially, a node firmness model is constructed and on that basis, reward and penalty function are designed according to optimal or non-optimal route identification. A node positioned energy efficient mechanism is constructed for election of accessible routes and manifests convergence of Node Positioned Learning Automaton Energy-efficient Routing algorithm. Next, with the identified energy-efficient optimal route, node with minimal load is selected by employing Statistically-evaluated Load balancing algorithm. Here, statistical means of standard deviation is applied to identify node with minimal load, therefore ensuring higher packet delivery ratio. Finally, with the minimal load evolving node, before performing actual data delivery, transmission probability of the node is ensured by means of Multilateration function. The Multilateration function uses the position information and with this the source node selects the relay nodes that are closer, therefore minimizing packet loss rate. The performance of the proposed Node Positioned Learning Automaton and Multilateration Data Delivery (NPLA-MDD) for MANET is evaluated using energy consumption, packet loss rate and PDR. The results of proposed method outperform than the conventional data delivery methods.