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Evolution of Wireless sensor networks (WSN) has found its identity in Wireless Body Area Networks (WBAN) to monitor the health status of adults undergone a surgery, etc. In addition, the mobility of the sensor nodes deployed on/in the human body plays a vital role in maintaining the accuracy of the physiological signal. In this paper, a Distributed Posture-based Traffic-Medium Access Control (DPT-MAC) protocol is proposed where the sensor nodes follow the Disc Communication model for the detection of neighbor nodes based on the proximity of the sensing range. Further, the modified IEEE 802.15.4 superframe structure determines the potential sleep posture of a subject to ensure a collision-free data transmission and prioritize the data traffic based on the criticality of the data like critical, periodic and nonregular data. The critical data detection occupies the channel on high priority and will have the probability to access the other channel space during the contention period of the noncritical data. The regular guaranteed time slot (GTS) is reduced from the tradition number of slots to five, which allows the nodes to handle the throughput. This uninterrupted data transmission minimizes the delay rate and collision ratio with any number of sensor nodes as the channel synchronization is strictly followed using the Carrier Sense Multiple Access/Collision Avoidance mechanism. Here, the optimization of the network quality parameters like energy consumption, throughput, delay and collision ratio assures a guaranteed increase in the Network Lifetime. The results show that the distributed topology outperforms the conventional star topology in sustaining the Network Lifetime. [ABSTRACT FROM AUTHOR]

Let = { T 1 , T 2 , ... , T k } be a set of k ≥ 2 spanning trees in a graph G. The k spanning trees are called completely independent spanning trees (CISTs for short) if the paths joining every pair of vertices x and y in any two trees have neither vertex nor edge in common except for x and y. Particularly, is called a dual-CIST provided k = 2. For data transmission applications in reliable networks, the existence of a dual-CIST can provide a configuration of fault-tolerant routing called protection routing. This paper investigates the problem of constructing a dual-CIST in the n -dimensional hierarchical folded cubic network H F Q n . The network is a two-level network using folded hypercube F Q n as clusters to reduce the diameter, hardware overhead and improve the fault tolerance ability. We propose a recursive algorithm to construct a dual-CIST of H F Q n in (2 2 n) time for n ≥ 2 , where the time required is the same scale as the number of vertices of H F Q n . Also, the diameter of each constructed CIST is 4 n + 1. [ABSTRACT FROM AUTHOR]

With the popularization of the Internet of Things technology and the improvement of 5G communication technology, the influence of mobile devices on the network structure is increasing. The devices in the network are usually regarded as social users that transmit information. Because the movement of users is dynamic and random, it is more difficult for complex networks to grasp the changing rules of their topological structure. The data transmission model established by considering only the historical behavior of users can no longer meet the demand for fast transmission of large-capacity data. Based on this, this paper proposes a dynamic personalized data transmission model (GRDPS) that considers the recurrent neural network and attention mechanism. First, it uses a recurrent neural network to build users' personalized preferences and model the user's historical behavior. Then, GRDPS introduces an attention mechanism to dynamically weight historical user behaviors based on the user's current message transmission. It is different from the previous methods of modeling user historical behaviors. Based on the requirements of user dynamics, GRDPS effectively considers the temporal characteristics of user historical behaviors and automatically learns the evolution law of user behaviors. Based on the demand of user randomness, GRDPS fully considers the characteristic correlation between the user's historical behavior and current transmission demand. Finally, GRDPS combines these two points to obtain a personalized ranking of users. The simulation results show that the delivery rate of GRDPS is up to 0.95. Moreover, its data transmission delay and network overhead are better than other methods in the experiment. [ABSTRACT FROM AUTHOR]

Among other technologies, the Internet of Things (IoT) is one of the promising technologies that will help us to make our environment smarter and gather, analyze and process sensor data without any human intervention. Low Power Wide Area Network (LPWAN) is a technology that is part of the IoT, in which is the long-range (LoRa) technology that can provide wide coverage at a cost of very low power and that can boost data communication in our smart environment. The ease of their integration with the electronic system has opened a lot of new scope in the field of low-power wide-area networks in IoT applications. This paper provides a well-rounded review of LPWAN technology and in-depth details of LoRa technology. A good insight is given into the implementation of LoRa technology to design smart cities and the types of antenna technology used in LoRa data communications. Finally, a few open issues, possible solutions and future development are pointed out. [ABSTRACT FROM AUTHOR]

The explosive growth of video applications has produced great challenges for data storage and transmission. In this paper, we propose a new ROI (region of interest) encoding solution to accelerate the processing and reduce the bitrate based on the latest video compression standard H.265/HEVC (High-Efficiency Video Coding). The traditional ROI extraction mapping algorithm uses pixel-based Gaussian background modeling (GBM), which requires a large number of complex floating-point calculations. Instead, we propose a block-based GBM to set up the background, which is in accord with the block division of HEVC. Then, we use the SAD (sum of absolute difference) rule to separate the foreground block from the background block, and these blocks are mapped into the coding tree unit (CTU) of HEVC. Moreover, the quantization parameter (QP) is adjusted according to the distortion rate automatically. The experimental results show that the processing speed on FPGA has reached a real-time level of 22 FPS (frames per second) for full high-definition videos (1 , 9 2 0 × 1 , 0 8 0), and the bitrate is reduced by 10% on average with stable video quality. [ABSTRACT FROM AUTHOR]

In this paper, we consider the impact of the product price, service level and delay parameters on the operation of enterprises in the current Chinese telecommunications industry. A three-oligarch game model is established, where system parameters are taken as important factors affecting the development of the involved companies. By improving their service levels, the three oligarchs could plunder the market of each other, but also enhance the reputation of the industry, thus bringing more communication data usage. In the paper, firstly we analyze the static Nash equilibrium, especially the impacts of competition intensity and service cost coefficiency. Then, we analyze the stability and evolution behavior of the system under the dynamic game. We found that the increase of competition intensity and cost coefficiency has adverse effects on the stability region. Finally, we show that a delay decision of a single company has a positive impact on its own profits, but not conducive to its own stability region and the profits of the opposing oligarchs, nor to the total profit. [ABSTRACT FROM AUTHOR]

In this paper, an ultra-wideband substrate integrated coaxial line (SICL) array based on silicon-based MEMS process is proposed for high-speed data transmission. A quasi-coaxial transition array is designed to connect the SICL array with grounded-coplanar waveguides (GCPWs). Moreover, a stepped-impedance matching structure is introduced to reduce the discontinuities and improve the transmission performance. For high efficiency design, a Bayesian Optimization (BO)-based approach is adopted to optimize dimensions of the proposed SICL array. The objective function is set to be the weighted combination of the bandwidth and the crosstalk of the proposed array structure to obtain wide bandwidth and low crosstalk simultaneously. With the proposed BO-based approach, iteration times can be reduced by approximately 99.9% compared with the parametric sweep method. A 40-channel SICL array is designed and fabricated under silicon-based Micro-electromechanical Systems (MEMS) process. Ultra-wideband of 110GHz is measured in each channel with the insertion loss less than 3dB and the return loss larger than 15dB. The couplings between two adjacent channels are no more than −30dB. Good eye diagram and low bit error rate (BER) are achieved for each channel at data rate of 95Gb/s and hence the total data rate can reach 3.8Tb/s. The bandwidth density of the proposed SICL array is 0.164Gb/s/μm, which is much higher than those of the conventional SICLs. [ABSTRACT FROM AUTHOR]

Recently, wireless body area network (WBAN) becomes a hot research topic in the advanced healthcare system. The WBAN plays a vital role in monitoring the physiological parameters of the human body with sensors. The sensors are small in size, and it has a small-sized battery with limited life. Hence, the energy is limited in the multi-hop routing process. The patient data is collected by the sensor, and the data are transmitted with high energy consumption. It causes failure in the data transmission path. To avoid this, the data transmission process should be optimized. This paper presents an advanced authentication and energy-efficient routing protocol (AAERP) for optimal routing paths in WBAN. Patients' data are aggregated from the WBAN through the IoMT devices in the initial stage. To secure the patient's private data, a hybrid mechanism of the elliptic curve cryptosystem (ECC) and Paillier cryptosystem is proposed for the data encryption process. Data security is improved by authenticating the data before transmission using an encryption algorithm. Before the routing process, the data encryption approach converts the original plain text data into ciphertext data. This encryption approach assists in avoiding intrusions in the network system. The encrypted data are optimally routed with the help of the teamwork optimization algorithm (TOA) approach. The optimal path selection using this optimization technique improves the effectiveness and robustness of the system. The experimental setup is performed by using Python software. The efficacy of the proposed model is evaluated by solving parameters like network lifetime, network throughput, residual energy, success rate, number of packets received, number of packets sent, and number of packets dropped. The performance of the proposed model is measured by comparing the obtained results with several existing models. [ABSTRACT FROM AUTHOR]

Wireless sensor networks' energy consumption is the major challenge to be handled. Clustering is one of the techniques majorly used for reducing energy consumption. During the course of time, many methodologies are being proposed and the existing ones are hybrid. Still, the energy can be reduced more. The scope of optimization is always there. Existing approaches either reduce energy consumption or work on routing or only on data gathering capabilities. But the technique proposed increases the lifetime of the wireless sensor network (WSN) by reducing energy consumption and improves routing efficiency. This paper proposes an approach based upon Fractal Clustering to improve the lifetime of the sensor nodes. The proposed approach named Enhanced Energy Efficient Fuzzy-based Fractal Clustering (EEFFC) algorithm optimizes the performance of WSN. First, fractal clustering is used on sensor nodes to find the location of the sensors. Then, a fuzzy inference system (FIS) is applied to results produced by fractal clustering. Applying FIS on cluster heads generated will optimize the results. As a result, the cost of data transmission will reduce, and hence, the lifetime of the network will improve. FIS generates multi-level clustering, which will result in a better routing path for sensor nodes. Hence, routing will also be improved. MATLAB 2020 is the simulation tool. The results of the simulation depict that EEFFC shows optimized results and it works better than LEACH, LEACH-SF, TEEN and DEEC. The energy consumption is being reduced by reducing the listening time of a node and by reducing the communication distance, for which clustering is optimized. The energy consumption has been reduced by 2% as compared to the algorithms it is compared with. Also, the node's time of death has been delayed by 3% in total. [ABSTRACT FROM AUTHOR]

The wireless network on chip WiNoC introduces wireless links in the traditional network on chip (NoC), which reduces the network diameter and enables high-throughput, low-latency data communications. In addition, if wireless nodes can dynamically request data transmission, wireless bandwidth will be more effectively utilized. In order to implement a conflict-free, adaptive bandwidth allocation strategy, a priority-based dynamic media access control mechanism has been designed. In this work, a dynamic priority calculation method has been proposed based on the packets' transmission time and the waiting time in the queue. Then, a priority calculating unit is designed to calculate the dynamic priority of the packet. Finally, the central control unit designed obtains the dynamic priority of the packets, and dynamically authorizes the use rights of the wireless medium according to the priority of the data packet. Simulation experiments show that the media access control mechanism proposed in this paper has significant improvements in throughput, delay, and power consumption performances compared with other mechanisms [S.Deb et al., Wireless NoC as interconnection backbone for multicore chips: promises and challenges, IEEE J. Emerg. Sel. Topics Circuits Syst. 2 (2012) 228–239]. [ABSTRACT FROM AUTHOR]

In view of the two shortcomings of the AODV routing protocol, they do not consider the bandwidth, delay and cost in the actual network, and the routing table has only one path from the basic node to the target node. This paper attempts to improve the AODV protocol by using particle swarm optimization. Through simulation experiments, this paper compares four improved particle swarm optimization algorithms, inertia weight, linear decline, shrinkage factor and chaos, and finds that ACPSO can find the optimal path faster and transmit data quickly. So, this paper uses chaotic particle swarm optimization (CACPSO) to improve AODV protocol. Finally, based on NS2 simulation platform, the improved AODV protocol is simulated and experimented. Different network environments are set up to test packet delivery rate, network delay and routing discovery frequency. The experimental results show that in the process of data transmission, the improved protocol has higher routing performance than AODV protocol, and can transmit data faster and more stably. [ABSTRACT FROM AUTHOR]

In modern communications, code converters and accurate data transmission are essential. This paper presents a new code converter (i.e., Binary to Gray and Gray to Binary) and Parity Checker using mixed logic design. Mixed modeling will be better to achieve low power, high speed and fewer transistors instead of considering a single logic style for array structures. It is important to note that additional metal layers are required for implementation. The HSPICE simulations have been done on these circuits with various supply voltages and frequencies. The existing circuits are compared with mixed logic design circuits and found that the proposed designs show better performance. Especially when compared with FS_XOR1 (which produces better results than others), the power consumption of Mixed logic design is reduced by 5.40%, the speed is improved by 14.89% and PDP is also decreased by 19.48% in the case of Binary to Gray. Moreover, significant improvements can be seen with other existing designs. [ABSTRACT FROM AUTHOR]

The Direct Simulation Monte Carlo (DSMC) algorithm is widely employed for simulating rarefied gas flows and is increasingly applied in near-continuum regimes for research and engineering purposes. However, its computational demands, notably load imbalance and extended simulation time, hinder widespread adoption. Addressing these challenges, this paper introduces the Two-Level parallel load balancing strategy. This novel approach combines thread-level and multi-process parallelism to enhance load balancing and reduce simulation time. Key features include a thread-level load-decoupling strategy implemented via OpenMP and a multi-process load balancing mechanism employing distributed memory via MPI. Building upon our previous PartPlusColl [L. Li, W. Ren and B. Zhang, J. Aeronaut. Astronaut. Aviat. Ser. A 46, 88 (2014)] approach, the load balancing mechanism utilizes Stop At Risk (SAR) criteria for repartitioning with METIS. Additionally, a specialized data transmission mechanism utilizing MPI nonblocking communication minimizes global communication between processes. Validation and evaluation are performed using four hypersonic flow cases around a cylinder and sphere, demonstrating significant improvements. Notably, the proposed strategy achieves 30% enhancement over the PartPlusColl strategy under 512 CPU cores compared to 16 CPU cores, and reduces between-process communication time with 33.57%. These advancements contribute to enhancing the effectiveness of the DSMC algorithm in near-continuum aerodynamic simulations. [ABSTRACT FROM AUTHOR]

In the colloquy concerning human rights, equality, and human health, mental illness and therapy regarding mental health have been condoned. Mental disorder is a behavioral motif that catalyzes the significant anguish or affliction of personal functioning. The symptoms of a mental disorder may be tenacious, degenerative, or transpire as a single episode. Brain sickness is often interpreted as a combination of how a person thinks, perceives, contemplates and reacts. This may be analogous to a specific region or workings of the brain frequently in a social context. Anxiety disorders, psychotic disorders, personality disorders, mood disorders, eating disorders, and many more are examples of mental disorders, while complications include social problems, suicides, and cognitive impairment. These days, mental disorders are quotidian worldwide, and clinically consequential levels of derangement rise adversely. The purpose of this paper is to aid in prognosis of the type of mental disorder by analyzing the brainwaves such as Alpha (α), Beta (β), Gamma (γ), Theta (), Delta (δ) with the help of big data analysis and the Internet of Medical Things (IoMT). IoMT helps in gathering the required data and data transmission, while big data analysis helps in predicting the type of disorder. [ABSTRACT FROM AUTHOR]

In WSN, extending the network life is still a major problem that needs to be tackled. Cross-layer protocols are used to get around these problems. In this paper, a new cross-layer design routing model is presented using a clustering-based technique. The proposed model is proceeding with the optimal cluster-based routing model via a new algorithm. Initially during the network generation, the node's energy is predicted by the deep learning model termed as DNN model on the basis of the distance between node and sink as the input. Subsequently, during the clustering process, the cluster head is optimally selected via a new optimisation algorithm named Self-Improved Shuffle Shepherd Optimisation (SISSO) Algorithm. The cluster head selection is done by considering the constraints including Link quality, Distance, Overhead, Energy and Delay. Finally, a Modified Kernel Least Mean Square (MKLMS)-based data aggregation process is to eliminate the redundant data transmission. The performance of the SISSO method is proven superior over other conventional approaches with regard to the alive node and network lifetime. In the alive node analysis of supernode, the proposed SISSO model achieves the maximal number of alive supernodes at 2,000 rounds (i.e. 0.67) than other conventional methods. [ABSTRACT FROM AUTHOR]

In this paper, the theoretical model of the coupling efficiency of BG beams to few-mode fibers (FMFs) in the case of perfect alignment, lateral or vertical offsets, and random angular jitter is investigated and compared with that of sew-mode fibers (SMFs). Under the same conditions, FMF obtains a higher coupling efficiency with the BG beam and flatter response characteristics to deviations from ideal conditions compared with SMF. At the same time, the effects of the half-cone angle and topological charge of the BG beam on the coupling efficiency and response characteristics during nonideal conditions are studied. According to the precision of the coupling system, a higher coupling efficiency can be obtained by adjusting the half-cone angle, topological charge, and focal length. That makes them a more practical choice for information transmissions, such as mobile platform communication and the transmission of pedestrian data collected during transportation. The research results could help apply the BG beam and other orbital angular momentum (OAM) beams coupled with FMF. [ABSTRACT FROM AUTHOR]

Recent healthcare systems are defined as highly complex and expensive. But it can be decreased with enhanced electronic health records (EHR) management, using blockchain technology. The healthcare sector in today's world needs to address two major issues, namely data ownership and data security. Therefore, blockchain technology is employed to access and distribute the EHRs. With this motivation, this paper presents novel data ownership and secure medical data transmission model using optimal multiple key-based homomorphic encryption (MHE) with Hyperledger blockchain (OMHE-HBC). The presented OMHE-HBC model enables the patients to access their own data, provide permission to hospital authorities, revoke permission from hospital authorities, and permit emergency contacts. The proposed model involves the MHE technique to securely transmit the data to the cloud and prevent unauthorized access to it. Besides, the optimal key generation process in the MHE technique takes place using a hosted cuckoo optimization (HCO) algorithm. In addition, the proposed model enables sharing of EHRs by the use of multi-channel HBC, which makes use of one blockchain to save patient visits and another one for the medical institutions in recoding links that point to EHRs stored in external systems. A complete set of experiments were carried out in order to validate the performance of the suggested model, and the results were analyzed under many aspects. A comprehensive comparison of results analysis reveals that the suggested model outperforms the other techniques. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are made up of multiple source-restricted wireless sensor nodes that gather, process, and transmit information. Existing research work proposed energy competence with trust as well as Quality of Service (QoS) multipath routing protocol for improving network lifetime and other QoS parameters, selection criteria for multipath. However, this protocol has some limitations, such as scalability, data redundancy, bandwidth utilization, and network traffic. The most important challenge lies in managing the voluminous data produced by the network's sensors. As a result of this study, Intelligent Data Fusion Techniques (IDFTs) were presented, which can greatly minimize redundant data, decrease the quantity of transmitting data, broaden the network life cycle, enhance bandwidth utilization, and therefore, resolve the energy and bandwidth usage bottleneck. This paper proposes Improved Whale Optimization Algorithms (IWOAs) for intelligent data fusion where the amount of data collected from sensor sources is reduced and the information offered is enhanced by duplicate data, which also increases data dependability. IWOAs are used to combine the actual information from the cluster's sensor nodes at the sink node, resulting in increased information and the ability to make local judgments about the particular events. The sink node transmits local decisions to base station on a regular basis that combines the local decisions and provides the ultimate judgment, easing the pressure on the base station to evaluate all of the data. As per the results obtained, the proposed intelligent data fusion method significantly increases the network's robustness and accuracy. [ABSTRACT FROM AUTHOR]

The revolution in the Internet of Things (IoT) is redesigning and reshaping the healthcare system technologically, economically and socially. The emerging and rapidly growing IoT-based Smart Healthcare System (SHCS) is seen as a sustainable solution to reduce the burden on the existing healthcare system due to increasing diseases and limited medical infrastructure. IoT-based SHCS plays a vital role in delivery of healthcare services in rural and remote areas where the essential medical amenities, necessary infrastructures and qualified medical practitioners are not available. Therefore, in this paper, a comprehensive investigation of futuristic IoT-based SHCS and its constituents is presented. This paper provides exhaustive review on different techniques and technologies dealing with smart healthcare framework, physiological sensing, signal processing, data communication, cloud computing and data analytics used in IoT-based SHCS. A comparative analysis of existing literature has been carried out to identify the recent trends and advancements in this very dynamic field of global importance. In addition to this, it highlights different issues and challenges, along with the recommendation for further research in the field. The prime objective of this paper is to deliver the state-of-the-art understanding and update about IoT-based SHCS and its constituents by providing a good source of information to the researchers, service providers, technologists, medical practitioners and the general population. [ABSTRACT FROM AUTHOR]

In the present era, Underwater Wireless Sensor Network (UWSN) is an emerging technology that involves a huge amount of sensor nodes to collect and monitor information from the underwater environment. However, the data transmission process is constrained due to the collision and energy consumption which can adversely affect the performance. Hence, there is an essential need to develop a suitable mechanism that addresses these challenges using a data aggregation-based routing mechanism in UWSN. In this paper, a Multi-Slot Scheduling with a Two-Layer Hexagonal based Integrated Aggregation model (MSS-TLHIA) is proposed that offers a prolonged lifetime with less energy consumption and collision avoidance. In this model, data aggregation is performed using the aggregator node selection process. Initially, the entire network is partitioned into several hexagonal grids using the golden ratio. This partitioning offers an improved coverage area for every node which are participating in the network. Once the network is partitioned into coverage areas called clusters, a Cluster Head (CH) is selected using the ranking-based fuzzy mechanism. Then, an aggregator node is selected in common for both the layers of the hexagonal grids. In order to prevent the energy drain of the aggregator node completely and to prolong their lifetime, the aggregator node is re-selected for every time slot. Furthermore, the occurrence of collision is avoided by the multi-slot scheduling process. Experimental results demonstrate that the performance of the proposed model is compared with other existing protocols and achieves better results in terms of network lifetime, energy consumption, collision rate, packet dropped rate, packet delivery, and data forwarding measures. [ABSTRACT FROM AUTHOR]

Cloud computing (CC), which provides numerous benefits to customers, is a new revolution in information technology. The benefits are on-demand, support, scalability, along with reduced cost usage of computing resources. However, with the prevailing techniques, the system's authentication is still challenging and it leads to being vulnerable. Thus, utilizing Barrel Shift-centric Whirlpool Hashing-Secure Diffie Hellman ASCII Key-Elliptic Curve Cryptography (BSWH-SDHAK-ECC), the hashed access policy (AP)-grounded secure data transmission is presented in this paper. The data owner (DO) registers their information initially. The user login and verify their profile grounded on the registration. The user selects the data to upload to the Cloud Server (CS) after successful verification. The AP is created; after that, the image attributes are extracted; also, utilizing the BSWH approach, a hash code is produced for the AP. Concurrently, by utilizing the Adaptive Binary Shift-based Huffman Encoding (ABSHE) technique, the selected image is compressed. Also, by utilizing the SDHAK-ECC algorithm, the compressed image is encrypted. Lastly, to the CS, the created AP along with the encrypted image is uploaded. The data user sent the request to access and downloads the data. After that, the AP was provided to the user by the data owner. Next, the user sends it to the CS, which checks its AP with the user's AP. When the AP is matched with the cloud AP, the encrypted data is downloaded and decrypted. Finally, the experimental outcomes revealed that the proposed model achieved a higher security value of 0.9970 that shows the proposed framework's efficient performance in contrast to the prevailing techniques. [ABSTRACT FROM AUTHOR]

In recent times, many MAC protocols were implemented for boosting and improving energy efficiency (EE) in WSNs. Moreover, the cooperative MIMO method is found to be much capable of enhancing the EE of WSNs if configured properly. This paper intends to propose cross-layer design for multihop virtual MIMO system to enhance the end-to-end (ETE) reliability, EE, and QoS of the adopted WSN. The protocol is set here to focus on the energy utilization for transmission of data packets by optimal selection of transmission constraints for each node of the network. Moreover, the protocol's ETE latency and throughput are also modeled as the dependent variables of BER performance of every link. To discover the improved BER criteria of each link that meets the ETE QoS requirement in reduced energy utilization, this paper employs a new hybrid optimization algorithm named Lion Mutated Dragonfly Algorithm (LM–DA) that is a hybrid variant of both Lion Algorithm (LA) and Dragonfly Algorithm (DA). Finally, the performance of the adopted scheme is validated over other state-of-the-art models. The results state that the energy consumed by the adopted LM–DA approach is about 2.65%, 1.77%, and 1.77% reduced over LA, PSO, and DA schemes, respectively. [ABSTRACT FROM AUTHOR]

Peer Data Management Systems (PDMSs) allow the efficient sharing of data between peers with overlapping sources of information. These sources share data through mappings between peers. In current systems, queries are asked over each peer's local schema and then translated using the mappings between peers. While this allows the data to be accessed uniformly, users lack access to information that is not in their own schemas. In this paper, we propose a light-weight, automatic method to create a mediated schema in a PDMS. Our work benefits PDMSs by allowing access to more data and without unduly stressing the peer's resources or requiring additional resources such as ontologies. We present our system - MePSys, which creates a mediated schema in PDMSs automatically using the existing mappings provided to translate queries. We further discuss how to update the mediated schema in a stable state, i.e. after the system setup period. [ABSTRACT FROM AUTHOR]

When transporting data packets on communication networks, the local routing protocols are often preferred because of the large-scale and complicated property of many realistic network structures such as Internet. Based on a local routing protocol with a navigation parameter proposed in a previous paper [W. X. Wang et al., Phys. Rev. E73, 026111 (2006)], this paper numerically investigates the distribution of travel time for transporting data packets from the origin to the destination in complex networks, including random networks, small-world networks and scale-free networks. Numerical results show that exponential distributions of travel time with various values of exponent in complex networks are obtained. Furthermore, the different values of the exponent can also intuitively prove the previous result for the optimal local routing strategy. Finally, violations of the First-Departure-First-Arrival situation in complex networks are discussed. [ABSTRACT FROM AUTHOR]

This paper addresses throughput improvement in millimeter-wave (mmWave) mesh networks via two novel distributed scheduling algorithms. The first one uses packet aggregation and block acknowledgment (ACK) that were introduced in the IEEE Std 802.11e-2005 for WiFi. Specifically, a distributed time-division multiplexing scheduling algorithm, which targets increasing the network capacity via reserving as many contiguous slots as possible for each node, is proposed thus enabling packet aggregation. This algorithm achieves its goal when the operating signal-to-noise ratio (SNR) is significantly high. If that is not the case, the second proposed algorithm can be used. It is a distributed one that starts initially with a random feasible schedule determined cooperatively between nodes. The algorithm then tries to reach better feasible schedules via parallel and successive local searches without violating feasibility constraints. Extensive simulations show that the first algorithm improves the network throughput by almost compared to the well-known memory-guided directional medium access control (MDMAC) due to reducing the transmission overhead. The second proposed algorithm is shown to increase the number of reserved slots by about over MDMAC. Both algorithms are shown to either increase or almost maintain the same degree of fairness among the nodes as quantified by Jain's fairness index. [ABSTRACT FROM AUTHOR]

This paper proposes a fuzzy logic (FL) model for evaluation of quality of service (QoS) in multimedia transmission over ad hoc networks as an effective mechanism for QoS management. It aims at minimizing the negative effects of major QoS parameters, (jitter, delay, packet loss) sustaining efficiency and reliability of data deliveries and improving overall system performance. Both triangular membership function (TMF) and Gaussian membership function (GMF) are adopted to demonstrate their effects in FL-QoS evaluation. The proposed approaches are implemented in Matlab/Simulink. Results indicate that input conditions have varying level of influences on the output based on the MFs used. It is generally observed that QoS fuzzy control with TMF gives a better performance than GMF. Typically, it is also noted that when the input conditions are selected at 50ms delay, 5ms jitter and 50% packet loss, we obtain 79% and 71% output responses with TMF and GMF, respectively. This shows that TMF method can control QoS in a multimedia transmission over ad hoc wireless network more effectively with good service output response than GMF. Generally, the paper shows that FL is capable of measuring network performance and predicting any QoS deterioration without complex mathematical calculation, to provide an improved QoS for customers' satisfaction. [ABSTRACT FROM AUTHOR]

The issues faced by Complementary metal oxide semi-conductor (CMOS) technology in the nanoregime have led to the research of other possible technologies which can operate with same functionalities however, with higher speed and lower power dissipation. One such technology is Quantum-dot Cellular Automata (QCA). At present, logic circuit designs using QCA have been comprehensively researched and one such application area being investigated is data transmission. Various data transfer techniques for reliable data transfer are available and among them convolution coding is being widely used in mobile, radio and satellite communications. Considering the evolution towards nano communication networks, in this paper an ultra-proficient designs of 1/2 rate and 1/3 rate convolution encoders based on a cost-efficient and fault tolerant XOR gate design have been proposed for application in nano communication networks. Based on the performance analysis, it is observed that the proposed designs are efficient in respect to cell count, area, delay and circuit cost and achieves performance improvement up to 40.21% for 1/2 encoder and 31.81% for 1/3 encoder compared to the best design in the literature. In addition to this, the energy dissipation analysis of the proposed designs is also presented. The proposed designs can thus be efficiently utilized in various nanocommunication applications requiring minimal area and ultra-low power consumption. [ABSTRACT FROM AUTHOR]

This paper presents a Filter Bank Multicarrier (FBMC), a viable waveform candidate for fifth generation (5G) communications using Staggered-Modulated Multitone (SMT). FBMC is preferred in optical communication because of its ability to work without Cyclic Prefix (CP). In any case, the operation of FBMC in optical access systems with Artificial Neural Networks (ANNs) has not been broadly explored either downstream or upstream. This work presents an advanced Nonlinear Feed-Forward Equalizer (NFFE) that makes use of multilayer ANN for dispersion compensation. ANN is trained to act as a filter with an extensive equalizer training which has the ability to mitigate dispersion and increase the performance of the system. The simulation work is used to study the performance of intensity modulated FBMC system with direct detection in Long Reach-Passive Optical Networks (LR-PONs).The transmission data rate is varied between 8 and 10 Gbps with the optical fiber length from 30 to 90 km of Standard Single Mode Fiber (SSMF). The obtained result suggests that FBMC system with ANN-NFFE equalizer fundamentally builds the resilience to the Chromatic Dispersion (CD) distortion, and a CP-less transmission is possible upto 90 km. [ABSTRACT FROM AUTHOR]

At these times, internet of things (IoT) technologies have become ubiquitous in the healthcare sector. Because of the increasing needs of IoT, massive quantity of patient data is being gathered and is utilized for diagnostic purposes. The recent developments of artificial intelligence (AI) and deep learning (DL) models are commonly employed to accurately identify the diseases in real-time scenarios. Despite the benefits, security, energy constraining, insufficient training data are the major issues which need to be resolved in the IoT enabled medical field. To accomplish the security, blockchain technology is recently developed which is a decentralized architecture that is widely utilized. With this motivation, this paper introduces a new blockchain with DL enabled secure medical data transmission and diagnosis (BDL-SMDTD) model. The goal of the BDL-SMDTD model is to securely transmit the medical images and diagnose the disease with maximum detection rate. The BDL-SMDTD model incorporates different stages of operations such as image acquisition, encryption, blockchain, and diagnostic process. Primarily, moth flame optimization (MFO) with elliptic curve cryptography (ECC), called MFO-ECC technique is used for the image encryption process where the optimal keys of ECC are generated using MFO algorithm. Besides, blockchain technology is utilized to store the encrypted images. Then, the diagnostic process involves histogram-based segmentation, Inception with ResNet-v2-based feature extraction, and support vector machine (SVM)-based classification. The experimental performance of the presented BDL-SMDTD technique has been validated using benchmark medical images and the resultant values highlighted the improved performance of the BDL-SMDTD technique. The proposed BDL-SMDTD model accomplished maximum classification performance with sensitivity of 96.94%, specificity of 98.36%, and accuracy of 95.29%, whereas the feature extraction is performed based on ResNet-v2 [ABSTRACT FROM AUTHOR]

This paper proposes an energy efficient approach for securing inter-connecting IOT devices with servers. A scheme using blockchain and a second network for security management was previously described [1]. To overcome the drawbacks and shortcomings of using traditional smart contract with Ethereum, a new approach is proposed. The proposed approach ensures that the overall IoT network is "hardened" against attack using a framework which is environmentally sustainable and meets the stringent requirements of mission critical applications. This new approach also results in shorter latency, higher throughput and consuming less power, thus suitable for edge computing environment in mobile. [ABSTRACT FROM AUTHOR]

Trustworthy and reliable applications built using intelligent software agents aim to provide improved performance using its characteristics. Agents introduced in various architectures represent its functionality as functional elements of the architecture and shows the interaction between other components present in the architecture. The Internet of things (IoT) reveals as a frequent technology that allows accessing the physical objects present in the world. IoT systems utilize wireless sensor network to transmit and receive data by establishing communication. Wireless Sensor Networks transmits digital signals to the cyber-world for analyzing and processing the information into useful data by either formulating or communicating with the intelligent and innovative system. While talking about IoT and WSN, agents introduced in such environments assist in making decisions quickly by perceiving the input from the environment. The number of agents needed for an application depends upon the complexity of the problem. Multi-Agent architectures discussed in the article describe their association, roles, functionality and interaction. This paper gives a detailed survey of various agent/multi-agent learning architectures introduced over IoT and WSN. Moreover, this survey with the performance and the SWOT analysis on the Agent-based learning architecture helps the reader and paves a way to pursue research on Agent-based architectural deployment over IoT and WSN paradigms. [ABSTRACT FROM AUTHOR]

With the substantial increase in the amount of data, the mismatch between the processing speed of the hardware and the software results in the 'Memory Wall' problem. Processing-in-memory (PIM), in which the compute and memory units are integrated, can avoid frequent data transmission. Binary neural network (BNN) uses binary weights and activations instead of full-precision weights and activations in the convolutional neural network, which reduces computational complexity with minor influence on accuracy. In this paper, we used a one-step operation to write a pair of SOT-MRAM cells and verified the two basic operations in BNN: XNOR and bitcount. Then, we employed an external control circuit with FPGA and accomplished 'I' single-character recognition based on vector-matrix multiplication in the SOT-MRAM array. [ABSTRACT FROM AUTHOR]

This paper mainly discusses how the strength of inter-community links affects the synchroni-zation state of the whole network and the individual community. It is found, when the inter-community link number is neither too small nor too large and the overall coupling strength takes right values, there will be an optimal inter-community link strength value, in which the community networks are in a balance region where the individual community is maximally independent, while the information transmission remains effective among different communi-ties. Combining the result of this paper and that of the number of inter-community links, it is easy to help us find the most effective community networks. [ABSTRACT FROM AUTHOR]

The reliability of board-level data communications intensively depends on the reliability of interconnections on a board. One of the most challenging interconnections reliability threats is intermittent resistive faults (IRFs). Detecting such faults is a major challenge. The main reason is the random behavior of these faults. They may occur randomly in time, duration and amplitude. The occurrence rate can vary from a few nanoseconds to months. This paper investigates IRF detection at the board level by introducing a new digital in situ IRF monitor. Hardware-based fault injection has been used to validate the proposed IRF monitor. As case studies, two widely used on-board transmission protocols namely the Universal Asynchronous Receiver Transmitter (UART) and the Serial Peripheral Interface bus (SPI), have been used. In addition, one fault management framework, based on the IJTAG standard, has been implemented to collect and characterize information from the monitors. The experimental results show that the proposed monitor is effective in detecting IRFs at the board level. [ABSTRACT FROM AUTHOR]

Data security, privacy and authenticity are crucial in wireless data transmission. Low power consumption is the main requirement for any chip design targeting the Internet of Things (IoT) applications. In this research paper, a comparative study of eight authenticated encryption and decryption algorithms, selected from the "Competition for Authenticated Encryption: Security, Applicability and Robustness" (CAESAR), namely, ACORN, ASCON, CLOC, JOLTIK, MORUS, PRIMATEs, SCREAM and SILC, is presented. The FPGA and ASIC implementations of these eight algorithms are synthesized, placed and routed. Power, area, latency and throughput are measured for all algorithms. All results are analyzed to determine the most suitable algorithm for IoT applications. These results show that ACORN algorithm exhibits the lowest power consumption of the eight studied at the expense of lower throughput and higher latency. MORUS algorithm gives the highest throughput among the eight selected algorithms at the expense of large area utilization. [ABSTRACT FROM AUTHOR]

High-speed, low-power analog-to-digital converter (ADC) is a critical element for 5-GBd, 20-Gb/s digital signal processing (DSP)-based coherent optical communication receiver. To satisfy high data transmission rate requirement of optical receiver, a single-core and open-loop flash ADC with a new proposed multiplexer-based encoder is presented in this paper. Compared with conventional encoder topology, the new proposed topology achieves the fastest encoding speed and lowest power consumption. The optimized distortion is achieved by utilizing a leakage current compensation technique and a local negative feedback method in switched-buffer track-and-hold amplifier (THA). Strict synchronization is obtained for clock signals by careful designing of layout in tree-based clock networks. Furthermore, a master–slave comparator incorporated with a preamplifier reduces signal-dependent kickback noise as well as offset voltage. By using master–slave comparators and proposed encoders, the sampling rate is up to 21.12 GS/s. The 4-bit, 20-GS/s flash ADC is realized in 0.13- μ m SiGe BiCMOS technology and it only occupies 1.05 mm × 1.46 mm chip area. With a power consumption of 1.831 W from 4-V supply, the ADC achieves an effective number of bits (ENOB) of 2.5 at 15 GS/s. [ABSTRACT FROM AUTHOR]

Symmetric and asymmetric cryptographic algorithms are used for a secure transmission of data over an unsecured public channel. In order to use these algorithms in real-time applications, many flexible hardware architectures have been proposed and implemented with multiple design constraints. Therefore, a systematic study is required to analyze various implementation approaches. This paper has focused on the identification and classification of recent research practices pertaining to the flexible hardware implementation of cryptographic algorithms. We have used Systematic Literature Review (SLR) process to identify 51 research articles, published during 2008–2017. The identified researches have been classified according to three design approaches: (1) crypto processor, (2) crypto coprocessor and (3) multicore crypto processor. Consequently, a comparative analysis of various cryptographic algorithms in terms of flexibility, throughput, area, power and implementation technology has been presented. A comprehensive investigation of flexible architectures for implementing cryptographic algorithms facilitates researchers and designers of the domain to select an appropriate design approach for a particular algorithm and/or application according to their needs. [ABSTRACT FROM AUTHOR]

In this paper, a soft decoding method is proposed for QAM-modulated coded OFDM systems. This technique efficiently mitigates the distortion caused by clipping the oversampled-OFDM signals. Because the main advantage of an OFDM system is its robustness in fading channels, where this system turns a frequency selective channel into a set of parallel flat non-selective fading sub-channels, in this paper, we analyze the performance of the proposed method over flat fading Rician sub-channels. Our simulation results show that the proposed soft decoding technique significantly outper-forms the conventional hard decoding method. [ABSTRACT FROM AUTHOR]

A major challenge facing firms competing in electronic business markets is the dynamic integration of knowledge within and beyond the firm, enabled by internet-based infrastructure and emergent fluid socio-technical networks. This paper explores how social actors dynamically employ intranets to integrate formal and informal knowledge within evolving socio-technical networks that emerge, permeate and extend beyond the organisational boundary. The paper presents two case studies that illustrate how static intranets can be useful for dynamically integrating knowledge when they are interwoven with other knowledge channels such as e-mail through which flows the informal knowledge needed to make sense of and situate formal organisational knowledge. The findings suggest that businesses should carefully examine how employees integrate intranets with other channels in their work, and the shaping of knowledge outcomes that flows from such use. There are practical implications for the proper skilling of the people who share and integrate knowledge in this way. The paper also provides a framework for dynamic knowledge integration in socio-technical networks, which can help underpin future research in this area. [ABSTRACT FROM AUTHOR]

A highly secure communication method is essential for end users for the exchange of information which is not interpreted by an intruder. Cryptography plays a crucial role in the current and upcoming digital worlds, for secure data transmission in wired and wireless networks. Asymmetric and symmetric cryptographic algorithms encrypt data against vulnerable attacks and transfer to authenticated users. Steganography is a method for providing secure information with the help of a carrier file (text, video, audio, image, etc.). This paper proposes Deoxyribonucleic Acid (DNA)-based asymmetric algorithm which is used to encrypt the patient's secret information and its performance is compared with ElGamal, RSA and Diffie–Hellman (DH) cryptographic algorithms. The proposed asymmetric algorithm is applied to image steganography which is used for encrypting and concealing the patient's secret information in a cover image. The proposed method consumes less hardware resources with improved latency. Dynamic Partial Reconfiguration (DPR) allows to transform a selective area rather than complete shutdown of the entire system during bitstream configuration. Cryptosystem with DPR is designed, synthesized in Xilinx Vivado and simulated in Vivado simulator. The design is targeted at Basys3, Nexys4 DDR and Zync-7000 all-programmable SOC (AP SoC) architectures and programmed with secure partial bit files to avoid vulnerable attacks in the channel. [ABSTRACT FROM AUTHOR]

Code error correction methods have been important techniques at a radio environment and video stream transmission. In general, when a server transmits some data packets to a client, the server resends the only loss packets. But in this method, a delay occurs in a transmission. In order to prevent the transmission delay, the loss packets are restored by the error correction packet on a client side. The code error correction method is called Hybrid Automatic Repeat reQuest (ARQ) and has been researched. On the other hand, congestion control schemes have been important techniques at a data communication. Some packet losses are generated by network congestion. In order to prevent some packet losses, the congestion control performs by prolonging packet transmission intervals, which is called High-performance and Flexible Protocol (HpFP). In this paper, we present a stochastic model of congestion control based on packet transmission interval with Hybrid ARQ for data transmission. That is, if the packet loss occurs, the data packet received in error is restored by the error correction packet. Moreover, if errors occur in data packets, the congestion control performs by prolonging packet transmission intervals. The mean time until packet transmissions succeed is derived analytically, and a window size which maximizes the quantity of packets per unit of time until the transmission succeeds is discussed. [ABSTRACT FROM AUTHOR]

The blurring of texture edges often occurs during image data transmission and acquisition. To ensure the detailed clarity of the drag-time images, we propose a time image de-noising method based on sparse regularization. First, the image pixel sparsity index is set, and then an image de-noising model is established based on sparse regularization processing to obtain the neighborhood weights of similar image blocks. Second, a time image de-noising algorithm is designed to determine whether the coding coefficient reaches the standard value, and a new image de-noising method is obtained. Finally, the images of electronic clocks and mechanical clocks are used as two kinds of time images to compare different image de-noising methods, respectively. The results show that the sparsity regularization method has the highest peak signal-to-noise ratio among the six compared methods for different noise standard deviations and two time images. The image structure similarity is always above which shows that the proposed method is better than the other five image de-noising methods. [ABSTRACT FROM AUTHOR]

Genomic data nowadays is playing a vital role in number of fields such as personalized medicine, forensic, drug discovery, sequence alignment and agriculture, etc. With the advancements and reduction in the cost of next-generation sequencing (NGS) technology, these data are growing exponentially. NGS data are being generated more rapidly than they could be significantly analyzed. Thus, there is much scope for developing novel data compression algorithms to facilitate data analysis along with data transfer and storage directly. An innovative compression technique is proposed here to address the problem of transmission and storage of large NGS data. This paper presents a lossless non-reference-based FastQ file compression approach, segregating the data into three different streams and then applying appropriate and efficient compression algorithms on each. Experiments show that the proposed approach (WBFQC) outperforms other state-of-the-art approaches for compressing NGS data in terms of compression ratio (CR), and compression and decompression time. It also has random access capability over compressed genomic data. An open source FastQ compression tool is also provided here (http://www.algorithm-skg.com/wbfqc/home.html). [ABSTRACT FROM AUTHOR]

Bandwidth limitation is a vital problem for high-speed data transmission in logging cable telemetry systems (LCTSs). This paper proposes a frequency compensation method with an analog circuit design, possessing high flexibility and robustness. Analytical expressions are derived for the relationship between pole-zero and gain, deviations caused by high temperature; and are then verified via simulation. To address the efficacy of the circuit design, a real case with low computation complexity and high accuracy is proposed and employed. The case of a 7km LCTS shows frequency compensation with a 200% bandwidth expansion - from 160kHz at 55dB of the original cable to 300kHz at 3dB - and a 60dB improvement in high frequency gain. After comparing the signals with and without compensation, the improvements in transmission performance by the proposed pre-emphasis circuit and equalizer are confirmed. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the behavior of biological tissues (skin) coupled to a substrate (sensor) based on a numerical model taking into account the relationship between strain/stress components at the interface. Based on this study, we understand and quantify the most appropriate biomechanical factors in order to optimize sensor/biological tissue interface conditions. A micromechanical description based on a mathematical formulation has been developed to evaluate the biomechanical behavior provided by a 2D viscoelastic model of Kelvin–Voigt. The results show a spatio-temporal law of tissue motion highlighting the need for an optimized interface for reliable data transmission in the case of connected device in a dynamic movement or in the manufacturing of intelligent and reactive prosthesis device. [ABSTRACT FROM AUTHOR]

Efficient workflow scheduling plays a critical role in achieving high performance in heterogeneous distributed computing systems. Given its key importance, workflow scheduling has been extensively studied, and various algorithms have been proposed in the literature mainly for systems with homogeneous or heterogeneous processors. Most of the algorithms leverage the average computation cost to prioritize tasks, and few focus on the combination of the level and out-degree of tasks, which both have a considerable impact on scheduling. A new list scheduling algorithm called level and out-degree earliest finish time (LOEFT) is proposed in this paper to address the problem of static workflow scheduling in a heterogeneous computing environment to reduce the workflow execution time. This algorithm has three major phases: task leveling, task prioritization and processor selection. In the task leveling phase, tasks are categorized into different groups based on depth value to ensure data transmission completeness. In the task prioritizing phase, the upward rank value is combined with the out-degree of every task to calculate the heterogeneous priority rank value on different processors and leverage the value to sort all tasks. In the processor selection phase, the selected task is assigned to the processor, which minimizes the former's earliest finish time. The experimental simulation of randomly generated DAG and real-world application workflows proves that the LOEFT algorithm can significantly reduce the workflow execution time. [ABSTRACT FROM AUTHOR]

Data security is critical in wireless sensor networks (WSNs) because communication signals are highly available due to data transmission in free space. Attacks ranging from passive eavesdropping to active snooping are more common on these networks. This paper proposes secure data transfer using data encryption based on the improved Rivest–Shamir–Adleman (RSA) with Diffie–Hellman (DH) key exchange algorithm (IRSA-DH). For this purpose, the adaptive distance-based agglomerative hierarchical (ADAH)-based clustering method is used. Then the cluster head (CH) is selected using the improved weight-based rain optimization (IWRO) to improve the network's lifespan. This study aims to design a secure group communication method for WSNs. In order to generate and distribute the key to the group, the RSA and DH and key exchange algorithm had been hybridized with the Key Management Center (KMC). For safe communication between users, the key exchange technique is investigated. The performance measures such as throughput, packet loss ratio (PLR), packet delivery ratio (PDR), latency, energy consumption, end-to-end delay (EED) and network lifetime are analyzed and compared with the existing approaches. [ABSTRACT FROM AUTHOR]

This paper presents a formal and model driven design approach for a high speed data transmission channel. The formal process algebra communicating sequential processes (CSP) was used to specify the system functionality. Automated model checking established, beyond reasonable doubt, important system properties, such as freedom from deadlock and livelock. Once these properties were established, the functionality was translated into an implementation which realizes high speed data transmission between two independent IC chips. Normal and failure case testing ensured that the implementation complies with the specification. This work shows how formal and model driven design methodologies speed up the process of turning ideas into physical problem solutions. More specifically, formal modeling gave us firm understanding and deep insight of the system functionality which enabled us to implement and to select correct system components. [ABSTRACT FROM AUTHOR]

This paper intends to increase the network lifetime of Wireless Multimedia Sensor Network (WMSN) by reducing the energy consumption for multimedia data transmission. To accomplish this, the optimal transmission radius of the transmitting sensor nodes and appropriate selection of optimal Cluster Head (CH) at every round are integrated with the energy consumption model to act as the cost model. Subsequently, we develop a new hybrid optimization model, termed as NC-GSO, that hybridizes the Glowworm Swarm Optimization (GSO) and Dragonfly (DA) Optimization. The proposed algorithm is used to minimize the cost function so that the optimal transmission radius and the CHs are determined. The performance of the proposed methodology is investigated in a simulated WMSN environment in which the enhanced network lifetime and the residual energy of the sensors are compared against the state-of-the-art algorithms. To ensure a fair comparison, statistical analysis is also conducted. The obtained results demonstrate the performance of the proposed algorithm in enhancing the lifetime of WMSN. [ABSTRACT FROM AUTHOR]