Research on Heterogeneous Communication Network for Power Distribution Automation

This paper addresses web object size which is one of important performance measures and affects to service time in multiple access environment. Since packets arrive according to Poission distribution and web service time has arbitrary distribution, M/G/1 model can be used to describe the behavior of the web server system. In the time division multiplexing (TDM), we can use M/D/1 with vacations model, because service time is constant and server may have a vacation. We derive the mean web object size satisfying the constraint such that mean waiting time by round-robin scheduling in multiple access environment is equal to the mean queueing delay of M/D/1 with vacations model in TDM and M/H2/1 model, respectively. Performance evaluation shows that the mean web object size increases as the link utilization increases at the given maximum segment size (MSS), but converges on the lower bound when the number of embedded objects included in a web page is beyond the threshold. Our results can be applied to the economic design and maintenance of web service.

SummaryWith the development of Internet of Things (IoT)‐related technologies and artificial intelligence (AI) technologies, various IoT services are becoming more intelligent, and their use range is increasing and diversifying. IoT hardware and IoT software must support AI‐related functions to provide an intelligent IoT service. In general, IoT devices powered by batteries have limited computing performance when compared to general computing environments. Therefore, it is essential to provide AI‐related functions at low power in IoT devices to implement and offer various intelligent services. Neuromorphic computing devices or neuromorphic computing architectures can operate with low power energy consumption. If applied to IoT devices, AI‐related functions can be implemented in a resource‐constrained IoT device environment. The proposed neuromorphic architecture abstraction (NAA) model dynamically selects the proper neuromorphic architecture by comparing the parameter size of a given SNN model. It also considers the specifications and error probability of the available neuromorphic architecture. We also implement the proposed model in a real IoT computing environment and show that the proposed NAA model and dynamic selection scheme can reduce the execution time for training and inferencing. It reduces the training and inferencing time of a given model compared with the method of randomly specifying the neuromorphic architecture.

Wireless and mobile networks have experienced great success over the past few years. However, any single type of wireless and mobile network cannot provide all types of services, e.g., wide coverage and high bandwidth. An integrated wireless and mobile network is introduced by combining these different types of wireless and mobile networks, which can provide more comprehensive services. In an integrated wireless and mobile network, a mobile terminal that is equipped with heterogeneous network interfaces is capable of accessing all the available networks. Therefore, how to select a desired network is an important issue for the integrated wireless and mobile network. Although some network-selection strategies have been proposed, most of them are designed to meet a user's individual needs, such as the bandwidth, the access fee, or the power consumption. The system performance also has not been touched. In this paper, we propose a cost-function-based network selection (CFNS) strategy in an integrated wireless and mobile network from a system's perspective, which also considers a user's needs. We also analyze the system performance of the proposed network-selection strategy by using a theoretical model and extensive simulations. The results obtained show that the proposed network-selection strategy affects multiple system parameters, which needs to be handled carefully.

Providing service continuity to the end users with best quality is a very important issue in the next generation wireless communications. With the evolution of the mobile devices towards a multimode architecture and the coexistence of multitude of radio access technologies (RAT's), the users are able to benefit simultaneously from these RAT's. However, the major issue in heterogeneous wireless communications is how to choose the most suitable access network for mobile's user which can be used as long as possible for communication. To achieve this issue, this paper proposes an intelligent network selection strategy which combines two multi attribute decision making (MADM) methods such as analytic network process (ANP) and the technique for order preference by similarity to an ideal solution (TOPSIS) method. The ANP method is used to find the differentiate weights of available networks by considering each criterion and the TOPSIS method is applied to rank the alternatives. Our new strategy for network selection can dealing with the limitations of MADM methods which are the ranking abnormality and the ping-ponf effect.

The proposal of the blockchain 3.0 architecture represented by Hyperledger Fabric simplifies the process of each node participating in the blockchain network so that a large number of IoT devices can be quickly integrated into the network. However, the participating institutions in the field of power Internet of Things are complex, the performance of participating nodes is not uniform, and the load imbalance caused by it makes it impossible to meet the transaction throughput requirements of the business. In this paper, we established a Zookeeper-based endorser node performance monitoring module and replaced the original random selection strategy with a dynamic endorser node selection strategy based on the available resources of the node, effectively alleviating the endorsement pressure of a single node in high concurrency scenarios, thereby improving the overall concurrent processing capabilities. It is worth noting that our optimization is pluggable and does not make any changes to the interface of the Hyperledger Fabric, and it does not weaken the usability of the system. By comparing the existing architecture with our design, it is found that this dynamic decision-making endorser node selection strategy can help select more appropriate nodes for endorsement according to the node’s system resources and real-time load conditions, thus improving the concurrency of the system.KeywordsHyperledger fabricEndorser node selectionConcurrencyZookeeper

Network selection is a critical task for mobile terminals moving in heterogeneous environment of next-generation wireless networks. Power consumption of mobile terminal is a matter of great concern in the present scenario for efficient network selection in integrated network of various wireless technologies. In this paper, multiple attributes decision-making-based dynamic network selection method PV–VPP is proposed by considering power consumption of mobile terminal at instantaneous battery level in heterogeneous networks.

Full waveform inversion (FWI) is a technique used to estimate subsurface model parameters by minimizing the difference between observed and calculated seismic data. Sparsity-promoting regularization are useful tools for traditional FWI methods to tackle complex subsurface structures. Since the traditional regularization techniques can only impose some fixed priors, it is necessary to develop a regularization strategy to obtain more flexible priors. In this way, we develop a structural sparse representation method that exploits the non-local self-similarity prior of the model, which is achieved by grouping similar patches using graph matching operators and a dynamic group selection strategy. A group-based dictionary is trained with the aim of providing the best sparse representation of complex features and variations in the entire model perturbation. The dynamic selection strategy of the training method can balance computational efficiency and inversion accuracy by constantly updating and retaining groups during the processing. In addition, two loop algorithm framework is utilized to enhance the robustness and the efficiency of the proposed method. Numerical experiments are presented to demonstrate that the proposed method outperforms the total variation regularization method and the adaptive dictionary learning with non-local self-similarity in terms of robustness and resolution. This structural sparsity-promoting regularization is incorporated into the FWI problem through a two-loop algorithm framework, enhancing the robustness and efficiency of FWI results.

The powerful benefits of multi-antenna systems can be obtained by cooperative communications among users in multiple access environments without the need for physical arrays. This paper studies a novel cooperative signaling strategy that achieves high performance and low implementation complexity for synchronous code division multiple access (CDMA) wireless mobile networks. The validity of the proposed strategy under slow flat Rayleigh fading channel plus additive white Gaussian noise (AWGN) is verified through closed-form error probability expressions and Monte-Carlo simulations. A variety of analytical results reveal that the new cooperative strategy significantly outperforms direct transmission subject to the same spectral efficiency and transmit power constraint.

It is argued that iterative signal cancellation receivers, with or without the use of error control coding, are preferred for practically viable multiuser detection. Achievable spectral efficiencies are calculated for both cases and arguments are given on how to achieve maximum spectral efficiencies by rate or power layering of the different users in a multiple access environment. The achievable spectral efficiencies of iterative cancellation receivers, which include error control codes, are compared to those which do not. The latter are found to be essentially viable only in power controlled environments.

This paper investigates the effects of using error-and-erasure decoding in coded parallel combinatorial spread spectrum (PC/SS) systems over Rayleigh fading channels. The PC/SS system is an advanced multi-code direct sequence spread spectrum system for high-speed data transmission. Our previous works have shown that the Reed-Solomon (RS) coded PC/SS systems provide significant improvement in error rate performance over conventional DS/SS systems. To achieve further performance improvement in the PC/SS systems, error-and-erasure decoding techniques are implemented in the RS coded PC/SS receiver. To obtain the erasure location information, a threshold for the signal-to-noise ratio is set at the correlator output. Numerical results show that the coded PC/SS systems with error-and-erasure decoding provides significant improvement in the bit error rate (BER). With errors-only decoding, the PC/SS systems cannot improve the error rate performance because of large SNR penalty introduced by coding. On the contrary, error-and erasure decoding still improves the performance of PC/SS systems under multiple access environment.

The effects of filtering in transmitters on the bit error performance of a binary asynchronous direct sequence spread spectrum communication system are examined in a multiple access environment. Computer simulations are carried out to evaluate the effects of non-linear phase Chebyshev and Butterworth filters and linear phase Bessel, Gauss and Nyquist roll-off filters. The performance degradation of the system is compared and discussed in terms of the BT product of the filter or the transmitted spectrum. >

We propose a zero correlation duration-ultra wideband (ZCD-UWB) wireless communication system based on the direct sequence ultra wideband (DS-UWB) scheme and special spreading sequences with zero correlation duration (ZCD) characteristics (Cha, J.S. et al., Electron. Lett., vol.36, no.11, p.991-3, 2000). Especially, we propose a ternary ZCD-UWB communication system having a novel interference-cancellation property. After constructing an enhanced ternary ZCD sequence and mathematical model for a ZCD-UWB wireless system, we present the theoretical bit error rate (BER) performance. By computer simulation, we verify the high system capacity of the proposed system and a performance superior to the conventional Walsh-based DS-UWB systems in multipath and in multiple access environments. We show that the proposed system can remove the interference signal perfectly without employing complicated hardware, such as multiuser detection (MUD) or other interference cancellation techniques.

This paper describes the Computer Network installed at a Steel Plant in Central India for Traffic Management function. The movement of Railway Wagons and Locomotives used for loading and unloading of material in the Steel Plant is managed by an on-line computerised information system. The system comprises of one mini computer installed at a central site and 20 personal computers installed at remote sites. The data communication between the mini computer and remote PCS takes place through Radio links in a multiple access environment.

Transform domain communication system (TDCS) and wavelet domain communication system (WDCS) have been reported to have interference avoiding capability under adverse environmental conditions. These systems achieve low probability of intercept (LPI) and orthogonality simultaneously by using the pseudorandom (PR) sequences for generating the phase vector of the basic function. Conventionally, the PR phase vectors in TDCS and WDCS were generated by a maximal length binary PR sequence (m-sequence), which allows only a relatively small number of users in the systems. This paper reports a method to increase the user capacity of TDCS and WDCS by applying Gold sequence to generate the PR phase vector of the basic function. The increased user capacity of the systems based on Gold sequence is tabulated. Simulation results also demonstrate that by using Gold sequences for the PR phase generation, both TDCS and WDCS can provide a comparable interference avoiding capability with a larger user capacity, compared to those of the systems based on m-sequences in multiple access environments.

Taking the mobile edge computing paradigm as an effective supplement to the vehicular networks can enable vehicles to obtain network resources and computing capability nearby, and meet the current large-scale increase in vehicular service requirements. However, the congestion of wireless networks and insufficient computing resources of edge servers caused by the strong mobility of vehicles and the offloading of a large number of tasks make it difficult to provide users with good quality of service. In existing work, the influence of network access point selection on task execution latency was often not considered. In this paper, a pre-allocation algorithm for vehicle tasks is proposed to solve the problem of service interruption caused by vehicle movement and the limited edge coverage. Then, a system model is utilized to comprehensively consider the vehicle movement characteristics, access point resource utilization, and edge server workloads, so as to characterize the overall latency of vehicle task offloading execution. Furthermore, an adaptive task offloading strategy for automatic and efficient network selection, task offloading decisions in vehicular edge computing is implemented. Experimental results show that the proposed method significantly improves the overall task execution performance and reduces the time overhead of task offloading.