Cause Of Packet Loss Research Articles

Quantitative measurement of link failure reaction time for devices with P4-programmable data planes

Quick handling of link failures remains a challenging issue in current communication networks, although it is crucial to many routing algorithms. Link failures are the leading cause of packet losses and delays, therefore, failure recovery is tied to stringent requirements for certain services, such as the sub-50 millisecond completion time for carrier-grade networks, which is sometimes difficult to achieve in traditional routing schemes. For this reason, fast recovery strategies are key pillars of modern communication networks. In this paper, we demonstrate the benefits of the devices with Programmable Data Planes (PDP) for fast reacting to link failures. We first review the link failure detection, reaction and recovery procedures and then we discuss the main fast failure recovery mechanisms employed by different types of devices in current communication networks. In addition, we present a novel method to measure the link failure reaction time of an Intel Tofino switch with PDP, as well as the results obtained when measuring such time using real hardware equipment. Our results show that such hardware devices provide a failure reaction time in the order of microseconds, with an average of 472.88μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu $$\\end{document}s, which poses PDP as a key technology to achieve zero packet loss and zero delay failure recovery.

Practical Packet Deflection in Datacenters

Bursts, sudden surges in network utilization, are a significant root cause of packet loss and high latency in datacenters. Packet deflection, re-routing packets that arrive at a local hotspot to neighboring switches, is shown to be a potent countermeasure against bursts. Unfortunately, existing deflection techniques cannot be implemented in today's datacenter switches. This is because, to minimize packet drops and remain effective under extreme load, existing deflection techniques rely on certain hardware primitives (e.g., extracting packets from arbitrary locations in the queue) that datacenter switches do not support. In this paper, we address the implementability hurdles of packet deflection. This paper proposes heuristics for approximating state-of-the-art deflection techniques in programmable switches. We introduce Simple Deflection which deflects excess traffic to randomly selected, non-congested ports and Preemptive Deflection (PD) in which switches identify the packets likely to be selected for deflection and preemptively deflect them before they are enqueued. We implement and evaluate our techniques on a testbed with Intel Tofino switches. Our testbed evaluations show that Simple and Preemptive Deflection improve the 99th percentile response times by 8× and 425×, respectively, compared to a baseline drop-tail queue under 90% load. Using large-scale network simulations, we show that the performance of our algorithms is close to the deflection techniques that they intend to approximate, e.g., PD achieves 4% lower 99th percentile query completion times (QCT) than Vertigo, a recent deflection technique that cannot be implemented in off-the-shelf switches, and 2.5× lower QCT than ECMP under 95% load.

Predictive Lossless Queue for Extremely Large Dataset Transfer in Markov Communication Systems

In this paper, a parametric prediction model is proposed for a queuing system driven by the Markov process. The aim of the model is to minimize the packet loss caused by time dependency characterized by the queue tail being too long, resulting in a time-out during the transfer of a large dataset. The proposed technique requires the key parameters influencing the queue content to be determined prior to its occupation regardless of the server capacity definition, using Bayesian inference. The subsequent time elapsing between the arrival and departure of a packet in the system is given, as well as the system load. This queue content planning is considered as the Markov birth-death chain; a type of discretization that characterizes almost all queuing systems, leading to an exponential queue, and captured herein using beta distribution. The inference results obtained using this exponential queue indicate that the queue with predictive parameters employing beta distribution, even when dealing with a loss system queue, involves less transition time and a greater load than a queue with coarse parameters; hence, preventing a long tail in the queue which is the cause of packet loss.

Impact of Inter-Gateway Distance on LoRaWAN Performance

The large-scale behaviour of LoRaWAN networks has been studied through mathematical analysis and discrete-time simulations to understand their limitations. However, current literature is not always coherent in its assumptions and network setups. This paper proposes a comprehensive analysis of the known causes of packet loss in an uplink-only LoRaWAN network: duty cycle limitations, packet collision, insufficient coverage, and saturation of a receiver’s demodulation paths. Their impact on the overall Quality of Service (QoS) for a two-gateway network is also studied. The analysis is carried out with the discrete-event network simulator NS-3 and is set up to best fit the real behaviour of devices. This approach shows that increasing gateway density is only effective as the gateways are placed at a distance. Moreover, the trade-off between different outage conditions due to the uneven distribution of spreading factors is not always beneficial, diminishing returns as networks grow denser and wider. In particular, networks operating similarly to the one analysed in this paper should specifically avoid SF11 and 12, which decrease the average overall PDR by about 7% at 10% nodes increment across all configurations. The results of this work intend to homogenise behavioural assumptions and setups of future research investigating the capability of LoRaWAN networks and provide insight on the weight of each outage condition in a varying two-gateway network.

Lossless data transmission for Internet of things application over wireless multimedia sensor networks using enhanced and optimal path scheduling approach to maximizing the quality of service

AbstractThe congestion of packet forwarding between a source and destination is challenging on downlink transmission in the entire file (ex. Audio and Video). Whenever file is been uploaded to the server, a user requests for file where server transmits it without knowledge of user's bandwidth, which is a major, cause of packet loss or time duration in the receiver end. To accumulate the better solution, Enhanced and Optimal Path Scheduling Approach (EOPSA) designs to find optimal path scheduling for multimedia data transmission in multimedia sensor network over cloud server using IoT devices. EOPSA studied the multisource video‐on‐demand streaming in multimedia sensor networks. The method introduced a heuristic distributed protocol to find optimal route for multimedia data transmissions. Efficient way to identify the bandwidth before the transmission ensures link establishment between sender and receiver. Here, the capture of bandwidth helps to check user's system capability to forward requested media data. Based on experiment evaluation, EOPSA improves 0.20 packet delivery ratio, 130 throughput, 0.20 second average delay and 14 communication overhead for 15, 25, 50, 75, and 100 nodes compared than conventional methods.

Multipoint Passive Monitoring in Packet Networks

Traffic monitoring is essential to manage large networks and validate Service Level Agreements. Passive monitoring is particularly valuable to promptly identify transient fault episodes and react in a timely manner. This article proposes a novel, non-invasive and flexible method to passively monitor large backbone networks. By using only packet counters, commonly available on existing hardware, we can accurately measure packet losses, in different segments of the network, affecting only specific flows. We can monitor not only end-to-end flows, but any generic flow with packets following several different paths in the network (multipoint flows). We also sketch a possible extension of the method to measure average one-way delay for multipoint flows, provided that the measurement points are synchronized. Through various experiments we show that the method is effective and enables easy zooming in on the cause of packet losses. Moreover, the method can scale to very large networks with a very low overhead on the data plane and the management plane.

MAC-Layer Packet Loss Models for Wi-Fi Networks: A Survey

Technical reports indicate that wireless and mobile devices will account for 71% of all IP traffic by 2022, an increase of 19% over four years. This increase is related to advances in wireless data communication technologies. Wireless networks have become one of the most important ways to connect devices to the Internet, therein improving productivity and encouraging information sharing. IEEE 802.11, known as Wi-Fi, has become the main standard for wireless local area networks. The most important metrics for measuring the quality of Wi-Fi are delay, jitter, and packet loss. Packet loss occurs when one or more packets fail to reach their destination and can occur for a variety of reasons. Packet loss influences the user's perceived quality of applications over Wi-Fi networks, mainly multimedia and real-time applications. The availability of accurate models for packet loss in Wi-Fi networks enables the development of more efficient methods for performance analysis and network design, as well as better computational simulations. Modeling packet loss in such networks presents a major challenge because packets may be lost for many different reasons, including signal attenuation, noise, multipathing, signal refraction, thermal noise, competition for media access and buffer issues. In this paper, we provide an overview of the causes of packet loss and a comprehensive survey of the available models for packet loss in Wi-Fi networks. The potential benefits of the survey are: (i) the systematic presentation of available packet loss models for Wi-Fi networks, their parameters, and respective packet loss rate evaluation, (ii) comparison of models considering validation scenarios and input parameters, and (iii) description of open issues and future research directions. We hope that our analysis will help researchers understand the most important characteristics of the packet loss process in Wi-Fi networks and the strengths and weaknesses of the main packet loss models.

Congestion avoidance algorithm using ARIMA(2,1,1) model-based RTT estimation and RSS in heterogeneous wired-wireless networks

In the past two decades, there has been a fast growth in the heterogeneous wired-wireless network which connects variety of networks such as wired network, wireless network, high speed network and sensor network with the Internet. Since the wired network and wireless network use the different technologies, there is a necessity of developing new protocols or redesigning of existing protocols. Transmission Control Protocol is redesigned to achieve the reliable and effective communication in the heterogeneous wired-wireless network. The basic assumption made in Transmission Control Protocol is that the packet losses are caused by the network congestion but in case of wireless network, the packet losses may be due to temporary link failure, high Bit-Error-Rate etc. Hence the congestion avoidance algorithm of Transmission Control Protocol needs to be redesigned to cope with heterogeneous wired-wireless network. Therefore in this paper, we propose a congestion avoidance algorithm which differentiates the cause of packet losses. The essential components of proposed algorithm are round-trip-time estimation, backlogged packet estimation, channel status notification, loss differentiation algorithm and congestion window control. A round-trip-time estimation using ARIMA(2,1,1) model is proposed in this paper which estimates the sudden changes in the round trip time. It helps us to estimate the backlogged packet and thereby differentiating the congestive packet loss from non-congestive packet loss. In addition, we use the received signal strength of wireless receiver to differentiate the packet losses. Based on the packet loss differentiation, the congestion window size is controlled to avoid the congestion in the network. The proposed algorithm is simulated using network simulator under different network environments. From the simulation results, it is realized that the proposed congestion avoidance algorithm performs well in the heterogeneous wired-wireless network.

Traffic-aware congestion control (TACC) for wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) have emerged as a revolutionary technology, that has shifted the focus of low power wireless sensor networks (WSNs). These networks are aimed at gathering and delivering both scalar and multimedia data from the environment. WMSNs inherit the miniature size, low power, low processing and short range wireless communication traits from WSNs. Addition of multimedia content in WMSNs demands fulfillment of various QoS parameters like low end-to-end delay, acceptable jitter rate, low packet loss rate and higher throughput. Over the past few years, considerable research efforts have been directed towards the fulfillment of these QoS requirements; by proposing new traffic-aware medium access and routing algorithms. However, the issues of rate adaptation and congestion control are still largely unexplored. Congestion in wireless networks is a major cause of packet loss resulting in degraded network performance. In WMSNs congestion is a common occurrence, due to the communication of high data rate, bursty video traffic over lossy wireless link. Therefore, it is critical to adjust the sending rate of source nodes based on network conditions. This work investigates the issue of rate adaptation and congestion control in WMSNs. A traffic-aware congestion control protocol (TACC) is proposed that operates on end-to-end principle at the transport layer. The proposed protocol uses burst loss information to detect congestion at the destination and directs source nodes to adjust reporting rate accordingly. The proposed protocol is evaluated using simulation analysis which shows significant improvement in terms of packet losses, end-to-end delay, packet delivery ratio and received picture quality.

Forensic Analysis of Packet Losses in Wireless Networks

Due to the lossy nature of wireless links, it is difficult to determine if packet losses are due to wireless-induced effects or from malicious discarding. Many prior efforts on detecting malicious packet drops rely on evidence collected via passive monitoring by neighbor nodes. However, they do not analyze the cause of packet losses. In this paper, we ask: 1) Given certain macroscopic parameters of the network (like traffic intensity and node density) what is the likelihood that evidence exists with respect to a transmission? 2) How can these parameters be used to perform a forensic analysis of the reason for the losses? Toward answering the above questions, we first build an analytical framework that computes the likelihood that evidence (we call this transmission evidence, or TE for short) exists with respect to transmissions, in terms of a set of network parameters. We validate our analytical framework via both simulations as well as real-world experiments on two different wireless testbeds. The analytical framework is then used as a basis for a protocol within a forensic analyzer to assess the cause of packet losses and determine the likelihood of forwarding misbehaviors. Through simulations, we find that our assessments are close to the ground truth in all examined cases, with an average deviation of 2.3% from the ground truth and a worst case deviation of 15.0%.

Node or Link? Fine-Grained Analysis of Packet-Loss Attacks in Wireless Sensor Networks

In wireless sensor networks, packet losses are often an indicator of possible undergoing attacks. Therefore, security solutions aiming at providing comprehensive protection must include functions for packet-loss detection. Determining the actual cause of these losses is crucial to a quick and automated reaction to the attack, be it a simple reporting of the attack or a more sophisticated action such as packet rerouting and retransmission. Packet losses in wireless sensor networks can be caused by either attacks affecting the nodes or attacks focused on the wireless links. The efficacy of the response to such attacks is highly dependent on an accurate identification of the actual attack cause. Therefore, approaches to correctly identifying the cause of packet losses are needed. The work presented in this article addresses this problem by designing and implementing a fine-grained analysis (FGA) tool that investigates packet-loss events and reports their most likely cause. Our FGA tool profiles the wireless links between the nodes, as well as their neighborhood, by leveraging resident parameters, such as RSSI and LQI, available within every received packet. The design of the system is fully distributed and event-driven, and its low overhead makes it suitable for resource-constrained entities such as wireless motes. We have validated our approach through real-world experiments, showing that our FGA tool is effective in differentiating between the various attacks that may affect nodes and links.

Packet Recycling and Delayed ACK for Improving the Performance of TCP over MANETs

Most of the schemes that were proposed to improve the performance of transmission control protocol (TCP) over mobile ad hoc networks (MANETs) are based on a feedback from the network, which can be expensive (require extra bandwidth) and unreliable. Moreover, most of these schemes consider only one cause of packet loss. They also resume operation based on the same stand-by parameters that might vary in the new route. Therefore, we propose two techniques for improving the performance of TCP over MANETs. The first one, called TCP with packet recycling (TCP-PR), allows the nodes to recycle the packets instead of dropping them after reaching the retransmission limit at the MAC layer. In the second technique, which is called TCP with adaptive delay window (TCP-ADW), the receiver delays sending TCP ACK for a certain time that is dynamically changed according to the congestion window and the trip time of the received packet. TCP-PR and TCP-ADW are simple, easy to implement, do not require network feedback, compatible with the standard TCP, and do not require distinguishing between the causes of packet loss. Our thorough simulations show that the integration of our two techniques improves the performance of TCP over MANETs.

PERFORMANCE IMPROVEMENT OF BOTTLENECK LINK IN RED VEGAS OVER HETEROGENEOUS NETWORKS

In communication networks, congestion avoidance in routers is one of the hottest topics. Current IP network has become the dominant paradigm for all networking environments. The significant cause of packet losses in such heterogeneous networks is no longer limited to network congestion. Traditional TCP interprets every packet loss as caused by congestion which may be not the case in the current Internet. TCP Vegas detects network congestion in the early stage and successfully prevents periodic packet loss that usually occurs in TCP Reno. In this paper a new variant of TCP Vegas namedRed Vegas has used. The Red Vegas may detect random packet losses precisely. Through the packet loss differentiation, Red Vegas reacts appropriately to the losses, and therefore the throughput of connection over heterogeneous networks significantly improved. The bandwidth of the bottleneck link is under-utilized when the random loss rate is high. Therefore, a new design of the fast recovery mechanism for Red Vegas would be carried out. The proposed mechanism improves the aggression of Vegas TCP in competing for the available bandwidth whilst maintaining the inherent stability of the original Vegas TCP scheme.

Approach for discriminating losses in 802.11 wireless LANs

Packet loss in 802.11 WLANs (wireless local area networks) can occur either because of collision or a signal that is not strong enough at the receiver antenna. A challenging issue is the determination of packet loss cause once it occurs, which is a key for improving the performance of 802.11 WLANs. This article proposes and evaluates an algorithm to achieve this goal. The core of this algorithm is power level statistics at the receiver MAC. The algorithm learns from the received power levels of both correct and corrupted packets and decides whether a packet is lost because of collision or a weak signal. The results of extensive simulation experiments have shown that the proposed approach has a good potential for diagnosing the cause of packet losses in 802.11 WLANs.

Packet-Loss Distinguishing Based Link Adaptation Enhancement for Wireless LANs

As we know, packet losses in wireless local area networks (WLANs) are due to collisions or link errors. In this paper, a new strategy that distinguishes the cause of packet losses in medium access control (MAC) layer is introduced. Based on the strategy, link adaptation algorithms, including the payload size adaptation algorithm and the data rate adaptation algorithm, are proposed and employed in WLANs. Simulation results show that both algorithms increase system throughput significantly.

A Protocol To Improve The Data Communication Over Wireless Network

Reliable transport protocols are tuned to perform well in traditional networks where packet losses occur mostly because of congestion. However, in networks with wireless links in addition to wired segments this assumption would be insufficient, as the high wireless bit error rate could become the dominant cause of packet loss. The main reason of this poor performance for TCP is that TCP cannot distinguish between packets losses due to wireless errors from those due to congestion. Moreover, TCP sender cannot keep the size of its congestion window at optimum level and always has to retransmit packets after waiting for timeout, which significantly degrades throughput and end-to-end performance of TCP. In this work, a novel protocol, called DLN (Data Loss Notification), is be proposed. By changing the ACK format of TCP, we could successfully distinguish packet losses incurred by congestion and channel error which will improve both throughput and delay performance of TCP in wireless environment significantly. This mechanism has been demonstrated to provide performance improvements across a range of bit-error rates.

무선 망에서의 연속적 ECN을 이용한 TCP 성능 개선 방법

In this paper, we propose an algorithm to improve TCP performance over wireless links. TCP is known to have poor performance over wireless links because TCP has no mechanism to differentiate congestion loss from wireless loss, and treats all losses as congestive. We present a simple method to determine the cause of packet loss using the successive ECN. In addition, we present an algorithm to control the congestion window size based on the estimated queue state in order to guarantee the fairness and high link utilization.

Performance Evaluation of Fast Handover in Mobile IPv6 Based on Link-Layer Information

Handover latency is the primary cause of packet loss resulting in performance degradation of standard Mobile IPv6. Mobile IPv6 with fast Handover enables a Mobile Node (MN) to quickly detect at the IP layer that it has moved to a new subnet by receiving link-related information from the link-layer; furthermore it gathers anticipative information about the new Access Point (AP) and the associated subnet prefix when the MN is still connected to the previous Corresponding Node (CN). This paper proposes an enhancement to Fast Mobile IPv6 handover (FMIPv6), based on link layer information, we also present performance evaluations in terms of the packet loss and handover latency using evaluation models.

An energy‐aware transmission mechanism for WiFi‐based mobile devices handling upload TCP traffic

AbstractThis paper presents an energy‐aware transmission mechanism that improves the throughput and reduces the energy consumption of mobile devices in wired‐cum‐wireless TCP networks. The proposed mechanism places an agent at the base station, which identifies the cause of packet losses in the underlying network. When the mobile device acts as a TCP source, it adjusts the size of the congestion window adaptively according to the cause of packet losses with the aids of the agent in order to improve the transmission performance. In addition, the proposed mechanism lets the communication device to stay in sleep mode after completing the transmission in order to reduce the energy consumption. As a result, the cooperation between the mobile device and the agent improves the transmission performance as well as the energy efficiency greatly. To evaluate the performance of the proposed mechanism, we analyzed the effect of TCP on the communication device for mobile devices and present a power model. With extensive simulations based on the power model, we demonstrate that the proposed mechanism significantly improves the transmission performance, and reduces the energy consumption over a wide range of both wired and wireless packet losses. Copyright © 2008 John Wiley & Sons, Ltd.

Joint transmit power and physical carrier sensing adaptation based on loss differentiation for high density IEEE 802.11 WLAN

In high density (HD) IEEE 802.11 WLAN, packet loss can occur due to co-channel interference (asynchronous interference) or collisions (synchronous interference). In order to effectively mitigate the interference for spatial reuse, the causes of packet loss should be differentiated and corresponding network parameters (physical carrier sensing (PCS) threshold, transmit power (TXPW) and contention windows size) tuned accordingly. Such loss differentiation ability is not supported by current IEEE 802.11 networks; we devised a novel, zero over-the-air overhead, robust yet accurate method of estimating the probability of collision and interference, respectively. In this work, we investigate how to use differentiated packet error rate (PER) to mitigate asynchronous interference for increasing spatial reuse. Motivated by analysis, a joint transmit power and PCS threshold self-adaptation algorithm based on loss differentiation is proposed. Heuristics that address node starvation and fairness are also incorporated within the above (aggregate throughput maximization) framework to allow a flexible suite of approaches to network tuning. Elaborate simulations show that such joint adaptation algorithm can increase both total throughput and worst link throughput in HD WLAN greatly compared with PCS only adaptation without loss differentiation.