Efficient and reliable video transmission with error localization

The transmission of video materials by digital compression has been widely applied in recent years. The following problems are involved in this approach. (1) A duplex system composed of main and backup links is often used in the transmission of video materials. Thus, the transmission capacity of the backup system becomes redundant in the normal state. (2) No automatic image quality monitoring method for video transmission has been established. On the other hand, the coding/decoding techniques for digital video transmission are almost fully established, and various devices are already widely used. Thus, it is highly desirable to reduce the above redundancy, that is, to achieve highly efficient automatic picture quality monitoring. Consequently, this paper proposes a flat multiscalable video transmission scheme in which highly efficient and highly reliable video transmission with automatic picture quality monitoring can be realized by simply adding pre‐ and postprocessing, without modifying the existing coding/decoding devices. In the proposed scheme, noise cancellation by averaging and high picture quality are realized by processing that reduces the correlation of coding noise in the decoded video pictures of the two systems. The SN ratios of the received video and the original pictures can be estimated from the residual correlation. The proposed scheme can be applied not only to improving the efficiency of video materials transmission, but also to improving the reliability of picture transmission over the Internet. © 2003 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 86(7): 42–53, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.1168

Variable length codes (VLC) have found widespread use for efficient encoding of symbols with unequal probabilities in many practical situations. However, bit errors can cause a loss of decoder synchronism that often leads to error propagation. Recent advances in the development of VLC that limit the effect of error propagation, such as reversible VLC and self-synchronising VLC, contribute further to their popularity. However, it is still important to model the performance of various VLC code sets so that comparisons can be made between different coding schemes and for different applications. Communicating sequential processes (CSP) is a well-established formal description technique that allows one to analyse the behaviour of concurrently evolving processes. It has been successfully applied to industrial-scale problems. The paper describes how CSP can be applied to the modelling of the resync process of VLC. This approach offers three main advantages. First, a complete model comprises processes and events as basic building blocks, making this approach highly scalable. Second, different semantic models provide different level of abstraction. Third, tools are available for automatic generation of sync sequences, which also provide a measure of sync performance. This facilitates comparisons of different VLC schemes in addition to code sets obtained using a given coding scheme.

In recent years, natural disasters and environmental pollution events occur frequently and seriously threaten people's lives and property. The first step of disaster prevention and mitigation is obtaining the monitoring data of disaster situation. Currently, there are two main problems in transferring monitoring data, one is that disaster monitoring sensors are always located in remote, which are hard to access the Internet to send and receive data effectively; the other is that when major natural disasters occurs, traditional communication network, like GSM, GPRS or Internet could not provide a reliable data transmission link or even totally failed. And our studies aimed to design and implement an embedded heterogeneous communication network router (EHCNR), which integrated three communication techniques: Ethernet, the third-generation telecommunication (3G) and the short message service (SMS) of BeiDou Navigation Satellite System (BDS). Based on EHCNR, we built communication mechanism to achieve the efficient and reliable transmission of disaster monitoring data. Environmental information monitored in our study was gathered by special designed sensors. All of the monitoring data would finally be transmitted to central data warehouse server (CDWS) and stored in database. In addition, we defined transmission priority for the three heterogeneous communication networks in the protocol layer of EHCNR, and realized the device-to-device (D2D) communication in 3G network crossing different telecom operators; also we designed and implemented the data transmission through SMS of BDS. Finally, we did experiments based on EHCNR under complicated conditions, and the test results were reliable and efficient.

The Internet of Things (IoT) based Smart city applications are the latest technology-driven solutions designed to collect and analyze data to enhance the quality of life for urban residents by creating more sustainable, efficient, and connected communities. Communication nodes are networked independently to monitor the circumstances, where they require being more energy-efficient and securing, to improve the performance of sustainable cities. Because, the enormous number of networked devices makes the smart cities application vulnerable to many security breaches, all of which have serious ramifications for a city and its residents’ safety, well-being, and economic development. Low-powered sensors have limitations in terms of battery life, short transmission range, and security considerations, despite the fact that the combination of edge computing and Green IoT considerably enhances network performance in terms of processing and data storage. Consequently, it is necessary to implement an advanced approach to provide energy resources with secure data transmission for sustainable cities. Therefore, this research proposes an Intelligent Buffalo-based Secure Edge-enabled Computing (IB-SEC) framework for smart cities by IoT platform, which aims to enhance communication efficiency, and reliability, with minimizing latency in terms of energy consumption and data security for data transmission. The developed IB-SEC platform utilizes a combination of the African Buffalo Optimization (ABO) algorithm and a Distributed Hash function-based security algorithm to enhance the efficiency, security, and reliability of data transmission in IoT-based smart city networks. This platform leverages the capabilities of secure edge computing and MAC protocols to achieve its goals, by implementing encryption, authentication, and access control mechanisms that ensure the wireless communication is secure, and the data is protected against unauthorized access. Overall, the IB-SEC framework provides an advanced approach to secure IoT networks and enable smart city applications. Moreover, the developed platform enables the integration of heterogeneous edge devices, sensors, and systems which is effectively managed and adapted by Median Access Control (MAC) protocols. The IB-SEC is implemented in MATLAB and validated through cutting-edge security algorithms in terms of improved security, reliability, throughput, and reduced latency and energy consumption.

In this paper an efficient and reliable video transmission system is developed over wide-band CDMA wireless networks. The video coder is based on MPEG4 coding standard, while the transmission system is subject to a joint design of quantization, spreading, channel coding, as well as, an effective error concealment. In particular two-fold advantages of wide-band CDMA technology are considered. One is its effective mitigation of multi-path fading; the other is its potential in supporting variable data rate as a function of user application. Extensive simulations with different test video sequences and various channel conditions have confirmed the effectiveness of the proposed system.

As the amount of information in the internet of things increases, data storage management tends to be distributed, which leads to problems such as difficult data cooperation and interaction between sites, low communication efficiency, and poor reliability. Blockchain is one of the new information technologies supporting the development of management information system. It provides a solution for the storage, verification, transmission, and exchange of distributed data. To optimize the communication performance from two aspects of communication topology and communication mechanism, a multi-link and concurrent communication tree model was constructed. To improve blockchain communication technology, an interactive design method based on big data rule mining and blockchain communication technology was proposed, which mainly solved the optimization of transmission performance of blockchain data. On the basis of ensuring the stability and reliability of data transmission, the efficiency of data transmission in blockchain was further optimized, and the integrated factor communication tree algorithm (IFT) was proposed. To solve the influence of transmission delay between nodes on communication performance, a multi-link multifactor weighted communication tree algorithm (MMWT) considering weight was proposed. Moreover, to improve the efficiency of data communication, ensure the reliability of transmission, and improve the fairness of service in the blockchain, different strategies for optimizing the performance of data communication in the blockchain were proposed under the constraints of factors such as node communication ability, node trust, weight, and service request priority. Finally, the simulation results showed that MMWT algorithm had good communication performance in concurrent communication time, communication tree reliability, communication tree depth, and other aspects.

In healthcare applications of WSN, the data loss due to congestion may cause death alarm for a patient in critical condition. Therefore, an efficient congestion avoidance or otherwise an efficient congestion control mechanism is required. In this paper, we present an energy efficient reliable multi-path data transmission protocol for reliable data transport over WSN for the health care application. The emergency data and sensitive data packets are transmitted through an alternate path having minimum correlation with transmission interference during congestion. The proposed protocol attempts to avoid congestion by computing the probability of congestion at the intermediate nodes and transmission rate at the intermediate node is adjusted. The buffer of each node is partitioned to support fair and efficient data delivery. The reliability of the proposed protocol is achieved through hop-by-hop loss recovery and acknowledgement. The performance of the proposed protocol is evaluated through extensive simulations. The simulation results reveal that it outperforms the existing congestion control protocols for healthcare application in terms of energy efficiency, reliability and end-to-end delivery ratio.

Nowadays, with the development of Internet communication, multipath transfer technology has been widely used in heterogeneous network communication. Multipath transfer technology enables efficient data transmission through multiple transmission paths to achieve the effect of aggregated bandwidth. However, traditional anonymous communication networks, such as Tor, I2P, etc., are single streams of data transmission. In the process of data transmission, it is easy to become the target of attacker’s listening, which makes the data easy to be damaged or even intercepted by the attacker, and cannot realize the requirement of secure, efficient and reliable data transmission. Therefore, this paper proposes an anonymous multipath transfer method based on data network coding. First, in the paper we propose a mathematical model for coding based on a circulant matrix. This model is about 80% more efficient in coding flexibility and coding/decoding efficiency compared with Galois Field (GF), and the redundant coding can tolerate 50% of packet loss. Second, a new multipath transfer mechanism is proposed in combination with data network coding, which can effectively avoid anonymity attacks. Finally, through simulation experimental tests, the results show that the method can effectively improve the reliability of data transmission in anonymous communication networks.

Variable length codes (VLCs), used in data compression, are very sensitive to error propagation in the presence of noisy channels. To address this problem, several joint source channel turbo techniques have been proposed in the literature. In this paper, we focus on pairs of source/VLC of low redundancy, i.e., when there is a good match between the source statistics and the length distribution of the VLC. It is a case not considered extensively in the literature so far and the classical concatenation of a VLC and a convolutional code is not satisfying. Through EXIT chart and interleaving gain analysis, we show that the introduction of a repetition code between the VLC and the convolutional code considerably improves global performance. In particular, excellent symbol error rates are obtained with reversible VLCs which are used in recent source codecs.

The integration of Flying Ad hoc Networks (FANETs) with Internet of Medical Things (IoMT) has introduced new opportunities and challenges in emergency healthcare delivery, especially in remote and hard-to-reach areas. This research proposes an Energy Aware Cluster Based Routing Protocol for FANETs (EA-CBRP-FAN) to enhance energy efficiency, scalability, and reliability in real-time medical data transmission. The proposed framework segments the network into cells and clusters, where sensor nodes (Cluster Members) collect vital health parameters and transmit them to Cluster Heads, which forward the data to base stations. These base stations interface with a healthcare application via cellular infrastructure, facilitating remote access to patient data for medical staff and emergency services. The network architecture also incorporates Internet of Drones (IoD) to support rapid medical response in areas inaccessible by ground transport. Performance evaluation using a Neural Network classifier shows the proposed protocol achieving approximately 42% accuracy across key metrics including precision, recall, and F1-score. The results affirm the protocol’s potential to support energy-efficient, prioritized, and resilient data routing in UAV-assisted IoMT environments.

A new coding scheme based on the scalar-vector quantizer (SVQ) is developed for compression of medical images. SVQ is a fixed-rate encoder and its rate-distortion performance is close to that of optimal entropy-constrained scalar quantizers (ECSQs) for memoryless sources. The use of a fixed-rate quantizer is expected to eliminate some of the complexity issues of using variable-length scalar quantizers. When transmission of images over noisy channels is considered, our coding scheme does not suffer from error propagation which is typical of coding schemes which use variable-length codes. For a set of magnetic resonance (MR) images, coding results obtained from SVQ and ECSQ at low bit-rates are indistinguishable. Furthermore, our encoded images are perceptually indistinguishable from the original, when displayed on a monitor. This makes our SVQ based coder an attractive compression scheme for picture archiving and communication systems (PACS), currently under consideration for an all digital radiology environment in hospitals, where reliable transmission, storage, and high fidelity reconstruction of images are desired.

As an extension of wireless sensor network in underwater environment, underwater acoustic sensor networks (UASNs) have caused widespread concern of academia. In UASNs, the efficiency and reliability of data transmission are very challenging due to the complex underwater environment in variety of ocean applications, such as monitoring abnormal submarine oil pipelines. Motivated by the importance of energy consumption in many deployments of UASNs, we therefore propose an energy-efficient data transmission scheme in this paper, called energy-efficiency grid routing based on 3D cubes (EGRCs) in UASNs, considering the complex properties of underwater medium, such as 3D changing topology, high propagation delay, node mobility and density, as well as rotation mechanism of cluster-head nodes. First, the whole network model is regarded as a 3D cube from the grid point of view, and this 3D cube is divided into many small cubes, where a cube is seen as a cluster. In the 3D cube, all the sensor nodes are duty-cycled in the media access control layer. Second, in order to make energy efficient and extend network lifetime, the EGRC shapes an energy consumption model considering residual energy and location of sensor nodes to select the optimal cluster-heads. Moreover, the EGRC utilizes residual energy, locations, and end-to-end delay for searching for the next-hop node to maintain the reliability of data transmission. Simulation validations of the proposed algorithm are carried out to show the effectiveness of EGRC, which performs better than the representative algorithms in terms of energy efficiency, reliability, and end-to-end delay.

The error recovery capability of variable length code (VLC) has been considered as an important performance and design criterion in addition to its coding efficiency. However, almost all of the existing methods for evaluating the error recovery capability of VLC assume that the transmission fault is a random single bit inversion. In this paper, we consider a more generalized problem of precisely evaluating the error recovery capability of VLC in the case that the encoded bit stream is transmitted over a BSC with arbitrary crossover probability. By making use of the Perron-Frobenius Theorem, we derive a very simple expression for the exact mean symbol error rate (MSER) in Levenshtein distance sense. We also prove that in the very low crossover probability region, the mean error propagation length (MEPL) derived for single inversion error case approaches a scaled value of MSER. In addition, we briefly discuss the error recovery of VLC over Gilbert-Elliott channel, which is one of the simplest and practical models for a channel with memory.

This paper presents a new parallel transmission framework for reliable multimedia data transmission over spectrally shaped channels using multicarrier modulation. We propose to transmit source data layers of different perceptual importance in parallel, each occupying a number of subchannels. New loading algorithms are developed to efficiently allocate the available resources, e.g. transmitted power and bit rate, to the subchannels according to the source layers they transmit. Instead of making the bit error rate of all the subchannels equal as in most existing loading algorithms, the proposed algorithm assigns different error performance to the subchannels as to achieve unequal error protection for different layers. The channel induced distortion in mean-square sense is minimized. We show that the proposed system can be applied nicely to both fixed length coding and variable length coding. Numerical examples show that the proposed algorithm achieves significant performance improvement comparing to the existing work for spectrally shaped channels commonly used in in ADSL.

Batched Sparse (BATS) codes are a type of network coding scheme that use a combination of random linear network coding (RLNC) and fountain coding to enhance the reliability and efficiency of data transmission. In order to achieve unequal error protection for different data, researchers have proposed unequal error protection BATS (UEP-BATS) codes. However, current UEP-BATS codes suffer from high error floors in their decoding performance, which restricts their practical applications. To address this issue, we propose a novel UEP-BATS code scheme that employs a precoding stage prior to the weighted BATS code. The proposed precoding stage utilizes a partially regular low-density parity-check (PR-LDPC) code, which helps to mitigate the high error floors in the weighted BATS code We derive the asymptotic performance of the proposed scheme based on density evolution (DE). Additionally, we propose a searching algorithm to optimize precoding degree distribution within the complexity range of the precoding stage. Simulation results show that compared to the conventional weighted BATS codes, our proposed scheme offers superior UEP performance and lower error floor, which verifies the effectiveness of our scheme.