High Packet Loss Rate Research Articles

Communication Efficient Distributed Newton Method over Unreliable Networks

Distributed optimization in resource constrained devices demands both communication efficiency and fast convergence rates. Newton-type methods are getting preferable due to their superior convergence rates compared to the first-order methods. In this paper, we study a new problem in regard to the second-order distributed optimization over unreliable networks. The working devices are power-limited or operate in unfavorable wireless channels, experiencing packet losses during their uplink transmission to the server. Our scenario is very common in real-world and leads to instability of classical distributed optimization methods especially the second-order methods because of their sensitivity to the imprecision of local Hessian matrices. To achieve robustness to high packet loss, communication efficiency and fast convergence rates, we propose a novel distributed second-order method, called RED-New (Packet loss Resilient Distributed Approximate Newton). Each iteration of RED-New comprises two rounds of light-weight and lossy transmissions, in which the server aggregates the local information with a new developed scaling strategy. We prove the linear-quadratic convergence rate of RED-New. Experimental results demonstrate its advantage over first-order and second-order baselines, and its tolerance to packet loss rate ranging from 5% to 40%.

Wireless network handheld terminal-based green ecological sustainable design evaluation system: Improved data communication and reduced packet loss rate

Abstract In response to the challenge of high packet loss rates due to poor mobility of PCs, we introduce a sustainable design evaluation system centered around wireless network handheld terminals. This system combines hardware components, including microprocessor and wireless communication modules, to achieve wireless data transmission and program debugging. In the software domain, a configurable communication protocol is employed to establish an ecological data communication module supporting wireless network handheld terminals. Leveraging real-time monitoring data from multiple points, we introduce an information fusion algorithm and construct a green ecological sustainability design evaluation model. Notably, experimental results reveal that our system outperforms alternatives based on sensor and RFID technologies. It exhibits a lower packet loss rate and extends the distance of zero packet loss, highlighting its advantages in data communication.

Network Coding for Efficient File Transfer in Narrowband Environments

Achieving efficient end-to-end file transfer is challenging in a narrow-band communication environment with high latency and high packet loss rate. The traditional TCP-based scheme and the UDP-based automatic retransmission scheme have defects in the transmission performance, which cannot meet the increasing user demands. This paper proposes a high-efficiency file transfer scheme based on random linear network coding and the Kalman filtering algorithm to implement efficient end-to-end file transfer in narrow-band environment. The scheme predicts the link quality of file transmission through the Kalman filter algorithm and designs an adaptive coding strategy for file transfer through random linear network coding. Experimental results show that the proposed method outperforms traditional file transfer schemes.

Optimization of BBR Congestion Control Algorithm Based on Pacing Gain Model.

In 2016, Google proposed a congestion control algorithm based on bottleneck bandwidth and round-trip propagation time (BBR). The BBR congestion control algorithm measures the network bottleneck bandwidth and minimum delay in real-time to calculate the bandwidth delay product (BDP) and then adjusts the transmission rate to maximize throughput and minimize latency. However, relevant research reveals that BBR still has issues such as RTT unfairness, high packet loss rate, and deep buffer performance degradation. This article focuses on its most prominent RTT fairness issue as a starting point for optimization research. Using fluid models to describe the data transmission process in BBR congestion control, a fairness optimization strategy based on pacing gain is proposed. Triangular functions, inverse proportional functions, and gamma correction functions are analyzed and selected to construct the pacing gain model, forming three different adjustment functions for adaptive adjustment of the transmission rate. Simulation and real experiments show that the three optimization algorithms significantly improve the fairness and network transmission performance of the original BBR algorithm. In particular, the optimization algorithm that employs the gamma correction function as the gain model exhibits the best stability.

Secured location-aware mobility-enabled RPL

Although there have been many studies on the Internet of Things (IoT), there are still major challenges for IoT to become ubiquitous. So far, the mobility management challenge has not been addressed well. Routing Protocol for Low-Power and Lossy Networks (RPL), which is known as the de-facto for routing in IoT, does not support mobile nodes. Some studies have tried to address this challenge, but they either caused a very high Packet Loss Rate (PLR) or produced lots of control packets. Also, they have not considered the security aspects of their work which is crucial for real-world applications. In this study, a novel extension for the RPL called Secured Location-Aware Mobility-enabled RPL (SLM-RPL) is proposed to facilitate the mobility management of RPL while considering security precautions. From the mobility management point of view, according to extensive evaluations, SLM-RPL greatly reduces the hand-off delay and PLR compared to other mobility management schemes, even in big, dense, or highly dynamic networks. Therefore, SLM-RPL is shown to be the best option to be used in IoT applications, especially loss-sensitive ones. Also, SLM-RPL produces small numbers of control packets and has a low memory overhead. Moreover, from the security point of view, a probability-based method has been proposed and embedded in SLM-RPL, which is shown to be able to reduce the negative impacts of DODAG Information Solicitation (DIS) attacks by more than 99%. Also, a performable attack on SLM-RPL called False-Location-Injection (FLI) attack has been introduced, and a lightweight hybrid-structured Intrusion Detection System (IDS) has been provided to counter this attack as well as Sybil, Rank, Sinkhole, and impersonation attacks. The proposed IDS uses a voting-based approach which, when the ψ parameter is adjusted, can mitigate the impact of False-Reporting and collusion attacks. According to the evaluations, the proposed IDS can counter the mentioned attacks in the presence of Collusion attackers in different scenarios with Accuracy ≥0.99.

A Low-Power Remote Information Monitoring System of Cold Chain Logistic Based on NB-IoT

<p>With the development of information technology, cold chain logistics monitoring systems are widely used in transportation of fresh food to detect the quality parameters in real time. Poor network transmission performance, high packet loss rate and high maintenance cost are the main problems in the current cold chain logistics monitoring. To solve these problems, the paper presents a low-power monitoring system based on Narrow Band Internet of Things (NB-IoT). Considering the characteristics of the moving carriage, the polling mode of Bluetooth is proposed for the communication of one sink node to three sensor nodes. An improved working sequence is designed to reduce the power consumption of Bluetooth modules. Subsequently, analyzing the standard NB-IoT terminal state transition diagram, combining with the practical applications of cold chain logistics, an improved terminal state transition diagram is proposed and its terminal power consumption is analyzed. In the experimental test, the packet loss rate is less than 1% within 8 km. And the battery life of improved Bluetooth module is 143 times of that of traditional one. The power consumption of main service of NB-IoT is discussed, the formula is given which includes the transmission quality, random access times, number of concurrent users, sleep interval and other parameters. Through simulation and calculate, the battery life of terminal is up to 17 years. These improvements will greatly reduce the cost of cold chain logistics monitoring system. In addition, the packet loss rate test experiment proves the high reliability of the communication system.</p> <p> </p>

Learning-Based Resource Management for Low-Power and Lossy IoT Networks

Internet of Things (IoT) networks are key to the realization of modern industries and societies. A key application of IoT is in smart-grid communications. Smart-grid networks are resource constrained in terms of computing power and energy capacity. Similarly, the wireless links between devices are typically associated with high packet-loss rates, low throughput, and instability. To provide a sustainable communication mechanism, an IoT network stack is proposed for these devices. However, each network stack layer has its own constraints. For example, to facilitate the operation of these low-power and lossy network (LLN) devices, the international engineering task force (IETF) standardized a network-layer protocol called a routing protocol for low-power and lossy networks (RPLs). RPL often creates an inefficient network in densely deployed and varying traffic load conditions. Future dense IoT-based networks are expected to automatically optimize the reliability and efficiency of communication by inferring the diverse features of both the environments and actions of the devices. Machine learning (ML) provides a promising framework for such a dense network environment. In this study, we examine the underlying perspective of ML for such systems. We utilize the multiarmed bandit (MAB)-based expected energy count (BEEX) technique, which provides nodes the ability to effectively optimize their operation. Using the proposed mechanism, nodes can intelligently adapt their network-layer behavior. The performance of the proposed (BEEX) algorithm is evaluated through a Contiki 3.0 Cooja simulation. The proposed method improves the energy consumption and packet delivery ratio and produces a lower control overhead than other state-of-the-art mechanisms.

A Monitoring System Based on NB-IoT and BDS/GPS Dual-Mode Positioning

Monitoring system is widely used to detect the environment parameters such as temperature, humidity and position information in cold chain logistic, modern agriculture, hospital and so on. Poor position precision, high communication cost, high packet loss rate are the main problems in current monitoring system. To solve these problems, the paper presents a new monitoring system based on Narrow Band Internet of Things (NB-IoT) and BeiDou system/Global System Position (BDS/GPS) dual-mode positioning. Considering the position precision, a dual-mode positioning circuit based on at6558 is designed, and the calculation formula of the positioning information of the monitored target has been derived. Subsequently, a communication network based on wh-nb75-ba NB-IoT module is designed after compared with the LoRa technology. According to the characteristics of high time correlation of sensor data, an adaptive optimal zero suppression (AOZS) compression algorithm is proposed to improve the efficiency of data transmission. Experiments prove the feasibility and effectiveness of the system from the aspects of measurement accuracy, positioning accuracy and communication performance. The temperature and humidity error are less than 1 °C and 5% RH respectively with the selected sensor chips. The position error is decided by several factors, including the number of satellites used for positioning, the monitored target moving speed and NB-IoT module lifetime period. When the monitored target is stationary, the positioning error is about 2 m, which is less than that of the single GPS or BDS mode. When the monitored target moves, the position error will increase. But the error is still less than that of the single GPS or BDS mode. Then the AOZS compression algorithm is used in actually experiment. The compression ratio (CR) of it is about 10% when the data amount increasing. In addition, the packet loss rate test experiment proves the high reliability of the proposed system.

A New-Dynamic Adaptive Data Rate Algorithm of LoRaWAN in Harsh Environment

The adaptive data rate (ADR) algorithm is used in LoRaWAN, allocating an appropriate transmission rate for terminal equipment to improve channel utilization and reduce power consumption. However, the standard ADR algorithm is only suitable for static terminal equipment. In addition, due to the complexity of the external environment, the selected data rate will not match the new environment and communication packets will be lost. Therefore, this article proposed a novel and more effective ADR algorithm called new-dynamic ADR (ND-ADR). The algorithm mainly solves two problems, i.e., the standard ADR algorithm cannot be applied to mobile terminal devices and the poor communication quality and high packet loss rate in harsh environments. In this study, we also developed a frame for LoRaWAN (FLoRaWAN), a simulation framework for the star network topology LoRaWAN in OPNET. Furthermore, we built an OKUMURA–HATA model and additionally introduced a noise factor <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta$ </tex-math></inline-formula> to simulate the loss of wireless communication in harsh environments. Finally, extensive simulation results showed that the number of data packets required by different end nodes for rate allocation was different. Compared with the standard ADR algorithm, even for mobile nodes in harsh environments, the ND-ADR algorithm reduced network energy consumption by about 13%, reduced network delay by about 18%, and increased effective throughput by about 15%. Therefore, the improved ND-ADR algorithm is more suitable for wireless communication of removable nodes in harsh environments. Its advantages are better awareness of link environment, faster data rate regulation, improved channel utilization, and further reduction of network energy consumption.

Design of Tone Recognition System for Pipa Strings Based on Wireless Sensors

Pipa has been widely used as a wooden musical instrument as early as the Han period. It mainly relies on human fingers to pluck the strings to make sounds. The timbre of the pipa also has a very strong national characteristic. Understanding the meaning of words, phrases, and sentences requires tone recognition. For tone identification, the fundamental frequency conveys the most unique information. This paper summarizes the influence of the pipa’s characteristics, technology and skills of the player, and the player’s factors on the timbre of the pipa performance. In addition, given the problems of low accuracy and high data packet loss rate in the existing pipa playing tone recognition methods, this paper proposes a pipa string playing tone recognition algorithm based on wireless sensors. According to the sensor stage and weight-corresponding characteristics, on the premise of minimizing the total mean square error, the optimal weight corresponding to the sensor measurement value is found according to the adaptive mode. The unbiased estimated value of the measured value of each node is obtained through iterative calculation. The Euclidean distance between the measured value and the estimated value of each sensor obtained by the normalization process is used as the adaptive weighted recognition weight. It completes the conversion of the adaptive weighted recognition algorithm structure and the binary recognition result. The experimental results show that the proposed method has good tonal recognition accuracy in the pipa playing environment.

The DAO Induction Attack: Analysis and Countermeasure

We study the destination advertisement object (DAO) induction attack, a new attack against Internet Protocol version 6 (IPv6) routing protocol for low-power and lossy networks (RPL), the standard routing protocol for the Internet of Things (IoT). In the DAO induction attack, a compromised node in the network periodically transmits a special control message. Each of these crafted control messages induces many nodes in the network to transmit in response. We show that transmitting these unnecessary messages can significantly increase the power consumption of nodes, hence reduce the lifetime of battery-operated IoT devices. In addition, we show that the attack severely impacts end-to-end latency and packet delivery ratio, two important network performance metrics. For instance, in a network with 50 nodes, our simulation results show that the attack increases the average end-to-end latency and packet loss ratio by 410% and 260%, respectively. To counter the attack, we propose a lightweight solution. We show that our solution imposes no overhead when the network is in its normal operation (i.e., it is not under attack) and can quickly detect the attack even when the network experiences high packet loss rates.

A Method for Optimizing the Allocation of Sea Resources Based on Ecological Environment Protection

&lt;p&gt;With the increasing demand for marine resources, the marine ecological environment system is gradually destroyed. The traditional allocation of marine resources has been unable to meet the global resource search, resulting in poor distribution uniformity of marine resources and high packet loss rate of resource allocation. Therefore, an optimal allocation method of sea resources based on ecological environment protection is proposed. Based on the concept of ecological protection, this method builds an evaluation index system for the allocation of Marine resources by measuring the loss of Marine spatial resource assets, and calculates the evolution trend and coordination of Marine ecology according to the weight of evaluation index. A robust optimization method for the optimal allocation of sea resources is established by obtaining the spatial differences in the allocation of sea resources. The experimental results show that the proposed method is more uniform in the distribution of sea resources and has a lower packet loss rate.&lt;/p&gt;&#x0D;

Deep Graph Reinforcement Learning Based Intelligent Traffic Routing Control for Software-Defined Wireless Sensor Networks

Software-defined wireless sensor networks (SDWSN), where the data and control planes are decoupled, are more suited to handling big sensor data and effectively monitoring dynamic environments and events. To overcome the limitations of using static routing tables under high traffic intensity, such as network congestion, high packet loss rate, low throughput, etc., it is critical to design intelligent traffic routing control for the SDWSNs. In this paper we propose a deep graph reinforcement learning (DGRL) model-based intelligent traffic control scheme for SDWSNs, which combines graph convolution with deterministic policy gradient. The model fits well for the task of intelligent routing control for the SDWSN, as the process of data forwarding can be regarded as the sampling of continuous action space and the traffic data has strong graph features. The intelligent control policies are made by the SDWSN controller and implemented at the sensor nodes to optimize the data forwarding process. Simulation experiments performed on the Omnet++ platform show that, compared with the existing traffic routing algorithms for SDWSNs, the proposed intelligent routing control method can effectively reduce packet transmission delay, increase packet delivery ratio, and reduce the probability of network congestion.

Low Delay Transmission Model of Internet of Things Based on Data Spectrum

The traditional low delay transmission model of Internet of things has the problem of high packet loss rate, so a low delay transmission model of Internet of things based on data spectrum is designed. Firstly, the data preprocessing of the Internet of things mainly includes data fusion, data compression and data filtering, then the trust model is established, and finally the task transmission link model of the Internet of things is constructed to realize the low delay transmission of the Internet of things. The experimental results show that the low delay transmission model of IOT based on data spectrum has lower packet loss rate, higher network throughput and higher network resource utilization than the traditional model.

A Fault-Tolerant Transmission Scheme in SDN-Based Industrial IoT (IIoT) over Fiber-Wireless Networks.

Driven by the emerging mission-critical and data-intensive applications in industrial intelligent manufacturing, the software-defined network (SDN) based fiber-wireless access network (FiWi) is attracting considerable attention thanks to its capability of central control and large bandwidth. However, the heterogeneity of the network leads to new challenges, since the packet loss can be caused either by the poor channel quality of wireless links or network component failures. A novel and adaptive mechanism combining sparse random linear network coding with parallel transmission (SNC-PT) is proposed to achieve the fault-tolerance against high packet loss rate and any network element malfunction. We illustrate the benefits of using the SNC-PT mechanism to improve fault tolerance by characterizing the network performance with respect to the completion time and goodput along with its relationship to channel quality and node failures. We show that significant performance gains can be obtained in comparison with conventional uncoded transmission based on transmission control protocol (TCP). The simulation results show that the SNC-PT mechanism is fault-tolerant, while it can significantly shorten the data transmission completion time to at least 12% of the baseline and increase the goodput by about 10% compared to other coding schemes such as random linear network coding.

Evaluating Hybrid Framework of VASNET and IoT in Disaster Management System

During emergency operations in Disaster Management System (DMS) for natural and man-made disasters, any breakdown in the existing information and communication technology will affect the aspect of effectiveness and efficiency on an emergency response task. For Vehicular Ad-hoc Sensor Network (VASNET), the limitation in terms of infrastructure that consists of RSU (Roadside Sensor Unit) may partially or fully destroy the post-disaster scenario. As such, performance degradation of VASNET affects the network infrastructure on high packet loss, delay, and produce a huge amount of energy consumption in DMS. Thus, modification of VASNET and integrate with Internet of Thing (IoT) technology is a must to improve and solving the current problem on VASNET technology. Therefore, the main objective of this study was to investigate the performance of the proposed modified VASNET framework integrated with IoT at DMS in terms of energy consumption and packet loss. A suggested node in the proposed framework was introduced to implement low data rate and high data rate in evaluating the proposed framework using LTE and LTE-A transmission protocol. It was found that LTE-A contributes more energy by 25.33 (mJ/Byte) compared to LTE on 20 (mJ/Byte) on a high data rate. On the other hand, in terms of low data rate, LTE-A influences the most on the proposed framework by recording 19.82(mJ/Byte), LTE only 19.33 (mJ/Byte). For packet loss, LTE shows a high packet loss rate by contributing 11.39% compared to LTE-A, which is 8.0% in terms of low data rate, and 14.80% compared to LTE-A, only 11.97% for high data rate. Consequently, LTE-A on high data rate contributes more energy consumption and LTE in packet loss on same data rate.

On latency reductions in vehicle-to-vehicle networks by random linear network coding

In the Internet of vehicles (IoV), direct communication between vehicles, i.e., vehicle-to-vehicle (V2V) may have lower latency, compared to the schemes with help of Road Side Unit (RSU) or base station. In this paper, the scenario where the demands of a vehicle are satisfied by cooperative transmissions from those one in front is considered. Since the topology of the vehicle network is dynamic, random linear network coding is applied in such a multi-source single-sink vehicle-to-vehicle network, where each vehicle is assumed to broadcast messages to others so that the intermediate vehicles between sources and sink can reduce the latency collaboratively. It is shown that the coding scheme can significantly reduce the time delay compared with the non-coding scheme even in the channels with high packet loss rate. In order to further optimize the coding scheme, one can increase the generation size, where the generation size means the number of raw data packets sent by the source node to the sink node in each round of communication. Under the premise of satisfying the coding validity, we can dynamically select the Galois field size according to the number of intermediate nodes. It is not surprised that the reduction in the Galois field size can further reduce the transmission latency.

An enhanced hybrid ant colony optimization routing protocol for vehicular ad-hoc networks

Vehicle ad-hoc networks (VANETs) are a subclass of mobile ad hoc networks (MANETs). The VANETs communication framework is used to provide communication between moving vehicles in highway and urban road scenarios. Dynamic properties of VANETs, such as high dynamic topology, frequent route failure, high mobility of nodes, and bandwidth constraints, reduce the efficiency of routing. The long length route between source and destination affects the efficiency of the protocol in the form of high overhead, frequent disconnections, high packet loss rate, low packet delivery rate, and low throughput. In this paper, we propose an Enhanced Hybrid Ant Colony Optimization Routing Protocol (EHACORP) to improve the efficiency of the routing process using the shortest path. The shortest path in the proposed protocol has low communication costs and the least number of hops between source and destination vehicles. The EHACORP has two phases. In phase 1, the EHACORP relies on a distance calculation method to compute the distance between vehicles. In phase 2, the source-based ant colony optimization is used to guide the ants to build a shorter path with the least number of hops to transmit data. The shortest path improves the efficiency of protocol in all aspects. The simulation results show that the EHACORP has improved packet delivery rate, throughput, end-to-end delay, routing overhead, and packet loss rate compared to Fuzzy based ant colony optimization (F-ANT), Ad hoc on-demand distance vector (AODV), ant colony optimization routing algorithm (ARA), and AntNet routing protocols.

Design of intelligent invigilator system based on artificial vision

Aiming at the problems of high packet loss rate and low intelligent degree in the current video monitoring system for examination invigilation, an intelligent invigilator system design method based on artificial vision is proposed in this paper. The system design is divided into hardware and software parts, including a / D circuit, clock circuit, video frame cyclic error correction and coding circuit, program loading circuit and output interface circuit. The experimental results show that the system can effectively reduce the video packet loss in the process of invigilation, improve the visual coverage of the invigilator area, and the system is highly integrated and intelligent.

Mathematical model construction of communication security assessment method based on TST switching network matrix

In view of the shortcomings of the existing communication security assessment methods, such as long communication transmission delay and high packet loss rate, a communication security assessment method integrating TST (timeslot switching) switching network matrix is proposed. Firstly, a TST switching network matrix needs to be created, then control measures are selected according to the communication security standards, and the weight values corresponding to the control measures are solved. According to the weight value, the communication control measures are classified. Finally, the best communication scheme is obtained by calculating the compromise rate, and the mathematical model of the communication security assessment method is constructed. Experimental results show that this method has short communication delay, low packet loss rate and high security.