This study is to explore the smart city information (SCI) processing technology based on the Internet of Things (IoT) and cloud computing, promoting the construction of smart cities in the direction of effective sharing and interconnection. In this study, a SCI system is constructed based on the information islands in the smart construction of various fields in smart cities. The smart environment monitoring

The Internet of Things (IoT) has developed a well-defined infrastructure due to commercializing novel technologies. IoT networks enable smart devices to compile environmental information and transmit it to demanding users through an IoT gateway. The explosive increase of IoT users and sensors causes network bottlenecks, leading to significant energy depletion in IoT devices. The wireless network is

In situ visualization on high-performance computing systems allows us to analyze simulation results that would otherwise be impossible, given the size of the simulation data sets and offline post-processing execution time. We develop an in situ adaptor for Paraview Catalyst and Nek5000, a massively parallel Fortran and C code for computational fluid dynamics. We perform a strong scalability test up

Both data shuffling and cache recovery are essential parts of the Spark system, and they directly affect Spark parallel computing performance. Existing dynamic partitioning schemes to solve the data skewing problem in the data shuffle phase suffer from poor dynamic adaptability and insufficient granularity. To address the above problems, this paper proposes a dynamic balanced partitioning method for

Recently, a considerable literature has grown up around the theme of composite services verification. Namely, the verification of the non-functional aspect generally consisting of optimizing the quality of service (QoS) of the composite service. Great efforts have been devoted to the study of several optimization methods and their impact on the QoS of the composite service. Guaranteeing the service

Recently, smart cities provide various services to citizens through the convergence of Information and Communications Technology and industries such as transportation, health care, and automobiles. Accordingly, the number of smart devices that use artificial intelligence technology to store the personal information of users to provide services efficiently is increasing. Smart devices can be used to

Grid scheduling is one of the most known NP-complete problems. Heterogeneity of machines causes mapping of tasks to be a challenging problem. Several meta-heuristic algorithms have been designed to reach optimality as possible. Sort-Mid is a recent efficient scheduler of excellent resource utilization. Its strategy was based on computing the mean of two consecutive middle values in the sorted list

The kNN (k nearest-neighbors) search is currently applied in a wide range of applications, such as data mining, multimedia, information retrieval, machine learning, pattern recognition, among others. Most of the solutions for this type of search are restricted to metric spaces or limited to use low dimension data. Our proposed algorithm uses as input a set of values (or measures) and returns the K

Fortran is still widely used in scientific computing, and a very large corpus of legacy as well as new code is written in FORTRAN 77. In general this code is not type safe, so that incorrect programs can compile without errors. In this paper, we present a formal approach to ensure type safety of legacy Fortran code through automated program transformation. The objective of this work is to reduce programming

Today’s industry has gradually realized the importance of lifting efficiency and saving costs during the life-cycle of an application. In particular, we see that most of the cloud-based applications and services often consist of hundreds of micro-services; however, the traditional monolithic pattern is no longer suitable for today’s development life-cycle. This is due to the difficulties of maintenance

Lattice-based cryptography forms the mathematical basis for current homomorphic encryption schemes, which allows computation directly on encrypted data. Homomorphic encryption enables privacy-preserving applications such as secure cloud computing; yet, its practical applications suffer from the high computational complexity of homomorphic operations. Fast implementations of the homomorphic encryption

Deep learning base solutions for computer vision made life easier for humans. Video data contain a lot of hidden information and patterns, that can be used for Human Action Recognition (HAR). HAR can apply to many areas, such as behavior analysis, intelligent video surveillance, and robotic vision. Occlusion, viewpoint variation, and illumination are some issues that make the HAR task more difficult

Cloud storage systems are increasingly adopting NoSQL database management systems (DBMS), since they generally provide superior availability and performance than traditional DBMSs. To the detriment of better consistency guarantees, several NoSQL DBMSs allow eventual consistency, in which an operation is confirmed without checking all nodes. Different consistency levels for an operation (e.g. read)

Due to the severity and great harm of coal and gas outbursts accidents, outbursts prediction becomes very necessary; the paper presents a hybrid prediction model of feature extraction and pattern classification for coal and gas outbursts. First, discrete wavelet transform (DWT) is utilized as a preprocessing technique to decompose subseries and extract the features with different frequencies and the

The rumors, advertisements and malicious links are spread in social networks by social spammers, which affect users’ normal access to social networks and cause security problems. Most methods aim to detect social spammers by various features, such as content features, behavior features and relationship graph features, which rely on a large-scale labeled data. However, labeled data are lacking for training

The widespread usage of cloud computing in different fields causes many challenges as resource scheduling, load balancing, power consumption, and security. To achieve a high performance for cloud resources, an effective scheduling algorithm is necessary to distribute jobs among available resources in such a way that maintain the system balance and user tasks are responded to quickly. This paper tackles

Disabilities due to neurodegenerative disease are rapidly increasing in number. The need for rehabilitative devices to achieve a normal and comfortable life in the absence of biochannels has also increased. The activities of biochannels can be easily replaced by implementing rehabilitative devices. The electrooculography (EOG)-based human–computer interface (HCI) is one of the most important techniques

Designing an optimal indoor space is challenging in interior architecture. The optimal space design requires a comprehensive analysis of the living situation of residents in a space. However, it is extremely difficult to collect data from the space where daily life occurs. Many spatial analysis sensors are required because various daily life data must be collected precisely. Hence, it is difficult

Two-dimensional convolution plays a fundamental role in different image processing applications. Image convolving with different kernel sizes enriches the overall performance of image processing applications. In this regard, it is necessary to design of reconfigurable convolver with respect to desired kernel sizes list. In this paper, a novel approach is presented for implementation of an area-efficient

The selection of text features is a fundamental task and plays an important role in digital document analysis. Conventional methods in text feature extraction necessitate indigenous features. Obtaining an efficient feature is an extensive process, but a new and real-time representation of features in text data is a challenging task. Deep learning is making inroads in digital document mining. A significant

An Internet-of-Vehicle (IoV) system primary transmits traffic information and various kinds of emergency notices through Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I); however, the transmission of multimedia enables drivers to control route conditions better, such as road obstacles and the range of a construction site. Additionally, car accidents usually require relevant video records

The fast JPEG image compression algorithm is a requisite in many applications such as high-speed video measurement systems and digital cinema. Many existing methods have implemented the JPEG compression in parallel based on GPU except for entropy coding, which is a variable-length coding method and seems like a better fit for sequential implementation. However, entropy coding is an essential part of

Automated guided vehicles (AGVs) are Internet of Things robots that navigate automatically as guided by a central control platform with distributed intelligence. Different methodologies have been proposed for AGV visual tracking applications. However, vision-based tracking in AGVs usually confronts the problem of time delay caused by the complexity of image processing algorithms. To balance the trade-off

One of the main steps in the data lifecycle is to publish it for data analysts to discover hidden patterns. But, data publishing may lead to unwanted disclosure of personal information and cause privacy problems. Data anonymization techniques preserve privacy models to prevent the disclosure of individuals’ private information in published data. In this paper, a distributed in-memory method is proposed

In recent years, new technology developments have been proposed and implemented to support people with hearing impairment and speech loss. It is a severe disability to be unable to speak and communicate. This group of people needs a device to help them use a smartphone in the same way as the rest of the population. This idea has pushed technologists to create new tools to help hearing-impaired and

With increasing numbers of GPS-equipped mobile devices, we are witnessing a deluge of spatial information that needs to be effectively and efficiently managed. Even though there are several distributed spatial data processing systems such as GeoSpark (Apache Sedona), the effects of underlying storage engines have not been well studied for spatial data processing. In this paper, we evaluate the performance

In this paper, a human-inspired optimization algorithm called stock exchange trading optimization (SETO) for solving numerical and engineering problems is introduced. The inspiration source of this optimizer is the behavior of traders and stock price changes in the stock market. Traders use various fundamental and technical analysis methods to gain maximum profit. SETO mathematically models the technical

The original version of this article unfortunately contained a mistake in equation 24.

Rapid communication of viral sicknesses is an arising public medical issue across the globe. Out of these, COVID-19 is viewed as the most critical and novel infection nowadays. The current investigation gives an effective framework for the monitoring and prediction of COVID-19 virus infection (C-19VI). To the best of our knowledge, no research work is focused on incorporating IoT technology for C-19

Consensus-based bundle algorithm (CBBA) is a decentralized task allocation algorithm that can produce feasible and conflict-free task assignment solution for multi-UAV system in the search and rescue scenarios. Further considering the new emerging tasks, this paper studies how to realize task reasssignment in the time-sensitive and dynamic environment. Effective task replanning algorithm aims to maximize

Before the HPC system is delivered to the user, system debugging engineers need to optimize the configuration of all system parameters, including the MPI runtime parameters. This process usually follows a trial-and-error approach, takes time and requires expert insight into the subtle interactions between the software and the underlying hard fight. With the expansion of system and application scale

Fuzzy C-mean (FCM) is an algorithm for data segmentation and classification, robust and very popular within the scientific community. It is used in several fields such as computer vision, medical imaging and remote control. The purpose of this paper is to propose a parallel implementation of the iterative type-2 fuzzy C-mean (IT2FCM) algorithm on a massively parallel SIMD architecture to segment different

Prior algorithms on graph simulation for distributed graphs are not scalable enough as they exhibit heavy message passing. Moreover, they are dependent on the graph partitioning quality that can be a bottleneck due to the natural skew present in real-world data. As a result, their degree of parallelism becomes limited. In this paper, we propose an efficient parallel edge-centric approach for distributed

An Internet of Things (IoT)-based informationized power grid system and a hierarchical energy storage system are put forward to solve energy storage problems in new energy power construction in remote areas. The system applies IoT to construct a distributed new energy grid system to optimize electric energy transmission. The information model is employed to establish a hierarchical energy storage system

In this manuscript, we first suggest a single-layer 2:1 QCA MUX with an ultra-low number of cells and high speed. Unlike existing designs, the output of the proposed design does not comply with the Boolean regulation and is produced using the essential characteristics of quantum technology. Single-layer 4:1 and 8:1 QCA multiplexers have also been implemented. Moreover, using the proposed 2:1 QCA MUX

Remote health monitoring is an important aspect especially for remote locations where standard medical facilities are not available. Smart cities use a similar concept to provide health facilities even when physicians are unavailable. Lung cancer remains to be one of the most critical types of cancer with a 5-year survival rate of only 18%. Efficient computer-aided diagnostic systems are required to

The deployment of virtual network functions (VNFs) at edge servers potentially impairs the performance of latency-sensitive applications due to their computational cost. This work considers a new approach to addressing this problem that provides line rate acceleration of VNFs by employing field-programmable gate array (FPGA) equipped edge servers. This approach has been validated by practical use cases

Performance differentiation and optimization are major dimensions and critical activities in cloud computing systems with shared execution infrastructures. Supporting these features from the perspective of cloud architecture, related concerns and requirements are important challenges, which need more in-depth research. In this regard, this work investigates the dark dimensions of the problem toward

The need for integration of applications and services in business processes from enterprises has increased with the advancement of cloud and mobile applications. Enterprises started dealing with high volumes of data from the cloud and from mobile applications, besides their own. This is the reason why integration tools must adapt themselves to handle with high volumes of data, and to exploit the scalability

Recently, there has been growing interest in social network analysis. Graph models for social network analysis are usually assumed to be a deterministic graph with fixed weights for its edges or nodes. As activities of users in online social networks are changed with time, however, this assumption is too restrictive because of uncertainty, unpredictability and the time-varying nature of such real networks

Processing large amount of high-resolution 3D data requires enormous computational resources. As a result, a suitable 3D data representation must be chosen, and the data must be simplified to a size that can be easily processed. The question is how can the data be simplified? Random point sampling is a common sampling strategy. However, it is sensitive to changes in density. We build a sampling module

Nowadays, high-performance computing (HPC) is stepping forward to exascale era. However, silent data corruption (SDC) behaved as bit-flipping can cause disastrous consequences for scientific computation, which jeopardizes the reliability of HPC at large scale. The most commonly used methods to address SDC are based on modular redundancy, which usually requires keeping execution progress consistent

Hypercubes are popular topologies of massive multiprocessor systems due to their super properties. Cross-cubes are significant variations of hypercubes and they have smaller diameters and higher fault-tolerant capability than hypercubes at the same dimensions. In this paper, we construct node-to-set disjoint paths of an n-dimensional cross-cube, \(C_{n}\), whose maximum length is limited by \(2n-3\)

The growing interest in cloud-based services has made the cost of energy a major concern for cloud service providers. On the other hand, there is an increasing global concern on the carbon footprints of data centers. Shifting from fossil fuels to renewable energy sources is essential to reduce operational costs in data centers while keeping carbon and greenhouse emissions to a minimum. However, considering

The IPv6 routing protocol for low power and lossy networks (RPL) has gained widespread application in the Internet of Things (IoT) environment. RPL has inherent security features to restrict external attacks. However, internal attacks in the IoT environment have continued to grow due to the lack of mechanisms to manage the secure identities and credentials of the billions of heterogeneous IoT devices

Finding the best approach for virtual machine placement (VMP) in cloud infrastructure is one of the most important optimization problems. The obtained solution of this problem significantly impacts on costs, energy, performance, etc. Physical machine (PM) processing capacity and virtual machine (VM) workloads have played important roles in VMP. Besides, in recent years with the increasingly development

In wireless sensor networks applications involving a huge number of sensors, some of the sensor devices may result to be redundant. As a consequence, the simultaneous usage of all the sensors may lead to a faster depletion of the available energy and to a shorter network lifetime. In this context, one of the well-known and most important problems is Maximum Network Lifetime Problem (MLP). MLP consists

Modern scientific research challenges require new technologies, integrated tools, reusable and complex experiments in distributed computing infrastructures. But above all, computing power for efficient data processing and analyzing. Containers technologies have emerged as a new paradigm to address such intensive scientific applications problems. Their easy deployment in a reasonable amount of time

The cloud runtime environment is dynamic; therefore, allocating tasks to computing resources might include various scenarios. Metaheuristic algorithms are usually used to choose appropriate scheduling scenarios; however, they suffer from premature convergence, trapping in local optima, and imbalance between the exploration and exploitation of search space. The multi-verse optimizer (MVO) algorithm

Cloud computing is a business model where having users and providers are competing to sell and buy services. Due to diverse software applications and dynamic cloud market, customers’ requirements are ever changing. Dynamic auction-based resource allocation models, namely: combinatorial double auction resource allocation (CDARA) model attracted the researchers’ attention. In existing work services are

Vehicular ad hoc networks (VANETs) provide real-time communication between vehicle units for comfortable and safe driving. VANETs are driven by the concept of broadcasting messages to other vehicle units. These messages are disseminated to other vehicles with proper security assurances that ensure authentication. In this paper, an authentication model for securing communications by authenticating vehicles

Internet of Things (IoT) is an emerging paradigm that consists of numerous connected and interrelated devices with embedded sensors, exchanging data with each other and central nodes over a wireless network and internet. Recently, due to the crucial importance of human well-being, IoT-enabled healthcare systems have gained significant attention. On the other hand, as IoT networks are large-scaled and

With the development of cloud computing application, attribute-based encryption (ABE) with flexibly fine-grained data access control is widely adopted. However, traditional data access structures are mainly constructed on independent and fixed attribute values. The data access policies in traditional ABE schemes don’t express the relationship of different attributes and the dynamic attribute values

In this paper, we investigate a MEC relay-assisted system with multiple relay nodes (RNs) and multiple remote servers (RSs), where both the selections of best RN and RS are considered. In order to explore the diversity of both RNs and RSs, we propose a sequential relay-remote selection and offloading strategy by taking the local computing, relay computing and remote computing into consideration. The

In recent years, it has been observed that many researchers have been working on different areas of detection, recognition and monitoring of human activities. The automatic determination of human physical activities is often referred to as human activity recognition (HAR). One of the most important technology that detects and tracks the activity of the human body is sensor-based HAR technology. In

The energy-efficient deployment of small cells helps to reduce environmental pollution in an ultra-dense network. In contrast, demand for massive connectivity and higher data rate are the promise of the present cellular system and small cell networks. Hence, energy consumption is reduced if base stations are optimally used. One way to improve the energy efficiency is by shutting down the redundant

The emerging trend in technical research is to use client-generated data composed of community media to survey community opinion and scientific communication on employment and care issues. This study gathered data from the social website questions and answers and the indirect effects of stack to survey the key factors that influence public preferences in technical knowledge and opinions. Using a web

A correction to this paper has been published: https://doi.org/10.1007/s11227-021-03923-0

With the development of online social networking applications, microblogs have become a necessary online communication network in daily life. Users are interested in obtaining personalized recommendations related to their tastes and needs. In some microblog systems, tags are not available, or the use of tags is rare. In addition, user-specified social relations are extremely rare. Hence, sparsity is

Quantum dot cellular automata (QCA) technology is considered as one of the most suitable replacements to reduce the CMOS-based digital circuit design problems at the nanoscale due to its tiny size, fast, latency and very low power consumption. One of the main components of microprocessors is the arithmetic logic unit (ALU) and in other words, it acts as the heart of microprocessors. This paper presents