Wireless Transmission Errors Research Articles

Dynamic Compression Ratio Selection for Edge Inference Systems With Hard Deadlines

Implementing machine learning algorithms on the Internet-of-Things (IoT) devices has become essential for emerging applications, such as autonomous driving and environment monitoring. But the limitations of computation capability and energy consumption make it difficult to run complex machine learning algorithms on IoT devices, especially when the latency deadline exists. One solution is to offload the computation-intensive tasks to the edge server. However, the wireless uploading of the raw data is time consuming and may lead to deadline violation. To reduce the communication cost, lossy data compression can be exploited for inference tasks but may bring more erroneous inference results. In this article, we propose a dynamic compression ratio selection scheme for edge inference system with hard deadlines. The key idea is to balance the tradeoff between the communication cost and inference accuracy. By dynamically selecting the optimal compression ratio with the remaining deadline budgets for queued tasks, more tasks can be timely completed with correct inference under limited communication resources. Furthermore, information augmentation that retransmits less compressed data of task with erroneous inference, is proposed to enhance the accuracy performance. While it is often hard to know the correctness of inference, we use uncertainty to estimate the confidence of the inference and based on that, jointly optimize the information augmentation and compression ratio selection. Finally, considering the wireless transmission errors, we further design a retransmission scheme to reduce performance degradation due to packet losses. The simulation results show the performance of the proposed schemes under different deadlines and task arrival rates.

Joint Source and Channel Rate Allocation over Noisy Channels in a Vehicle Tracking Multimedia Internet of Things System.

As an emerging type of Internet of Things (IoT), multimedia IoT (MIoT) has been widely used in the domains of healthcare, smart buildings/homes, transportation and surveillance. In the mobile surveillance system for vehicle tracking, multiple mobile camera nodes capture and upload videos to a cloud server to track the target. Due to the random distribution and mobility of camera nodes, wireless networks are chosen for video transmission. However, the tracking precision can be decreased because of degradation of video quality caused by limited wireless transmission resources and transmission errors. In this paper, we propose a joint source and channel rate allocation scheme to optimize the performance of vehicle tracking in cloud servers. The proposed scheme considers the video content features that impact tracking precision for optimal rate allocation. To improve the reliability of data transmission and the real-time video communication, forward error correction is adopted in the application layer. Extensive experiments are conducted on videos from the Object Tracking Benchmark using the H.264/AVC standard and a kernelized correlation filter tracking scheme. The results show that the proposed scheme can allocate rates efficiently and provide high quality tracking service under the total transmission rate constraints.

Cumulated Checksum and Dynamic Addresses for Secure Wireless Sensor Networks

Due to the broadcast nature of wireless channel, attacks against wireless sensor networks are much easier to carry out as compared to wired networks. Passive attacks such as eavesdropping and traffic analysis cannot be eliminated even if cryptographic technologies are used. Conventional frames are usually designed to include checksum, which facilitates to adversaries capturing correct frames for further attacks. In most wireless sensor networks, source address and destination address at data link layer are unprotected, which makes traffic analysis quite easy. In this paper, we argue that the long-hold design principles of data link layer protocols are unreasonable from the perspective of wireless security. A secure ARQ scheme for wireless sensor networks named Sec-ARQ is proposed. Without the help of preshared keys or complex authentication infrastructure, Sec-ARQ protects frame checksum and addresses by cumulated checksum. Cumulated checksum is unknown to adversaries because of unavoidable wireless transmission errors. As frame checksum is unavailable to adversaries, error frames caused by collision cannot be detected, rendering eavesdropping useless. Addresses protection provided by cumulated checksum disables traffic analysis attacks. Sec-ARQ can defend against passive attacks effectively. Simulation results prove that Sec-ARQ can improve wireless security with little performance sacrifice, which is more suitable for resource-constrained wireless sensor networks.

Efficient mining of high-speed uncertain data streams

Currently available algorithms for data streams classification are mostly designed to deal with precise and complete data. However, data in many real-life applications is naturally uncertain due to inherent instrument inaccuracy, wireless transmission error, and so on. We propose UELM-MapReduce, a parallel ensemble classifier based on Extreme Learning Machine (ELM) and MapReduce for handling uncertain data streams. We train an efficient parallel ELM-based ensemble classifier from sequential training chunks of the uncertain data streams. The weight of each base classifier in the ensemble is adjusted according to its mean square error on the up-to-date test chunk, and the classifier with the lowest accuracy is replaced. UELM-MapReduce can classify uncertain data streams with both efficiency and accuracy while effectively handling concept drift. Experimental results demonstrate that UELM-MapReduce has better performance than other methods in prediction accuracy and computational efficiency.

Are All Bits Equal?—Experimental Study of IEEE 802.11 Communication Bit Errors

Recently, practical subframe-level schemes, such as frame combining and partial packet recovery, have been proposed for combating wireless transmission errors. These approaches depend heavily on the bit error behavior of wireless data transmissions, which is overlooked in the literature. We study the characteristics of subframe bit errors and their location distribution by conducting extensive experiments on several IEEE 802.11 WLAN testbeds. Our measurement results identify three bit error patterns: slope-line, saw-line, and finger. Among these three patterns, we have verified that the slope-line and saw-line are present in different physical environments and across various hardware platforms. However, the finger pattern does not appear on some platforms. We discuss our current hypotheses for the reasons behind these bit error patterns and how identifying these patterns may help improve the robustness of WLAN transmissions. We believe that identifiable bit error patterns can potentially introduce new opportunities in channel coding, network coding, forward error correction (FEC), and frame combining.

TCP’s dynamic adjustment of transmission rate to packet losses in wirelessnetworks

Abstract Based on the assumption of transmission control protocol (TCP) that packetsare lost due to congestion, TCP’s congestion control algorithms suchas fast retransmit/recovery (FRR) and retransmission timeouts (RTO)unconditionally reduce the transmission rate for every packet loss. When TCPoperates in wireless networks, however, FRRs/RTOs are often triggeredregardless of congestion due to sudden delay and wireless transmissionerrors. The congestion irrelative FRRs/RTOs incur TCP’s misbehaviorsuch as blindly halving the transmission rate, unnecessarily retransmittingthe outstanding packets which may be in the bottleneck queue. Although manyprevious studies have been proposed to detect the congestion irrelativeFRRs/RTOs, they paid little attention on effectively adjusting thetransmission rate for the detected congestion irrelative FRRs/RTOs. In this article, we propose an enhanced TCP to dynamically adjust itstransmission rate according to network conditions. Our scheme adjusts thetransmission rate in proportion to the available bandwidth in order toquickly utilize the available bandwidth, and also re-adjusts it in inverseproportion to the loss rate in order to avoid burst losses and longgo-back-N retransmissions. By doing so, our scheme hassignificant effects to avoid the performance degradation caused by thecongestion irrelative FRRs/RTOs. Throughout the extensive experiments, weevaluate our scheme and compare it with previous works in terms of goodput,fairness, and friendless under various network topologies. The results showthat our scheme significantly outperforms previous studies while itmaintains the fair and friendly behavior to other TCP connections.

Delay Analysis and Optimization of Bandwidth Request under Unicast Polling in IEEE 802.16e over Gilbert-Elliot Error Channel

In the centralized polling mode in IEEE 802.16e, a base station (BS) polls mobile stations (MSs) for bandwidth reservation in one of three polling modes; unicast, multicast, or broadcast pollings. In unicast polling, the BS polls each individual MS to allow to transmit a bandwidth request packet. This paper presents an analytical model for the unicast polling of bandwidth request in IEEE 802.16e networks over Gilbert-Elliot error channel. We derive the probability distribution for the delay of bandwidth requests due to wireless transmission errors and find the loss probability of request packets due to finite retransmission attempts. By using the delay distribution and the loss probability, we optimize the number of polling slots within a frame and the maximum retransmission number while satisfying QoS on the total loss probability which combines two losses: packet loss due to the excess of maximum retransmission and delay outage loss due to the maximum tolerable delay bound. In addition, we obtain the utilization of polling slots, which is defined as the ratio of the number of polling slots used for the MS's successful transmission to the total number of polling slots used by the MS over a long run time. Analysis results are shown to well match with simulation results. Numerical results give examples of the optimal number of polling slots within a frame and the optimal maximum retransmission number depending on delay bounds, the number of MSs and the channel conditions. Copyright © 2009 The Institute of Electronics, Information and Communication Engineers.

End-to-End Loss Differentiation Algorithm Based on Estimation of Queue Usage in Multi-Hop Wireless Networks

When TCP operates in multi-hop wireless networks, it suffers from severe performance degradation. This is because TCP reacts to wireless packet losses by unnecessarily decreasing its sending rate. Although previous loss differentiation algorithms (LDAs) can identify some of the packet losses due to wireless transmission errors as wireless losses, their accuracy is not high as much as we expect, and these schemes cannot avoid sacrificing the accuracy of congestion loss discrimination by misclassifying congestion losses as wireless losses. In this paper, we suggest a new end-to-end loss differentiation scheme which has high accuracy in both wireless loss discrimination and congestion loss discrimination. Our scheme estimates the rate of queue usage using information available to TCP. If the estimated queue usage is larger than 50% when a packet is lost, our scheme diagnoses the packet loss as congestion losses. Otherwise, it diagnoses the packet loss as wireless losses. Because the estimated queue usage is highly correlated to congestion, our scheme has an advantage to more exactly identify packet losses related to congestion and those unrelated to congestion. Through extensive simulations, we compare and evaluate our scheme with previous LDAs in terms of correlation, accuracy, and stability. And the results show that our scheme has the highest accuracy as well as its accuracy is more reliable than the other LDAs.

On the impact of a more realistic physical layer on MANET simulations results

Network simulation tools are frequently used to analyze the performance of MANET protocols and applications. Currently they offer only simple wireless communication models that neglect many radio propagation effects. In this paper, we integrate a more realistic physical layer model into a simulation tool. It consists of a radio propagation model and a model of wireless transmission errors. They have been evaluated against real-world measurements. We prove that such more realistic models change simulation results considerably. To the best of our knowledge, no other study of MANETs has been performed so far with such a detailed physical layer model. Hence, this paper also gives new insights on the performance of MANETs in real outdoor environments.

ECS: An enhanced carrier sensing mechanism for wireless ad hoc networks

In wireless ad hoc networks, whenever a node overhears a frame, the node should defer its transmission to prevent the interference with the ongoing transmission. The exact duration value by which the node should defer is contained in the frame. However, due to the wireless transmission errors and due to the fact that the carrier sensing range is normally greater than the transmission range, a frame overheard by a node may not always be interpretable and thus the node cannot get the precise duration value by which the node should defer. Therefore, an important issue is that whenever a node detects an erroneous frame, how long the node should defer for. In the current IEEE 802.11 standards, the node will always defer the transmission by a fixed duration (represented by EIFS). We show that this duration is sometimes smaller and sometimes larger than the desired period by which the transmission should be deferred, and it leads to substantial unfairness and throughput degradation. We propose an enhanced carrier sensing (ECS) scheme, which distinguishes among the type of the erroneous frames based on their lengths and defers the transmission accordingly. Simulation results show that the ECS improves the fairness as well as the throughput substantially. To the best of our knowledge, this is the first work that focuses on the carrier sensing mechanism to improve the performance of IEEE 802.11.

Transmission delay based control over networks with wireless links

To achieve the mobility of computers during communication, the TCP connections between fixed host and mobile host may often traverse wired and wireless networks, and the recovery of losses due to wireless transmission error is much different from congestion control. The paper analyzes the side effect of RTT estimation while making the TCP source to handle congestion and wireless error losses properly. Then present a strategy using information feedback by the last hop acknowledgement and monitoring the queuing level of the wired bottleneck link by calculating the changes in transmission delay along the path. With the identification of the early stage of congestion, it can respond to wired congestion quickly while keeping wireless link more reliable, and make TCP react to the different packets losses more appropriately.