Packet Recovery Research Articles

Securing the Transmission While Enhancing the Reliability of Communication Using Network Coding in Block-Wise Transfer of CoAP

The practical employment of network coding (NC) has shown major improvements when it comes to the transmission reliability of sender data and bandwidth utilization. Moreover, network coding has been employed recently to secure the transmission of data and prevent unauthorized recovery of sender packets. In this paper, we employ network coding (NC) in a practical way in networks with constrained resources with the goal of improving the reliability and security of data transfer. More specifically, we apply NC on the recent options of block-wise transfer (BWT) of the constrained application protocol (CoAP). The goal is to enhance the reliability of CoAP when used to transfer larger data blocks using BWT. Also, we employ an innovative homomorphic encryption approach to secure the BWT of CoAP.

Design and implementation for a UAV-based streaming media system

The Unmanned Aerial Vehicle (UAV)-based video streaming transmission is critical for real-time communication (RTC) applications in flying ad-hoc networks (FANET). The communication links between the nodes, however, are often unstable, especially in harsh network environments. This article first presents an architecture of a UAV-based streaming media system (USMS) for more reliable transmission, where the UAVs play multiple roles simultaneously in terms of video capturing, encoding, transmission, caching, decoding, and evaluation. To promote fluency of video transmission, we propose a distributed algorithm to explore the Tradeoff between the bandWidth, the Load, and the Video parameters (TWLV) based on the UAV flying status and Quality of Service (QoS). To enhance the Quality of Experience (QoE) significantly, we design an application-oriented multi-link transmission system with a novel multi-module stacking technology. Leveraging this design, we implement an extended splitting-merging streaming (ESMS) algorithm to deal with heavy payloads and reduce transmission latency. We also propose a multi-link retransmission (MLR) algorithm to eliminate consecutive packet losses and achieve more efficient video rebuffering. Sufficient experimental results verify that compared with the commercially available products that utilize application-layer forward error correction (AL-FEC), MultiPath TCP (MPTCP), and Deadline-aware Transport Protocol (DTP), our proposed USMS outperforms in throughput promotion, latency reduction, congestion control, packet recovery, and rebuffering efficiency.

ECRLoRa: LoRa Packet Recovery under Low SNR via Edge–Cloud Collaboration

Low-Power Wide-Area Networks (LPWANs), extensively utilized for connecting billions of IoT devices, encounter wireless interference challenges in unlicensed frequency bands. Cutting-edge research suggests employing Received Signal Strength Indication (RSSI) sequences for error detection to mitigate interference-related issues. Nevertheless, the effectiveness of this method significantly declines under low signal-to-noise ratios (SNRs). Additionally, long-range communication often results in low SNR received signals, sometimes even below the noise floor. Targeting this fundamental issue, this article proposes the LPWAN packet technique, broadly applicable across diverse scenarios through edge–cloud collaboration. On the edge side, we propose an innovative architecture that fully exploits spatial distribution and interference independence in the field. Rather than utilizing resource-intensive RSSI-based error detection, we leverage a lightweight coding scheme for error detection at the Long Range (LoRa) edge, forwarding correct frames to the cloud. On the cloud side, packet recovery is achieved utilizing group-weighted voting. We design and implement ECRLoRa with commercially available devices (SemTech’s SX1278 and SX1302 LoRa chipsets) and assess its performance in low SNR environments. Our thorough evaluation demonstrates that our approach attains a Packet Recovery Ratio of 96% with low SNR (i.e., below −10 dB), resulting in 1.8× throughput, 7.5× faster recovery time, and 4.92× average accuracy compared to state-of-the-art cloud-optimized application layer solutions.

Modeling and Analysis of Cooperative Packet Recovery Protocol

Modeling and Analysis of Cooperative Packet Recovery Protocol

Analysis of Coded Slotted ALOHA With Energy Harvesting Nodes for Perfect and Imperfect Packet Recovery Scenarios

We analyze the performance of Coded Slotted ALOHA (CSA) protocols in scenarios where users are equipped with limited batteries that are recharged through Energy Harvesting (EH). First, we assume a Perfect Packet Recovery Scenario (PPRS) for which the received packets are decoded with no errors when there is no interference. We introduce Battery Outage Probability (BOP) as an extra performance metric; and, we derive the optimal EH-CSA transmission policies, which offer the maximum attainable traffic load while maintaining an asymptotically negligible Packet Loss Ratio (PLR), under specific rate and BOP constraints. We extend our study to Imperfect Packet Recovery Scenario (IPRS) where impairments at the physical layer, including channel estimation and channel decoding errors, will distort messages being passed through the iterative Successive Interference Cancellation (SIC) process. The distorted messages being passed through the SIC process potentially lead to error propagation. In order to track the error propagation process, we define the concept of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Accumulated Noise plus Interference Power</i> (ANIP), and analytically track the evolution of its probability distribution. We employ our results to evaluate the bit error rates for different transmission policies for the case of IPRS. We also demonstrate the advantages of the optimal transmission policies through numerical examples for both PPRS and IPRS. Our results show that the optimal EH-CSA policies outperform the policies optimized for standard CSA without EH considerations, and the schemes that are optimal for PPRS are not necessarily optimal for the IPRS case. Furthermore, the EH-CSA optimal policies strictly outperform standard CRDSA when the system is required to support higher traffic loads.

Accelerating Partial Packet Recovery in RLNC

Accelerating Partial Packet Recovery in RLNC

VIDEO SENSOR OVER ULTRA-LOW POWER RELAY WIRELESS NETWORKS

Ultra-low-power wireless networks have a vast array of potential applications, which are becoming increasingly achievable as technology gets smaller. Before these systems can be used to their full potential, however, efficient methods of data transfer are imperative in order to keep power consumption low while allowing the devices to cooperate as one unit or group. The transfer of large files, such as image data, presents a particular challenge because of the size limits imposed by the 802.15.4 MAC protocol. Operating sensory nodes at larger distances than normal also results in significant data loss. This paper presents a solution to this issue using a modified sensor network that includes nodes dedicated to listening for packet recovery. A set of algorithms is devised in order to allow nodes to detect missing data from a source as well as offer the ability to request that missing data from one of the dedicated relay nodes. The methods described were tested with the iMote2 device and found to almost double the distance at which two nodes can be placed from each other while still maintaining reliable data transfer. It was also concluded that the Linux driver in charge of passing values from the 802.15.4 chip to the MAC layer does not properly pass the Cyclical Redundancy Check (CRC) result into the MAC frame. As a result, it is not possible to filter out corrupt data at the application layer.

Complex sparse Bayesian learning for guided wave dispersion curve estimation in plate-like structures

This paper proposes a new dispersion curve estimation method that employs the complex sparse Bayesian learning (CSBL). It is well accepted that guided wave packets are distorted because of the differences in propagation velocities at different frequencies; thus, the preceding velocity–frequency curve estimation is beneficial for wave packet recovery, feature recognition and defect localization. Conventional dispersion curve estimation methods, such as two-dimensional Fourier transform and multiple signal classification, are suitable for array signal and are restricted by the transducer aperture, leading to a small application scope. According to the frequency–response model of the guided wave, for each frequency, the responses obtained by the transducers can be sparsely represented based on an overcomplete dictionary matrix constructed using multiple discretized wavenumbers and known distances. A CSBL algorithm was developed to infer the posterior probability density function of the weight vector in the sparse representation. The non-zero elements in the sparse weight vector mean that the corresponding dictionary atoms indicated wavenumbers are contained in the frequency response, and the velocity–frequency curve can be finally derived from the wavenumber–frequency curve. The proposed CSBL method has a satisfactory capability to solve this sparse representation of the complex frequency response because a hierarchical form of the Laplace prior is employed to achieve a high degree of sparsity of the weight vector. This method effectively incorporates the real and imaginary parts of the complex frequency response by employing the same hyperparameter to integrate the known information. This method requires only a few randomly placed transducers; thus, it has a wide range of applications. The effectiveness of the proposed approach was validated using multiple guided-wave signals obtained through numerical simulations and an experimental study on a plate structure.

On Streaming Codes With Unequal Error Protection

Error control codes for real-time interactive applications such as audio and video streaming must operate under strict delay constraints and be resilient to burst losses. Previous works have characterized optimal streaming codes that guarantee perfect and timely recovery of all source packets when the burst loss is below a certain maximum threshold. In this work, we generalize the notion of streaming codes to the unequal error protection (UEP) setting. Toward this end, we define two natural notions of streaming codes; symbol-level UEP and packet-level UEP. In the symbol-level UEP, the symbols within each source packet have varying recoverability requirements. In the packet-level UEP scenario, packets at even time slots and odd time slots have different recovery guarantees. We discuss practical motivations for both settings and develop coding schemes. We establish optimality or near-optimality guarantees through information-theoretic converse bounds. Simulations over Gilbert and Fritchman channels show that our coding schemes outperform baseline schemes over a wide range of channel parameters.

Application Layer ARQ Algorithm for Real-Time Multi-Source Data Streaming in UAV Networks.

Because of the specific characteristics of Unmanned Aerial Vehicle (UAV) networks and real-time applications, the trade-off between delay and reliability imposes problems for streaming video. Buffer management and drop packets policies play a critical role in the final quality of the video received by the end station. In this paper, we present a reactive buffer management algorithm, called Multi-Source Application Layer Automatic Repeat Request (MS-AL-ARQ), for a real-time non-interactive video streaming system installed on a standalone UAV network. This algorithm implements a selective-repeat ARQ model for a multi-source download scenario using a shared buffer for packet reordering, packet recovery, and measurement of Quality of Service (QoS) metrics (packet loss rate, delay and, delay jitter). The proposed algorithm MS-AL-ARQ will be injected on the application layer to alleviate packet loss due to wireless interference and collision while the destination node (base station) receives video data in real-time from different transmitters at the same time. Moreover, it will identify and detect packet loss events for each data flow and send Negative-Acknowledgments (NACKs) if packets were lost. Additionally, the one-way packet delay, jitter, and packet loss ratio will be calculated for each data flow to investigate the performances of the algorithm for different numbers of nodes under different network conditions. We show that the presented algorithm improves the QoS of the video data received under the worst network connection conditions. Furthermore, some congestion issues during deep analyses of the algorithm’s performances have been identified and explained.

K-means clustering for SAT-AIS data analysis

The paper deals with a problem of automatic identification system (AIS) data analysis, especially eliminating the impact of AIS packet collision and detecting existing outliers in AIS data. To solve this problem, a clustering-based approach is proposed. AIS is a system that supports the exchange of information between vessels about their trajectories, e.g. position, speed or course. However, SAT-AIS, which enables the system to work on a global scale, struggles against packet collisions due to the fact that the satellite, which receives AIS data from ships, has a field of view that covers multiple areas that are not synchronized among themselves. As a result, the received data is difficult to process by AIS receivers, because most of the messages have a character of noise. In this paper, results of a computational experiment using k-means algorithm for packet recovery and for dealing with noise have been presented. The outcome proves that a clustering-based approach could be used as an initial step in AIS packet reconstruction, when the original data is incorrect.

On the Minimum Average Age of Information in IRSA for Grant-Free mMTC

We consider the optimal design of the frame-based irregular repetition slotted ALOHA (IRSA) protocol for minimizing the average age of information (AAoI) in grant-free massive machine-type communications (mMTC). To this end, we first characterize the AAoI as a function of the number of user elements (UEs), the frame duration, and the repetition distribution of IRSA. We present this characterization for IRSA schemes with packet recovery at the end of frame and packet generation either at the beginning of the frame or just in time before first transmission in a frame. We also propose and characterize the AAoI of a novel early packet recovery method which further reduces the average age of information. In all cases, the analysis reveals that, as a function of normalized channel traffic (defined as the ratio of number of UEs to frame duration), the AAoI first decreases linearly due to more frequent updates received from the UEs, and increases sharply beyond a critical point due to packet recovery failures caused by collisions. We then consider the problem of minimizing AAoI by optimizing over the normalized channel traffic and repetition distribution for all the proposed sampling and recovery schemes. The optimization problem is challenging since the objective function is semi-analytical and can only be completely characterized using simulations. In an asymptotic regime where the number of UEs as well as the frame size is large, we characterize the AAoI using upper and lower bounds. We also obtain a locally optimal normalized channel traffic and repetition distribution using differential evolution. Based on the insights obtained from the asymptotic analysis, we also propose a pragmatic approach to obtain a normalized channel traffic and repetition distribution for AAoI reduction in the non-asymptotic case. Finally, we empirically show that our AAoI minimizing schemes outperform conventional throughput optimal schemes.

Improving the Decoding Speed of Packet Recovery in Network Coding

The reliability of communication channels is one of the most challenging tasks in wireless communication. Network coding (NC) has emerged as a compelling solution to improve throughput performance and reliability by sending coded packets and accepting valid ones at the receiver. Discarding corrupted coded packets in NC often meant discarding potentially useful information. Thus, using forward error correction (FEC) in each coded packet makes the corrupted packets useful at the receiver. In this letter, we propose a fast decoding algorithm for packet recovery in NC (F-PRNC) using an algebraic consistency between the coded packets to detect their possible corrupted parts. We provided a complexity analysis of the F-PRNC and compared it with partial packet recovery schemes such as DAPRAC and S-PRAC. Our simulation result shows that F-PRNC exceeds both methods in a variety of conditions.

Packet Loss Recovery in Broadcast for Real-Time Applications in Dense Wireless Networks

Packet loss recovery in wireless broadcast is challenging, particularly for real-time applications which have strict and short delivery deadline. To recover the maximum number of lost packets within a short time, existing packet recovery solutions often rely on instantly decodable network coding (IDNC). Some of these solutions can recover nearly the maximum number of lost packets possible at the cost of collecting feedback from all (or a large percentage of) users. This is impractical in dense networks. In addition, their runtime grows with the number of users, which is not desirable due to the urgent delivery deadline of real-time applications. In this work, we introduce random instantly decodable network coding (RIDNC), a random encoding approach to IDNC. We propose RA ndom IDN C E ncoder (RACE), a fast RIDNC encoder that can recover nearly as many lost packets as the optimal RIDNC encoder. We compare RACE with the CrowdWiFi encoder, a high performing packet loss recovery solution used in CrowdWiFi, a commercial system for broadcasting live video in dense networks. We show that RACE is up to two orders of magnitude faster than the CrowdWiFi encoder, and recovers more lost packets in practice, where there is not enough time to collect feedback from many users.

Random NOMA With Cross-Slot Successive Interference Cancellation Packet Recovery

Conventional power-domain non-orthogonal multiple access (NOMA) relies on precise power control, which requires real-time channel state information at transmitters. This requirement severely limits its application to future wireless communication systems. To address this problem, we consider NOMA without power allocation, where we exploit the random channel fading and opportunistically perform successive interference cancellation (SIC) detection. To mitigate the multi-user interference, we propose a random NOMA where users randomly transmit their data packets with a certain probability. Then a cross-slot SIC packet recovery scheme is proposed to recover transmitted data packets. We model the cross-slot SIC packet recovery as a Markov process, and provide a throughput analysis, based on which the sum rate is maximized by jointly optimizing the transmission probability and the encoding rate of users.

Partial packet in wireless networks: a review of error recovery approaches

Data transmission in wireless networks is vulnerable to errors, due to the nature of wireless characteristics. As a result, corrupted packets are a common case in wireless data transmissions. Many techniques have been proposed to tackle these issues and one of the recommended techniques is the partial packet recovery (PPR) scheme. There are various existing PPR methods that have been proposed in wireless networks over the past two decades. In addition, the recent works have shown the possibility of network coding along with its capabilities in recovering the partial packets. A review study of PPR approaches in wireless networks is presented in this study. The authors classify the approaches into several groups based on the soft information in the PHY layer. Furthermore, they describe the PPR techniques that have used in each of these groups. Their studies found that there are 24 protocols have been proposed using PPR to improve the performance in wireless networks.

Harnessing Node Multiplicity for Detecting and Mitigating False Data in Wireless Relay Networks

We present the physical-layer maximum a posteriori (MAP) test for detecting false data in multiple-source wireless relay networks. The MAP test, which minimizes the average probability of detection error, exploits the noisy (erroneous) information about the true packet that the destination receives (overhears) directly from the source nodes as a reference. We show that the average probability of detection error decreases exponentially as the number of source nodes increases, regardless of the reliability of the reference information. This indicates that the multiplicity of source nodes can be leveraged to construct a powerful integrity check mechanism for detecting false data at the destination. We also present a parallel MAP test that improves the detection accuracy when the number of source nodes is limited and overhearing channel disparities are high. Then, we present a packet recovery mechanism to recover false alarmed packets, i.e. unmodified packets that are mistakenly declared as modified, by the MAP test and thereby to improve the throughput.

Reliable BIER With Peer Caching

BIER (Bit-Indexed Explicit Replication) alleviates the operational complexities of multicast protocols (associated to the multicast tree and the incurred state in intermediate routers), by allowing for source-driven, per-packet destination selection, efficient encoding thereof in packet headers, and stateless forwarding along shortest-path multicast trees. BIER per-packet destination selection enables efficient reliable multicast delivery: packets not received by a subset of intended destinations can be efficiently BIER-retransmitted to only that subset. While BIER-based reliable multicast exhibits attractive performance attributes, relying on source retransmissions for packet recovery may be costly – even unnecessary, if topologically close peers are able to provide a copy of the packet. Thus, this paper extends the use of reliable BIER multicast to allow recovery also from peers, using Segment Routing (SR) to steer retransmission requests through a set of potential (local) candidates, before requesting retransmissions from the source as a last resort only. A general framework is introduced, which can accommodate different policies for the selection of candidate peers for retransmissions. Simple (both static and adaptive) policies are introduced and analyzed, both (i) theoretically and (ii) by way of simulations in data-center-like and real-world topologies. Results indicate that local peer recovery is able to substantially reduce the overall retransmission traffic, and that this can be achieved through simple policies, where no signalling is required to build a set of candidate peers.

Design of network coding based reliable sensor networks

Network coding can be very useful in achieving a balance between energy efficiency and end-to-end packet error in sensor networks, particularly if only a subset of the nodes act as encoding nodes. In this article, a mathematical model and a heuristic algorithm are proposed to plan for the best placement of encoding nodes while ensuring reliability. These approaches are also able to address scenarios where sensor networks, using different gateways, are federated. In this case a distributed storage system is required to ensure the recovery of packets when related coded packets arrive to the different gateways. The experimental results show that the adequate number and placement of encoding nodes can be effectively determined, significantly enhancing the performance of constrained sensor networks using network coding.

Throughput Analysis of Interference Cancellation-Based Random Access With Feedback

We consider interference cancellation-based random access for scenarios of multiple users communicating with a common receiver. An instinct feedback is assumed to inform the users whether their packets were correctly recovered. Users update their transmission packets once recovered, or a retransmission process is triggered. At the receiver, interference cancellation decoding is employed to resolve packet collisions. By modeling the transmission and packet recovery as a Markov process, a throughput analysis is provided based on which the optimal transmission probability is derived.