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The capacity of a linearly homomorphic signature (LHS) to facilitate linear computations on signed data is a frequently employed feature to safeguard network coding-based applications against pollution attacks. The security of LHS wholly depends on the security of secret signing keys; once a secret key is compromised, the application system's security will be broken. However, as relatively insecure mobile devices are increasingly used in network-coding application systems, the key exposure issue is becoming more prevalent. In order to mitigate the harm of key exposure to LHS deployed in network coding systems, we integrate forward security into LHS and use the fixed-dimension lattice basis delegation technique and the additive homomorphic hash function family to propose a forward-secure identity-based LHS scheme, which achieves post-quantum security while ensuring the validity of signatures from previous time periods even if the current secret key is compromised. The proposed scheme supports performing linearly homomorphic operations over the binary field so that the calculation of messages is a simple XOR operation. In this way, the decoding of the target node is equivalent to solving a linear system on F 2 , making it very suitable for deployment in network coding systems. We then define the first security model on the forward security of LHS and prove that the proposed scheme can resist adaptively chosen identity and dataset attacks under lattice assumptions. Moreover, compared with previous related works, the performance analysis shows that our scheme enjoys a comparable computation cost, has a lower communication cost, and provides higher security and stronger functionality. [ABSTRACT FROM AUTHOR]

In recent years, network coding has attracted widespread attention due to its important role in digital communication and network security. Among these, cyclic subspace codes have very important applications in error correction and rectification in random network coding, attracting many scholars to conduct research on them. As an important tool in constructing cyclic subspace codes, the present study focuses on the construction of Sidon spaces by leveraging the roots of irreducible polynomials and primitive elements over finite fields. In this paper, we construct some Sidon spaces with new parameters. Specifically, we let k , m 1 , m 2 be three positive integers and define ρ 1 = m 1 2 k − 1 , ρ 2 = m 2 2 m 1 − 1 . On the basis of these newly constructed Sidon spaces, we obtain new cyclic subspace codes with size ρ 1 ρ 2 q k q n − 1 q − 1 and minimum distance 2 k . [ABSTRACT FROM AUTHOR]

A subspace of a finite field is called a Sidon space if the product of any two of its nonzero elements is unique up to a scalar multiplier from the base field. Sidon spaces, introduced by Roth et al. in (IEEE Trans Inf Theory 64(6):4412–4422, 2018), have a close connection with optimal full-length orbit codes. In this paper, we will construct several families of large cyclic subspace codes based on the two kinds of Sidon spaces. These new codes have more codewords than the previous constructions in the literature without reducing minimum distance. In particular, in the case of n = 4 k , the size of our resulting code is within a factor of 1 2 + o k (1) of the sphere-packing bound as k goes to infinity. [ABSTRACT FROM AUTHOR]

Homomorphic signature is an extremely important public key authentication technique for network coding to defend against pollution attacks. However, there are many problems with previous homomorphic signature schemes which require key escrow, cannot resist malicious key generation center (KGC), and are insecure in the post-quantum era. Therefore, we propose a lattice-based certificateless linearly homomorphic signature scheme. In our scheme, certificateless structure can avoid key escrow and malicious KGC. The lattice structure ensures that our scheme is secure in the post-quantum era. The bimodal Gaussian distribution is used to improve the security and the efficiency. Compared with the previous schemes, our scheme has smaller storage space (no key escrow), can avoid malicious KGC, is more secure in the post-quantum era, and has higher signature efficiency. At the same time, our scheme is more suitable for network coding. Finally, under random oracle model, we proved that our scheme is weakly context hiding and existentially unforgeable against adaptive chosen message attacks against external attackers and the internal KGC. [ABSTRACT FROM AUTHOR]

Wireless communication systems are inherently challenged by factors such as fading, path loss, and shadowing, leading to potential errors in data transmission. Traditional methods to mitigate these issues include power control, diversification, variable beamforming, and modulation techniques. However, the unpredictable nature of the wireless medium often limits their effectiveness. A new approach to address these challenges is the implementation of cascaded intelligent reflecting surfaces (IRS). IRS systems consist of multiple passive elements that intelligently reflect electromagnetic waves, thereby enhancing signal quality. The Advanced Discrete Fourier Transform (ADFT) matrix scheme is explored in channel estimation, a novel method particularly suitable for wireless networks utilising cascaded IRS. The ADFT matrix scheme is significant for its efficiency in managing the common‐link configuration of cascading channel coefficients, which effectively reduces pilot overhead. When compared to traditional channel estimation methods like the Least Square|least squares, Maximal a posteriori probability, and Linear Minimum Mean Square Error, the ADFT matrix scheme exhibits superior performance. It achieves a remarkable reduction in normalised mean squared error (NMSE) – 66% and 80% at 20 dB and 15 dB Signal to‐Noise Ratios (SNR), respectively. Furthermore, increasing the pilot length correlates with enhanced NMSE performance, with a noted 33% improvement as the base station distance increases. Simulations demonstrate that with an escalation in the number of IRS elements and SNR, the ADFT matrix scheme consistently surpasses conventional methods. This advancement represents a significant leap in the field of wireless communication technology. [ABSTRACT FROM AUTHOR]

The complete characterization of the almost-entropic region yields rate regions for network coding problems. However, this characterization is difficult and open. In this paper, we propose a novel algorithm to determine whether an arbitrary vector in the entropy space is entropic or not, by parameterizing and generating probability mass functions by neural networks. Given a target vector, the algorithm minimizes the normalized distance between the target vector and the generated entropic vector by training the neural network. The algorithm reveals the entropic nature of the target vector, and obtains the underlying distribution, accordingly. The proposed algorithm was further implemented with convolutional neural networks, which naturally fit the structure of joint probability mass functions, and accelerate the algorithm with GPUs. Empirical results demonstrate improved normalized distances and convergence performances compared with prior works. We also conducted optimizations of the Ingleton score and Ingleton violation index, where a new lower bound of the Ingleton violation index was obtained. An inner bound of the almost-entropic region with four random variables was constructed with the proposed method, presenting the current best inner bound measured by the volume ratio. The potential of a computer-aided approach to construct achievable schemes for network coding problems using the proposed method is discussed. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicles (UAVs) have emerged as efficient tools in disaster-stricken areas, facilitating efficient data dissemination for post-disaster rescue operations. However, the limited onboard energy of UAVs imposes significant constraints on their operational lifespan, thereby presenting substantial challenges for efficient data dissemination. Therefore, this work investigates a data dissemination scheme to enhance the UAVs' bandwidth efficiency in multi-UAV-enabled Internet of Vehicles, thereby reducing UAVs' energy consumption and improving overall system performance when UAVs hover along designated flight trajectories for data dissemination. Specifically, first, we present a software-defined network-based framework for data dissemination in multi-UAV-enabled IoV. According to this framework, we formulate a problem called C2BS (Coding-based Cooperative Broadcast Scheduling) that focuses on optimizing the UAVs' bandwidth efficiency by leveraging the combined benefits of coding and caching. Furthermore, we demonstrate the NP-hardness of the C2BS problem by employing a polynomial time reduction technique on the simultaneous matrix completion problem. Then, inspired by the benefits offered by genetic algorithms, we propose a novel approach called the Genetic algorithm-based Cooperative Scheduling (GCS) algorithm to address the C2BS problem. This approach encompasses a coding scheme for representing individuals, a fitness function for assessing individuals, operators (i.e., crossover and mutation) for generating offspring, a local search technique to enhance search performance, and a repair operator employed to rectify infeasible solutions. Additionally, we present an analysis of the time complexity for the GCS algorithm. Finally, we present a simulation model to evaluate the performance. Experimental findings provide evidence of the excellence of the proposed scheme. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper we consider a scenario where there are two wireless body area networks (WBANs) interfere with each other from a game theoretic perspective. In particular, we envision two WBANs playing a potential game to enhance their performance by decreasing interference to each other. Decreasing interference extends the sensors' batteries life time and reduces the number of re‐transmissions. We derive the required conditions for the game to be a potential game and its associated the Nash equilibrium (NE). Specifically, we formulate a game where each WBAN has three strategies. Depending on the payoff of each strategy, the game can be designed to achieve a desired NE. Furthermore, we employ a learning algorithm to achieve that NE. In particular, we employ the Fictitious play (FP) learning algorithm as a distributed algorithm that WBANs can use to approach the NE. The simulation results show that the NE is mainly a function of the power cost parameter and a reliability factor that we set depending on each WBAN setting (patient). However, the power cost factor is more dominant than the reliability factor according to the linear cost function formulation that we use throughout this work. [ABSTRACT FROM AUTHOR]

As the demand for sensing and monitoring the marine environment increases, the Ocean Mobile Internet of Things (OM-IoT) has gradually attracted the interest of researchers. However, the unreliability of communication links represents a significant challenge to data transmission in the OM-IoT, given the complex and dynamic nature of the marine environment, the mobility of nodes, and other factors. Consequently, it is necessary to enhance the reliability of underwater data transmission. To address this issue, this paper proposes a reinforcement learning-based adaptive network coding (RL-ANC) approach. Firstly, the channel conditions are estimated based on the reception acknowledgment, and a feedback-independent decoding state estimation method is proposed. Secondly, the sliding coding window is dynamically adjusted based on the estimates of the channel erasure probability and decoding probability, and the sliding rule is adaptively determined using a reinforcement learning algorithm and an enhanced greedy strategy. Subsequently, an adaptive optimization method for coding coefficients based on reinforcement learning is proposed to enhance the reliability of the underwater data transmission and underwater network coding while reducing the redundancy in the coding. Finally, the sampling period and time slot table are updated using the enhanced simulated annealing algorithm to optimize the accuracy and timeliness of the channel estimation. Simulation experiments demonstrate that the proposed method effectively enhances the data transmission reliability in unreliable communication links, improves the performance of underwater network coding in terms of the packet delivery rate, retransmission, and redundancy transmission ratios, and accelerates the convergence speed of the decoding probability. [ABSTRACT FROM AUTHOR]

Signal space alignment (SSA) is a promising technique for interference management in wireless networks. However, despite the excellent work done on SSA, its robustness against jamming attacks has not been considered in the literature. In this paper, we propose two antijamming strategies for the SSA scheme applied in the multiple-input–multiple-output (MIMO) Y channel. The first scheme involves projecting the jamming signal into the null space of each source's precoding vectors, effectively eliminating it entirely. The second scheme removes interference originating from the jammer by subtracting the disturbance estimate from the incoming signal. The estimate is derived on the basis of the criterion of minimizing the received signal energy. The block error rate (BLER) performance of the proposed strategies in various channel configurations is verified by link level simulations and is presented to show the efficiency in mitigating jamming signals within the SSA-based MIMO Y channel. [ABSTRACT FROM AUTHOR]

Ensuring source location privacy is crucial for the security of underwater acoustic sensor networks amid the growing use of marine environmental monitoring. However, the traditional source location privacy scheme overlooks multi-attacker cooperation strategies and also has the problem of high communication overhead. This paper addresses the aforementioned limitations by proposing an underwater source location privacy protection scheme based on game theory under the scenario of multiple cooperating attackers (SLP-MACGT). First, a transformation method of a virtual coordinate system is proposed to conceal the real position of nodes to a certain extent. Second, through using the relay node selection strategy, the diversity of transmission paths is increased, passive attacks by adversaries are resisted, and the privacy of source nodes is protected. Additionally, a secure data transmission technique utilizing fountain codes is employed to resist active attacks by adversaries, ensuring data integrity and enhancing data transmission stability. Finally, Nash equilibrium could be achieved after the multi-round evolutionary game theory of source node and multiple attackers adopting their respective strategies. Simulation experiments and performance evaluation verify the effectiveness and reliability of SLP-MACGT regarding aspects of the packet forwarding success rate, security time, delay and energy consumption: the packet delivery rate average increases by 30%, security time is extended by at least 85%, and the delay is reduced by at least 90% compared with SSLP, PP-LSPP, and MRGSLP. [ABSTRACT FROM AUTHOR]

Blockchain technology has witnessed a burgeoning integration into diverse realms of economic and societal development. Nevertheless, scalability challenges, characterized by diminished broadcast efficiency, heightened communication overhead, and escalated storage costs, have significantly constrained the broad-scale application of blockchain. This paper introduces a novel Encode-and CRT-based Scalability Scheme (ECSS), meticulously refined to enhance both block broadcasting and storage. Primarily, ECSS categorizes nodes into distinct domains, thereby reducing the network diameter and augmenting transmission efficiency. Secondly, ECSS streamlines block transmission through a compact block protocol and robust RS coding, which not only reduces the size of broadcasted blocks but also ensures transmission reliability. Finally, ECSS utilizes the Chinese remainder theorem, designating the block body as the compression target and mapping it to multiple modules to achieve efficient storage, thereby alleviating the storage burdens on nodes. To evaluate ECSS's performance, we established an experimental platform and conducted comprehensive assessments. Empirical results demonstrate that ECSS attains superior network scalability and stability, reducing communication overhead by an impressive 72% and total storage costs by a substantial 63.6%. [ABSTRACT FROM AUTHOR]

Random Linear Network Coding (RLNC) is well-known to provide high throughput and low latency for vast communication networks. However, RLNC often suffers from high coefficients overhead, specifically, when it's applied to limited resource or short-packet networks. Herein, the problem of RLNC coefficients vector overhead is revisited. A novel framework, based on modular arithmetic and prime numbers, and influenced by the Chinese remainder theorem (CRT), is proposed to reduce the coefficients overhead by augmenting only a tiny one item coefficient instead of the entire coefficients vector. The proposed method successfully addresses all the shortcomings of previous methods, including restrictions on generation size and packet density, recoding on intermediate nodes, and creating innovative coding vectors. Theoretical analysis and experimental demonstrate the superior performance of the proposed scheme in terms of coefficients overhead ratio, download time, throughput, and packet drop rate. This evaluation has considered two types of networks: wireless sensors network for Internet of things, and conventional wireline Ethernet. [ABSTRACT FROM AUTHOR]

The multi-hop wireless sensor network (WSN) suffers from energy limitation and eavesdropping attacks. We propose a simple and energy-efficient convergecast mechanism using inter-flow random linear network coding that can provide confidentiality to the multi-hop WSN. Our scheme consists of two steps, constructing a logical tree of sensor nodes rooted at the sink node, with using the Bloom filter, and transmitting sensory data encoded by sensor nodes along the logical tree upward to the sink where the encoded data are decoded according to our proposed multi-hop network coding (MHNC) mechanism. We conducted simulations using OMNET++ CASTALIA-3.3 framework and validated that MHNC outperforms the conventional mechanism in terms of packet delivery ratio, data delivery time and energy efficiency. [ABSTRACT FROM AUTHOR]

Network coding is a potent technique extensively utilized in decentralized Internet of Things (IoT) systems, including the Internet of Medical Things (IoMT). Nevertheless, the inherent packet-mixing characteristics of network coding expose data transmission to pollution attacks, potentially compromising the integrity of original files. The homomorphic signature scheme serves as a robust cryptographic tool that can bolster network coding's resilience against such attacks. However, current schemes are computationally intensive for signature verification, making them impractical for IoMT environments. In this study, we propose a lightweight identity-based network coding scheme (IBNS) that minimizes computational overhead during the signing and verification processes. This scheme has been demonstrated to be secure against adaptive chosen-message attacks and is well-suited for IoMT applications. Furthermore, we assess the performance of our IBNS through both theoretical and experimental analyses. Simulation outcomes confirm that our scheme outperforms previous ones in terms of practicality and efficiency. [ABSTRACT FROM AUTHOR]

This letter proposes an augmented scheme of LT codes to improve the decoding success rate. The method involves substituting the 1‐s in full‐degree columns of the generator matrix of conventional LT codes with binary extension field elements and simultaneously increasing the ratio of full‐degree columns in the ideal soliton distribution. For non‐full‐degree columns, we retain the nonzero elements as 1‐s in the conventional LT codes generator matrix to preserve computational efficiency. Compared to conventional LT codes, the proposed method enhances the linear independence of the generator matrix, leading to a higher decoding success rate with minimal data packets. Experimental results demonstrate the effectiveness of the method at improving the performance of LT codes, with close to 100% decoding success rate achieved with around 5% data redundancy. [ABSTRACT FROM AUTHOR]

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions, vulnerabilities, and assaults. Complex security systems, such as Intrusion Detection Systems (IDS), are essential due to the limitations of simpler security measures, such as cryptography and firewalls. Due to their compact nature and low energy reserves, wireless networks present a significant challenge for security procedures. The features of small cells can cause threats to the network. Network Coding (NC) enabled small cells are vulnerable to various types of attacks. Avoiding attacks and performing secure "peer" to "peer" data transmission is a challenging task in small cells. Due to the low power and memory requirements of the proposed model, it is well suited to use with constrained small cells. An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code (HHMAC) hash between transmissions since the HMAC function is generated using the shared secret. In this research, a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure "peer" to "peer" data transmission model using lightweight H-MAC (1D-LM-P2P-LHHMAC) is proposed with accurate intrusion detection. The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels, Key Pair Generation Time Levels, Chaotic Map Accuracy Levels, Intrusion Detection Accuracy Levels, and the results represent that the proposed model performance in chaotic map accuracy level is 98% and intrusion detection is 98.2%. The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high. [ABSTRACT FROM AUTHOR]

Desktop as a Service (DaaS) provides users with flexible, customizable and highly secure cloud based virtual desktop access. As the major carrier of execution results in DaaS, screen updates play an important role in users' quality of experience. In order to bring users the same feelings like manipulating a local device, timeliness and reliability should be balanced. However, a timely but unreliable transmission scheme (i.e. UDP) or a completely reliable transmission scheme (i.e. TCP) is inappropriate for such a transmission scenario, especially under a high-loss network. In this paper, we propose a Prediction and Network Coding based Transmission Scheme (PNCTS) for efficient screen updates delivery in DaaS. As an end-to-end partially reliable transmission scheme, it prioritizes different data obtained by partitioning screen updates and employs network coding and TFRC (TCP Friendly Rate Control) to compensate for data loss and adjust the sending rate of screen updates, respectively. To reduce the overhead of network coding, PNCTS uses a Hidden Markov Model to predict the reliability level of network and makes different encoding strategies for the data with different priorities. Simulation results show that PNCTS can improve display quality and instantaneous goodput effectively while maintaining end-to-end delay and jitter at a relatively low level under the static and time-varying network conditions. [ABSTRACT FROM AUTHOR]

Cognitive radio is one of the new technologies for 4G/5G applications, so cooperative relay communication and network coding are considered as certain methods to help improve their respective applications. A primary broadcast system for multimedia video streaming applications that broadcasts data to primary users and an auxiliary cooperative relay secondary cognitive radio system are considered. The secondary cooperative overlay system can use multiple error control coding methods for point-to-point data retransmission, such as channel coding, network coding, and combined coding methods to improve system performance under variable link conditions. A new technique of adaptive coding of AC2NC combined channel network for data retransmission is proposed. The new AC2NC first analyzes the channel feedback information and then selects the best retransmission coding technique based on the target bandwidth or transmission time optimization. This is instead of using a single static channel or a network coding technique with dynamic channel conditions. The proposed AC2NC improves system throughput, reduces retransmission time, and provides more spectrum access opportunities for the secondary system's own data transmissions. AC2NC's relative throughput and time saving capabilities for cognitive radio users have been shown to exceed ninety percent, under certain channel conditions, compared to some static coding methods. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Message-transmission energy expenditure dominates battery lifetime in a Wireless Sensor Network (WSN). This paper newly combines network coding with a brokered WSN architecture to decrease the number of messages by means of message aggregation. It also facilitates low-latency delivery of critical messages and improves the overall energy efficiency of a WSN. Sensor nodes are arranged into subgroups, in each of which a broker separates messages into High Priority (HP) and Best Effort (BE) queues. Both arriving HP and BE messages are separately aggregated through network coding and, according to priority, are forwarded to the next broker or eventually to a data sink, where they are decoded. Service differentiation, together with network coding, prolongs the lifetime of the network by reducing the amount of energy consumed in brokers and increases message throughput by reducing waiting times at intermediate brokers. Best-effort message latency was reduced message as well as for high-priority messages. Without network coding all WSN nodes had run out of energy, whereas with the network-coded approach, twenty percent of the sensor nodes were still alive. This compares with some prior research which provides one or more of low message latency, increased message throughput, reduced WSN energy consumption, and prioritized queueing but not all these features together. [ABSTRACT FROM AUTHOR]

Summary: Resource scheduling mechanism of LEO satellite networks is the key to determining communication efficiency. Facing the LEO satellite networks with the dynamic topology changes, varying service requirements, and intermittent inter‐satellite links (ISLs), the state‐of‐the‐art cannot achieve high resource efficiency under both heavy and burst traffic loads, and the applicability of parameters design is insufficient under intermittent ISLs. Considering this, we propose a dynamic even distribution mechanism combined with network coding DENC. This novel mechanism obtains the service requirements and allocates resources dynamically through the even distribution algorithm to balance network maintenance overhead and resource waste and improves the success probability of transmission based on network coding to balance retransmission and redundancy. In this paper, we establish performance analysis models to optimize the parameters such as maintenance frequency and coding coefficient. Besides, we construct a system‐level simulation platform. Mathematical and simulation results indicate that the resource efficiency of EMNC can be improved by more than 48% compared with SAHN‐MAC, ICSMA, CSMA‐TDMA, and HTM when all nodes have service needs, and the ISL outage rate is 20%. As the outage probability of ISL increases and the proportion of nodes with service requirements decreases, the performance advantage of EMNC becomes more apparent. [ABSTRACT FROM AUTHOR]

In this paper, we put forward the model of multiple linear-combination security multicast network coding, where the wiretapper desires to obtain some information about a predefined set of multiple linear combinations of the source symbols by eavesdropping any one (but not more than one) channel subset up to a certain size r, referred to as the security level. For this model, the security capacity is defined as the maximum average number of source symbols that can be securely multicast to all sink nodes for one use of the network under the linear-combination security constraint. For any security level and any linear-combination security constraint, we fully characterize the security capacity in terms of the ratio of the rank of the linear-combination security constraint to the number of source symbols. Also, we develop a general construction of linear security network codes. Finally, we investigate the asymptotic behavior of the security capacity for a sequence of linear-combination security models and discuss the asymptotic optimality of our code construction. [ABSTRACT FROM AUTHOR]

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 an efficient end-to-end file transfer scheme in a 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. [ABSTRACT FROM AUTHOR]

Systematic codes are of important practical interest for communications. Network coding, however, seems to conflict with systematic codes: although the source node can transmit message packets, network coding at the intermediate network nodes may significantly reduce the number of message packets received by the destination node. Is it possible to obtain the benefit of network coding while preserving some properties of the systematic codes? In this paper, we study the systematic design of batched network coding, which is a general network coding framework that includes random linear network coding as a special case. A batched network code has an outer code and an inner code, where the latter is formed by linear network coding. A systematic batched network code must take both the outer code and the inner code into consideration. Based on the outer code of a BATS code, which is a matrix-generalized fountain code, we propose a general systematic outer code construction that achieves a low encoding/decoding computation cost. To further reduce the number of random trials required to search a code with a close-to-optimal coding overhead, a triangular embedding approach is proposed for the construction of the systematic batches. We introduce new inner codes that provide protection for the systematic batches during transmission and show that it is possible to significantly increase the expected number of message packets in a received batch at the destination node, without harm to the expected rank of the batch transfer matrix generated by network coding. [ABSTRACT FROM AUTHOR]

The construction of the Industrial Internet has become a concrete implementation and an essential starting point in accelerating the digital transformation and intelligent upgrading of industrial manufacturing enterprises. The problem of addressing and forwarding for resource-constrained devices restricts data acquisition and dissemination on the Industrial Internet. In order to retrieve content reasonably, we propose IDEANE, an identity-differentiated content acquisition and multipath forwarding scheme with network coding and edge computing. In IDEANE, content requests are disseminated based on the identity and location information carried in a multi-identifier network, which can improve the efficiency of interest message requests and reduce idle links in the network. Moreover, the content acquisition computation is offloaded to multiple edge nodes, and the encoded data are transmitted to the edge nodes for recovery. IDEANE offloads the less demanding computing tasks to the edge nodes close to the content requesters, to relieve the pressure on providers. In addition, a collaboration method among multiple edge nodes is also studied. Multiple edge nodes collaborate to support the mobility of content requesters, save energy consumption in terminal devices, reduce transmission latency, and ensure data security. The experimental results show that IDEANE can avoid duplicated transmission, reduce the network link overhead, improve network throughput, and enhance network robustness and reliability. [ABSTRACT FROM AUTHOR]

In this paper, we consider a two-way network-coded relaying system consisting of two Primary Users (PUs) communicating via the relay node as the primary network with licensed spectrum. Multiple IoT devices capable of harvesting energy from a power beacon, utilize the same spectrum as Secondary Users (SUs). The SUs cooperate with the primary network and then transmit their own data. The devices harvest their required energy from a power beacon (PB), located near the primary relay node and store the energy in finite-size batteries. In phase one, the primary network communicate using the network coding technics and in the second phase, the SUs cooperate with the relay node by retransmitting the relay's data to PUs. In the last phase, SUs transmit their gathered information to a fusion center (FC). We apply TDMA and Signals Combining (SC) schemes in cooperation phase and derive the closed-form expressions for the outage sumrate of the secondary network. To increase the outage sumrate of the secondary network, a new NOMA-based simultaneous cooperate and transmit (NBSCT) scheme with a new time schedule is proposed. The corresponding expressions are derived and compared with that of the mentioned methods for various network parameters. The numerical results verifies that the outage sumrate of secondary network in proposed NBSCT scheme outperforms the TDMA and SC schemes under Rician fading and improves the outage sumrate by approximately 9.8 % . [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Deep reinforcement learning is a successful learning model in many application domains. A Cognitive radio network (CRN) is a promising solution for spectrum scarcity and sharing issues, while the intrusion of network coding schemes will enhance the utilization efficiency of the spectrum. In the CRN network model, the network coding scheme is incorporated to maximize the throughput and effectiveness of the data transmission. This study includes three stages: spectrum sharing model, routing model, and network coding scheme. Dueling enhanced Q reinforcement learning model is proposed for efficient spectrum sharing, and this can be executed with state, action and reward functions. The second phase is routing, which is insisted with adaptive transient search differential evaluation routing protocol to obtain an optimal path for data transmission. The third phase is network coding, and it is very crucial. A homomorphic Network coding scheme is proposed to secure and transmit efficient data by maximizing throughput and minimizing delay. The evaluation of the spectrum sharing model, network coding scheme and routing protocol are analyzed in terms of throughput, transmission delay, routing overhead, packet delivery ratio and end-to-end delay and compared with existing available techniques. In the network coding scheme, if the channel loss probability and channel conflict probability are 0.5, the proposed model attains a throughput of 2.3 × 10 5 Bits/s and 2.8 × 10 5 Bits/s, respectively. In the spectrum sharing scenario, the proposed model obtains a PU system throughput of 14 Mbps and an SU system throughput of 45 Mbps, respectively. [ABSTRACT FROM AUTHOR]

In today's information technology (IT) world, the multi-hop wireless sensor networks (MHWSNs) are considered the building block for the Internet of Things (IoT) enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service (QoS) in a stipulated time slot to end-user over the Internet. Smart city (SC) is an example of one such application which can automate a group of civil services like automatic control of traffic lights, weather prediction, surveillance, etc., in our daily life. These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput, energy efficiency, and end-to-end delay, wherein low latency is considered a challenging issue in next-generation networks (NGN). This paper introduces a single and parallels stable server queuing model with amulti-class of packets and native and coded packet flowto illustrate the simple chain topology and complexmultiway relay (MWR) node with specific neighbor topology. Further, for improving data transmission capacity inMHWSNs, an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node. Finally, the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets. The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Subspace codes are of great use in noncoherent linear network coding (Katti et al in ACM SIGCOMM Comput Commun Rev 38(4):401–412, 2008; Kötter and Kschischang in IEEE Trans Inform Theory 54(8):3579–3591, 2008; Silva et al. in IEEE Trans Inform Theory 54(9):3951–3967, 2008). As a particular subclass of subspace codes, cyclic constant dimension subspace codes can be encoded and decoded more efficiently. There is an increased interest in constructing cyclic constant dimension subspace codes whose sizes and minimum distances are as large as possible. Roth et al. (IEEE Trans Inform Theory 64(6):4412–4422, 2017) constructed several cyclic constant dimension subspace codes using Sidon spaces. In this paper, we present a criterion which can be used to determine whether or not the sum of some distinct Sidon spaces is again a Sidon space. Based on this result, we obtain cyclic constant dimension subspace codes via the sum of several Sidon spaces. Our results generalize some results in Niu et al. (Discret Math 343(5):111788, 2020) and Roth et al. (IEEE Trans Inform Theory 64(6):4412–4422, 2017). [ABSTRACT FROM AUTHOR]

Sorting extremely large datasets is a frequently occurring task in practice. These datasets are usually much larger than the computer’s main memory; thus external memory sorting algorithms, first introduced by Aggarwal and Vitter [Commun. ACM, 31 (1988), pp. 1116–1127], are often used. The complexity of comparison based external memory sorting has been understood for decades by now, but the situation remains elusive if we assume the keys to be sorted are integers. In internal memory, one can sort a set of n integer keys of Θ(lgn) bits each in O(n) time using the classic radix sort algorithm, but in external memory, there are no faster integer sorting algorithms known than the simple comparison based ones. Whether such algorithms exist has remained a central open problem in external memory algorithms for more than three decades. In this paper, we present a tight conditional lower bound on the complexity of external memory sorting of integers. Our lower bound is based on a famous conjecture in network coding by Li and Li [Proceedings of the 42nd Allerton Annual Conference on Communication, Control and Computing, 2004], who conjectured that network coding cannot help anything beyond the standard multicommodity flow rate in undirected graphs. The only previous work connecting the Li and Li conjecture to lower bounds for algorithms is due to Adler et al. [Proceedings of the 17th Annual ACM-SIAM Symposium on Discrete Algorithm, 2006, pp. 241–250]. Adler et al. indeed obtain relatively simple lower bounds for oblivious algorithms (the memory access pattern is fixed and independent of the input data). Unfortunately obliviousness is a strong limitation, especially for integer sorting: we show that the Li and Li conjecture implies an Ω(n lg n) lower bound for internal memory oblivious sorting when the keys are Θ(lgn) bits. This is in sharp contrast to the classic (nonoblivious) radix sort algorithm. Indeed going beyond obliviousness is highly nontrivial; we need to introduce several new methods and involved techniques, which are of their own interest, to obtain our tight lower bound for external memory integer sorting. [ABSTRACT FROM AUTHOR]

In wireless distributed computing systems, worker nodes connect to a master node wirelessly and perform large-scale computational tasks that are parallelized across them. However, the common phenomenon of straggling (i.e., worker nodes often experience unpredictable slowdown during computation and communication) and packet losses due to severe channel fading can significantly increase the latency of computational tasks. In this paper, we consider a heterogeneous, wireless, distributed computing system performing large-scale matrix multiplications which form the core of many machine learning applications. To address the aforementioned challenges, we first propose a random linear network coding (RLNC) approach that leverages the linearity of matrix multiplication, which has many salient properties, including ratelessness, maximum straggler tolerance and near-ideal load balancing. We then theoretically demonstrate that its latency converges to the optimum in probability when the matrix size grows to infinity. To combat the high encoding and decoding overheads of the RLNC approach, we further propose a practical variation based on batched sparse (BATS) code. The effectiveness of our proposed approaches is demonstrated by numerical simulations. [ABSTRACT FROM AUTHOR]

The error performance of generalised spatial modulation (GSM) can be further enhanced by applying Plotkin polar codes (PPCs) to GSM. This motivates us to propose a Plotkin polar coded GSM (PPC-GSM) scheme where GSM signals are protected by the PPCs. We further extend the PPC-GSM scheme to cooperative scenarios based on a natural split in the Plotkin's construction and propose the coded cooperative scheme with two sources called network polar coded cooperative GSM (NPCC-GSM). In the Plotkin's construction, two shorter codes (subcodes) were derived from a longer code. The constructed polar subcodes were then utilised to achieve coded cooperation between two sources and offer a network coding. Furthermore, we investigate the network polar coded cooperative spatial modulation (NPCC-SM) scheme as a suitable benchmark to the proposed NPCC-GSM scheme. The simulation results reveal that for the same spectral efficiency the NPCC-GSM scheme performs nearly the same as the NPCC-SM scheme in terms of bit error rate performance, but with a significant reduction in the number of transmit antennas. Moreover, the NPCC-GSM scheme outperforms the PPC-GSM scheme under identical conditions. The enhanced performance is made possible due to the synergy between two sources and the joint decoding at the destination. [ABSTRACT FROM AUTHOR]

Summary: Security in wireless sensor networks (WSNs) is challenging, owing to resource, computing, and environmental constraints. Researchers have proposed several security systems for multicasting in WSNs, but none have offered foolproof security. To make high‐security multicasting a reality, the proposed I‐RLNMCDS‐ODMRP protocol uses state‐of‐the‐art techniques such as identity‐based cryptography, random linear network coding, the minimum connected dominating set, and the on‐demand multicast routing protocol. Also, this article analyzes computation and memory overhead in the proposed protocol in terms of time in seconds and bytes, respectively, and examines its security properties. In the experimental results, the proposed protocol does not take much time to compute encryption and decryption parameters. Further, it requires little memory to store multicast message information. In the future, the proposed protocol will be tested on healthcare applications for intrabody communication through wireless body area networks. [ABSTRACT FROM AUTHOR]

In today’s information technology (IT) world, the multi-hop wireless sensor networks (MHWSNs) are considered the building block for the Internet of Things (IoT) enabled communication systems for controlling everyday tasks of organizations and industry to provide quality of service (QoS) in a stipulated time slot to end-user over the Internet. Smart city (SC) is an example of one such application which can automate a group of civil services like automatic control of traffic lights, weather prediction, surveillance, etc., in our daily life. These IoT-based networks with multi-hop communication and multiple sink nodes provide efficient communication in terms of performance parameters such as throughput, energy efficiency, and end-to-end delay, wherein low latency is considered a challenging issue in next-generation networks (NGN). This paper introduces a single and parallels stable server queuing model with a multi-class of packets and native and coded packet flow to illustrate the simple chain topology and complex multiway relay (MWR) node with specific neighbor topology. Further, for improving data transmission capacity in MHWSNs, an analytical framework for packet transmission using network coding at the MWR node in the network layer with opportunistic listening is performed by considering bi-directional network flow at the MWR node. Finally, the accuracy of the proposed multi-server multi-class queuing model is evaluated with and without network coding at the network layer by transmitting data packets. The results of the proposed analytical framework are validated and proved effective by comparing these analytical results to simulation results. [ABSTRACT FROM AUTHOR]

In this letter, a novel maximum distance separable coding enabled proxy‐based Internet censorship circumvention system is proposed to handle severe security threats. By introducing redundancy encoding and multi‐proxy transmission, its anti‐censorship capability is significantly enhanced in terms of transmission reliability and data security. A generalized characterization method is constructed for the proposed system utilizing a six‐parameter tuple. Defining successful transmission probability and secure transmission probability as the evaluation metrics of system performances, their mathematical formulations are further derived theoretically. Extensive simulation results are provided to demonstrate the effectiveness and advantages of the proposed system. [ABSTRACT FROM AUTHOR]

We establish the undecidability of conditional affine information inequalities, the undecidability of the conditional independence implication problem with a constraint that one random variable is binary, and the undecidability of the problem of deciding whether the intersection of the entropic region and a given affine subspace is empty. This is a step towards the conjecture on the undecidability of conditional independence implication. The undecidability is proved via a reduction from the periodic tiling problem (a variant of the domino problem). Hence, one can construct examples of the aforementioned problems that are independent of ZFC (assuming ZFC is consistent). [ABSTRACT FROM AUTHOR]

Two explicit schemes are designed to illustrate bidirectional controlled teleportation in a fair and practical manner. One is a symmetric scheme for single-qutrit states. The other is an asymmetric scheme for single- and two-qutrit states. Then, we extend three-dimensional system to high-dimensional system and come up with a universal scheme for arbitrary n 1 - and n 2 -qudit states by using a (2 n 1 + 2 n 2 + 1) -qudit entangled state as the quantum channel, where n 1 ≤ n 2 . The senders and the controller need to perform general Bell basis measurement and Z basis measurement, respectively. According to their measurement results, the receivers can reestablish the initial states simultaneously by performing single-qudit recovery operations which are derived by a general formula. It is worth mentioning that 2 n 1 + 1 dit classical communication cost is saved at the controller's broadcast channel with the aid of network coding. Moreover, we consider the effect of two-type high-dimensional decoherence noises: dit-flip noise and d-phase-flip noise. [ABSTRACT FROM AUTHOR]

Network coding and cloud storage are two quite different areas in their nature and were studied independently in the past years. In recent years, researchers had proposed many identity-based network coding (IB-NC) schemes for network coding, and identity-based proof-of-retrievability (IB-PoR) protocols for cloud storage. The common feature lies in that both IB-NC scheme and IB-PoR protocol avoid the tedious management of public key certificates. In this paper, for the first time, we reveal an intrinsic relationship between IB-NC scheme and IB-PoR protocol. More specifically, we will first present how to generally construct an IB-PoR protocol from any IB-NC scheme. In the opposite direction, because of the impossibility of black-box construction proposed by Chen et al. in their classical work, we propose a new notion named admissible IB-PoR protocol and describe how to obtain IB-NC scheme from any admissible IB-PoR protocol. We remark that our constructions are systematic and hence one can naturally get a series of IB-NC schemes or IB-PoR protocols, which will greatly enrich the current constructions for both network coding and cloud storage. Furthermore, we analyze and prove the security of the transformed scheme, which is based on the underlying one. Finally, in order to show the power of our general transformations, we propose two concrete instantiations and present the detailed simulations, which are based on recently proposed schemes. [ABSTRACT FROM AUTHOR]

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Active eavesdropper sends jamming signals to raise the transmit power of base stations and steal more information from cellular systems. Network coding resists the active eavesdroppers that cannot obtain all the data flows, but highly relies on the wiretap channel states that are rarely known in wireless networks. In this paper, we present a reinforcement learning (RL) based random linear network coding scheme for drone-aided cellular systems to address eavesdropping. In this scheme, the network coding policy, including the encoded packet number, the packet and power allocation, is chosen based on the measured jamming power, previous transmission performance and BS channel states. A virtual model generates simulated experiences to update Q-values besides real experiences for faster policy optimization. We also propose a deep RL version and design a hierarchical architecture to further accelerate the policy exploration and improve the anti-eavesdropping performance, in terms of the intercept probability, the latency, the outage probability and the energy consumption. We analyze the computational complexity, drone deployment, secure coverage area and the performance bound of the proposed schemes, which are verified via simulation results. [ABSTRACT FROM AUTHOR]

Summary: The recently proposed quadrature spatial modulation aided single‐input multiple‐output media‐based modulation (QSM aided SIMO‐MBM) improves the spectral efficiency and achieves a high data rate and overall system error performance when compared with conventional SIMO‐MBM and SIMO schemes. Cooperative network (CN) involves collaboration among nodes to improve wireless network reliability, link quality, and spectral efficiency. This paper investigates the performance of QSM aided SIMO‐MBM in CN by employing the decode and forward relaying technique, which utilizes two source nodes that simultaneously transmit a unique message block on the same time slot to the relay node; the relay node decodes the received message block from both transmitting nodes, before re‐encoding and re‐transmitting the decoded message block in the next time slot to the destinations in order to enhance the error performance of the QSM aided SIMO‐MBM further. Each node can decode the data of the other node using network coding (NC) techniques. Algebraic algorithms are applied to the detected message to accumulate the various transmissions. The theoretical average error probability of the proposed scheme was formulated using a lower bound technique, and the Monte Carlo simulation (MCS) results obtained validated the result. The MCS results achieved exhibit a significant improvement of 8 dB at 6 b/s/Hz for a BER of 10−5 and 12 dB at 8 b/s/Hz for a BER of 10−5 over the conventional QSM aided SIMO‐MBM scheme. Consequently, the obtained results show that the system configuration with mrf=2 outperforms the system configuration with mrf=4 for the proposed scheme. [ABSTRACT FROM AUTHOR]

As an information transmission technology, network coding can reduce the transmission delay and improve the transmission efficiency with network performance. However, the nodes in network are vulnerable to the pollution and forgery attacks. Until now, most of network coding schemes are from pairing. Under the requirement of low computation complexity, we construct certificateless homomorphism network coding signature scheme (CL-HNCSS). In CL-HNCSS, certificateless technology avoids key management and key escrow for multi-source nodes, the homomorphism and scalar multiplication are used to reduce the computation cost. CL-HNCSS satisfies the unforgeability under the adaptive chosen-message attacks and can resist the pollution attacks. In addition, CL-HNCSS has very high communication and computation efficiency. [ABSTRACT FROM AUTHOR]

We study the relation between latency and alphabet size in the context of Multicast Network Coding. Given a graph $G = (V, E)$ representing a communication network, a subset $S \subseteq V$ of sources, each of which initially holds a set of information messages, and a set $T \subseteq V$ of terminals; we consider the problem in which one wishes to design a communication scheme that eventually allows all terminals to obtain all the messages held by the sources. In this study we assume that communication is performed in rounds, where in each round each network node may transmit a single (possibly encoded) information packet on any of its outgoing edges. The objective is to minimize the communication latency, i.e., number of communication rounds needed until all terminals have all the messages of the source nodes. For sufficiently large alphabet sizes (i.e., large block length, packet sizes), it is known that traditional linear multicast network coding techniques (such as random linear network coding) minimize latency. In this work we seek to study the task of minimizing latency in the setting of limited alphabet sizes (i.e., finite block length), and alternatively, the task of minimizing the alphabet size in the setting of bounded latency. We focus on the establishing the computation complexity of the problem and present several intractability results. In particular, through reductive arguments, we prove that it is NP-hard to (i) approximate (and in particular to determine) the minimum alphabet size given a latency constraint; (ii) approximate (and in particular to determine) the minimum latency of communication schemes in the setting of limited alphabet sizes. [ABSTRACT FROM AUTHOR]

One of the important unsolved problems in information theory is the conjecture that the undirected multiple-unicast network information capacity is the same as the routing capacity. This conjecture is verified only for a handful of networks and network classes. Moreover, only two explicit upper bounds on information capacity are known for general undirected networks: the sparsest cut bound and the linear programming bound. In this paper, we present an information-theoretic upper bound, called the partition bound, on the capacity of general undirected multiple-unicast networks. We show that a decision version problem of computing the bound is NP-complete. We present two classes of undirected multiple-unicast networks such that the partition bound is achievable by routing. Thus, the conjecture is proved for these classes of networks. Recently, the conjecture was proved for a new class of networks defined by properties relating to cut-set and source-sink paths. We show the existence of a network outside of this new class of networks such that the partition bound is achievable by routing. [ABSTRACT FROM AUTHOR]