The International Telecommunications Union defines in its IMT‐2020 recommendations three types of use of 5G services: mMTC (massive Machine‐type Communications), eMBB (enhanced Mobile Broadband), and uRLLC (ultra‐Reliable Low Latency Communications). The mMTC service allows a considerable number of machines and devices to communicate while guaranteeing a good quality of service. The eMBB service allows

Convolutional neural network (CNN) inference usually runs on high‐performance graphic processing units (GPUs). Since GPU is a high power consumption unit, that makes the energy consumption increases sharply due to the deep learning tasks. The energy efficiency of CNN inference is not only related to the software and hardware configurations, but also closely related to the application requirements of

In this article, we present two deterministic leader election algorithms for programmable matter on the face‐centered cubic grid. The face‐centered cubic grid is a three‐dimensional 12‐regular infinite grid that represents an optimal way to pack spheres (i.e., spherical particles or modules in the context of the programmable matter) in the three‐dimensional space. While the first leader election algorithm

In cloud datacenter network, deadline‐aware disaster evacuation transfers the endangered data out of disaster zone using limited residual network resources. Previous work has not jointly considered the selection of safe datacenter and reasonable allocation of bandwidth proportion in time‐varying postdisaster network environment. Therefore, they cannot make full use of network transmission capability

Gesture recognition has always been a research hotspot in the field of human‐computer interaction. Its purpose is to realize the natural interaction with the machine by recognizing the semantics expressed by gesture. In the process of gesture recognition, the occlusion of gesture is an inevitable problem. In the process of gesture recognition, some or even all of the gesture features will be lost due

The growing popularity of users in online social network gives a big opportunity for online auction. The famous Information Diffusion Mechanism (IDM) is an excellent methods even meet the incentive compatibility and individual rationality. Although the existing auction in online social network has considered the buyers' information has not known by the seller, current mechanism still cannot preserve

With the improvement of informatization and the development of computer technology, identity recognition with fingerprint has been the growing trend, but the stained fingerprint will make recognition difficult. To solve the above problem, this paper briefly introduced the traditional point matching fingerprint recognition algorithm and the damaged fingerprint recognition method based on the convolution

Dragonfly algorithm (DA) is a new swarm intelligence optimization algorithm based on the static and dynamic swarm behavior of dragonflies. The algorithm has the characteristics of simple structure, strong search ability, easy implementation, and strong robustness. However, the DA algorithm itself also has insufficient solution accuracy and slow convergence speed. The Wind Driven Optimization algorithm

This paper presents how parallel advanced graph partitioning algorithms can be designed and improved with the use of global application states monitoring of distributed programs. The proposed algorithms have been implemented inside a novel distributed program design framework Program Execution Governed by Asynchronous Supervision of States in Distributed Applications (PEGASUS DA). This framework provides

With the development and popularization of Internet technology, network security has become the focus of attention. Vulnerabilities and back doors are regarded as two of the main reasons of network security problems. Dynamic heterogeneous redundant (DHR) architecture is a typical framework of cyberspace mimic defense. It can make use of untrusted hardware and software components to construct a high

Deep neural networks have been demonstrated to be useful in varieties of intelligent tasks, and various specialized NN accelerators have been proposed recently to improve the hardware efficiency, which are typically equipped with software‐managed scratchpad memory (SPM) for high performance and energy efficiency. However, traditional SPM management techniques cause memory fragmentation for NN accelerators

In this article, we propose a new criterion for a switching algorithm to be used in MIMO‐OFDM systems. The switching algorithm, which selects between spatial multiplexing and MIMO diversity using the Demmel condition number as selection metrics, is first analyzed. Then, we show the limitation of this criterion, when increasing the receive antenna number. As a solution, we propose multiantenna processing

Predicting the daily tourism flow of scenic spots is of great significance for improving the management quality and the tourist experience. Affected by complex factors, daily tourism flow data have strong nonlinear characteristics. In this article, a multilayer neural network S‐CNNLSTM is put forward to make accurate short‐term tourism flow prediction. First, to reduce the redundant information between

Massive progress and fruitful results have been achieved since the implementation of the Belt and Road Initiative (B&R). However, the risk of exchange rate between countries along the Belt and Road cannot be ignored. In this paper, we propose a B&R exchange rate index to evaluate the currency risk of countries along the B&R, along with a research on the multiscale features of the B&R exchange rate

High performance system‐on‐chip (SoCs) designs have led to high‐density integrated circuits using field programmable gate arrays (FPGAs) for rapid prototyping and reconfigurable digital circuits. Using FPGA reconfigurability, it is possible to design a configurable network‐on‐chip (NoC) for different applications. NoC architectures provide efficient communication infrastructures for implementing very

Traffic bottlenecks dynamically change with the variance of traffic demand. Identifying traffic bottlenecks plays an important role in traffic planning and provides decision making. However, traffic bottlenecks are difficult to identify because of the complexity of traffic road networks and many other factors. In this article, we propose an influence spreading based method to find the dynamic changed

This article provides a comprehensive study of OpenCL heterogeneous programming for porting applications to CPU–GPU computing platforms, with a real‐life application for the solidification modeling. The aim is to achieve a flexible workload distribution between available CPU–GPU resources and optimize application performance. Considering the solidification application as a use case, we explore the

Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications. Here, we propose a task‐based scheme for parallelizing it, with quasi‐linear speedup over large problems. This type of parallel applications is challenging, because several tasks might be computing the same region. In this article, we are presenting the algorithm itself with

For the problem of surface electromyography (sEMG) gesture recognition, considering the fact that the traditional machine learning model is susceptible to the sEMG feature extraction method, it is difficult to distinguish the subtle differences between similar gestures. The NinaPro DB1 dataset is used as the research object, and the sEMG feature image and the Convolutional Neural Network (CNN) are

Outsourcing data to cloud servers is a popular service for data owners, however, how to check the integrity and freshness of the outsourced data is very challenge. Recently, Jin et al. proposed a cloud auditing protocol with full integrity and freshness support for cloud data, unfortunately in this article, we show their proposal is not secure. Concretely, the cloud servers can forge the authentication

In this work, we perform the feasibility analysis of a multi‐grained parallel version of the Zielonka Recursive (ZR) algorithm exploiting the coarse‐ and fine‐ grained concurrency. Coarse‐grained parallelism relies on a suitable splitting of the problem, that is, a graph decomposition based on its Strongly Connected Components (SCC) or a splitting of the formula generating the game, while fine‐grained

Web scraping is the process of extracting data from web pages and it is an essential part for the generation of datasets. Currently the field is dominated by capable commercial applications, however, there is always a need for web crawling and web scraping applications for custom projects. Developing fit for purpose tools for retrieving and structuring data from web services, cloud systems, and big

The problem of convergence and diversity in the course of population evolution is difficult to be balanced for solving the many‐objective optimization problem (MaOP). To track with the problem, a many‐objective optimization algorithm is designed. In the algorithm, a hybrid selection mechanism under the concurrent integration strategy is built to improve algorithm performance by employing the different

Community detection is a fundamental research problem in social networks. However, most existing research focuses on homogeneous networks while ignoring the multitopology and attributes in social media. In this article, we propose community detection algorithms based on community kernels to detect high‐quality communities in heterogeneous social networks. It is noticed that the social community has

Kalman filter (KF) is one of the most important and common estimation algorithms. We introduce an innovative designing of Kalman filter algorithm based on domain decomposition (we call it DD‐KF). DD‐KF involves decomposition of the whole computational problem, partitioning of the solution and a slight modification of KF algorithm allowing a correction at run‐time of local solutions. The resulted parallel

Insights from geohash coding algorithms introduce significant opportunities for various spatial applications. However, these algorithms require massive storage, complex bit manipulation, and extensive code modification when scaled to higher dimensions. In this article, we have developed a two‐bit geohash coding algorithm that divides the search space into four equal partitions where each partition

Solid state drives (SSDs) built upon MLC NAND flash memories suffer from a low lifetime endurance induced by continuously scaling‐down feature sizes and increasing bit density per cell. To cost‐effectively address this problem, we propose to integrate both hierarchical data redundancy and heterogeneous flash memory techniques into the SSD, named H2‐SSD. Through deploying across‐chips data redundancy

Online social networks (OSNs) have become one of the most popular platforms where people communicate by sharing contents and personal information. The interactions performed by the users allow to identify the homophily between users and reveal the presence of several communities that could depend on several factors: such as the type of relationships (eg, colleagues and school mates) or to users' preferences

The elderly care station is a new concept, which is the terminal service institution of the home‐based elderly care system in Beijing. Because its supervision of service quality (SQ) is not standardized and its current subsidy is irrelevant to SQ, this paper provides a framework for an evaluation system of the elderly care station. An SQ evaluation index system for the elderly care station is designed

Blockchain is a decentralized transaction and data management solution, the technological leap behind the success of Bitcoin and other cryptocurrencies. As the variety of existing blockchains and distributed ledgers continues to increase, adopters should focus on selecting the solution that best fits their needs and the requirements of their decentralized applications, rather than developing yet another

This article presents a high‐level synthesis implementation of the longest common subsequence (LCS) algorithm combined with a weighted‐based scheduler for comparing biological sequences prioritizing energy consumption or execution time. The LCS algorithm has been thoroughly tailored using Vivado High‐Level Synthesis tool, which is able to synthesize register transfer level (RTL) from high‐level language

Large‐scale problems in engineering and science often require the solution of sparse linear algebra problems and the Krylov subspace iteration methods (KM) have led to a major change in how users deal with them. But, for these solvers to use extreme‐scale hardware efficiently a lot of work was spent to redesign both the KM algorithms and their implementations to address challenges like extreme concurrency

Modern information systems are continuously collecting and storing large volumes of business process event logs. The analysis of event logs can provide valuable insights for business process re‐engineering and enhancement. Process discovery, as one of the most challenging event log analysis techniques, aims to discover a business process model from an event log. Many process discovery approaches have

With the development of the Internet of Things (IoT) technology, various attacks and threats have emerged. The advanced persistent threat (APT) refers to a class of advanced multiple‐steps attacks among diverse attack activities, which brings severe threats to the IoT systems ascribe to its pertinence, concealment, and permeability. However, the existing technologies and methods fail to timely recognize

Wireless sensor networks (WSNs) are composed of sensors exchanging the information that they collect from the environment. The use of a scheduler offers an efficient solution to eliminate information redundancy and possible collisions in this network. A scheduler is responsible for choosing the sensors to exchange information at each step of the algorithm's execution. This article presents a WSN handshake

In the wireless sensor networks energy consumption is broadest and widely explored area of research. The solution for energy optimization encompasses various techniques such as efficient routing protocols, data scheduling, clustering, hardware redesigning, supervised and unsupervised network learning algorithm, and so forth. Compared with all the methods that has been so far discussed, swarm intelligence

Service choreographies support a distributed composition approach that is based on the specification of the external interaction of the participant services in terms of flows of message exchanges, given from a global perspective. When developing distributed service‐based applications, different services are produced by different teams; at the same time, such choreographies can also interact with third‐party

Scheduling and resource allocation in clouds is used to harness the power of the underlying resource pool. Service providers can meet quality of service (QoS) requirements of tenants specified in Service Level Agreements. Improving resource allocation ensures that all tenants will receive fairer access to system resources, which improves overall utilization and throughput. Real‐time applications and

Radix sorting is an essential basic data processing operation in many computer fields. It has important practical significance to accelerate its performance through Graphic Processing Unit (GPU). The heterogeneous parallel computing technology attracts much attention and is widely applied for its effective computation efficiency and parallel real‐time data processing capability. Taking advantage of

Internet of Things (IoT) is utilized as an emerging sample for defining the future of technology in which physical items like sensors, radio‐frequency identification tags, mobile phones, actuators, and so on, can have interaction together and have cooperation with their neighbors for obtaining joint objectives. The performance of the deployed tasks and applications on the network is considered as one

In a vehicular ad hoc network (VANET) each node is required to transmit periodic and event‐driven messages. The periodic messages are also known as beacons and consist of the basic vehicle status, such as position, speed, direction, and any additional information required by a safety application. One of the main concerns faced with this technology is channel congestion, which often happens in scenarios

Aiming at the typical phenomenon of Shanghai historic landscape islands, the article adopts cellular automaton (CA) smart research method to determine historic landscape island constraint planning factors in accordance with the status quo and characteristics of islands. Taking Shanghai Moller Villa as example, the article standardizes and rasterizes constraint planning factors and therefore affords

This article investigates the multi‐GPU performance of a 3D buoyancy driven cavity solver using MPI and OpenACC directives on multiple platforms. The article shows that decomposing the total problem in different dimensions affects the strong scaling performance significantly for the GPU. Without proper performance optimizations, it is shown that 1D domain decomposition scales poorly on multiple GPUs

Breast cancer is the most common tumor that seriously threatens the life of women. However, with imprecise measure methods, the detection results are not reliable enough, and this will bring more pain and cost to patients. Therefore, accurate identification of breast cancer is a very important issue. To tackle this problem, a composite firefly algorithm (named CoFA) is proposed, in which each firefly

The density peaks clustering (DPC) algorithm is a density‐based clustering algorithm. Its density peak depends on the density‐distance model to determine it. The definition of local density for samples used in DPC algorithm only considers distance between samples, while the environments of samples are neglected. This leads to the result that DPC algorithm performs poorly on complex data sets with large

In this article, we present an experimental performance study of a parallel implementation of two Poissonian image restoration algorithms. Hybrid parallelization, based on MPI and OpenMP standards, is investigated. The implementation is tested for high‐resolution radiographic images, on a supercomputer based on Intel Xeon processors, combined with Intel Xeon Phi coprocessors. The experimental results

The rapid development of Internet technology, networking, and emergence technologies has deeply impacted manufacturing. Moreover, the massive data being generated have increased tremendously. All of these factors have supported the transformation of the traditional manufacturing paradigm toward smart manufacturing. At present, the Industrial Internet of Things (IIoT) is an underlying platform for various

Using heterogeneous accelerators to obtain high performance for mathematical kernels remains an active research frontier in computational science. The accelerators have compute architectures that are different from the CPUs and in addition have memory spaces independent of the CPU systems to which they are connected. It follows that accelerators require a different approach to writing optimal code

Hybrid cloud, typically a combination of public and private cloud deployment models, is a rising paradigm due to the benefits it offers: full control of data and applications in the private cloud and elastic computing resource availability in the public cloud. This combination however brings an extra layer of complexity that can potentially erode the benefits and present serious challenges if not managed

Evaluation information generated by various users is processed using various requirements and data to make recommendations for solving the problems, and it analyzes satisfaction with the results. Despite people normally utilizes the processed information for decision making, not all information, however, brings positive outcomes to users. There are some users who perceived it negatively. In order to

Pansharpening aims to fuse a lower‐resolution multispectral (MS) image and a higher‐resolution panchromatic image, resulting in an image with the color quality of the former and spatial detail quality of the latter. Of all, the component substitution (CS)‐based pansharpening methods have drawn attentions with their ability to produce sharp images. Despite their success in sharpening the images, these

Federated learning is an improved version of distributed machine learning that further offloads operations which would usually be performed by a central server. The server becomes more like an assistant coordinating clients to work together rather than micromanaging the workforce as in traditional DML. One of the greatest advantages of federated learning is the additional privacy and security guarantees

This article considers a locality optimization technique for the parallel solution of a special class of large systems of ordinary differential equations (ODEs) by explicit one‐step methods on GPUs. This technique is based on tiling across the stages of the one‐step method and is enabled by the special structure of the class of ODE systems considered, that is, the limited access distance. The focus

Due to the continuous development and progress of information technology, the Internet has also entered the era of big data based on the Internet of Things (IoT). How to protect the security of data stored and transmitted in the IoT is one of the urgent problems to be solved. This article focuses on the security issues of storage and transmission of image data in the IoT. Secret image sharing (SIS)

Traditional applications have been developed for decades. Most of the security research around them have focused on the detection of memory corruption vulnerabilities, such as buffer overflow, double fetch, and integer overflow. On the contrary, logic bugs, a kind of flaws caused by unreasonable application logic, attract much less attention.

It is well known that virtual network (VN) embedding (VNE) aims to solve how to efficiently allocate physical resources to a VN. However, this issue has been proved to be an NP‐hard problem. Besides, as most of the existing approaches are based on heuristic algorithms, which is easy to fall into local optimal. To address the challenge, we formalize the problem as a mixed integer programming problem

The specific characteristics of vehicular ad hoc networks, such as high speed of nodes and frequent topology changes, impose challenges for the routing process. In addition, the advent of the Internet of Vehicles (IoV) concept along with the autonomous and connected cars contribute to the proliferation of new innovative applications with different quality of service requirements, rising new challenging

The field of telecommunication has undergone a very rapid technological evolution, which has forced researchers to find techniques that allow better exploitation of hardware and software. Among the proposed technologies, cognitive radio, a concept that was designed after several technologies such as software radio. Cognitive radio has been widely used for opportunistic access of the shared spectrum

Lidar‐based city objects detection is an interesting topic along with the development of Laser scan equipment which has been widely applied in various applications such as 3D building reconstruction, navigation, and so on. In this article, we describe a city object detection algorithm for airborne Lidar images using superpixel segmentation and DenseNet classification. Compared with the existing studies

The fast‐growing Android application market has attracted more and more application developers. However, many plagiarists use decompiled tools to modify original applications to get clones, which has become a serious threat. For detecting cloned applications, most of the existing schemes do not consider the detected accuracy and time consumption at the same time. In this article, we propose a two‐phase