Internet of Things (IoT) and cyber-physical systems demand proper real-time data processing and analysis to fulfill the essential characteristics of seamless computing services such as less processing time, dynamic network management, and location awareness. With the evolution of mobile edge computing, numerous security and privacy issues have been addressed including policy management, authentication

Data provenance has led to a developing need for the technologies to empower end-users to assess and take action on the data life cycle. In the Big Data era, companies' amount of data over the world increases each day. As data increases, metadata on the data origin and lifecycle of data also overgrows. Thus, this requires innovations that can provide a better understanding and interpretation of data

In this special issue of Concurrency and Computation Practice and Experience, we are pleased to present eight selected papers that were previously presented at the Brazilian “XX Simpósio em Sistemas Computacionais de Alto Desempenho,” WSCAD 2019. The event was held in conjunction with the 31st International Symposium on Computer Architecture and High Performance Computing, SBAC-PAD 2019, in Campo Grande

This article proposes a new method for image classification and image retrieval. The advantages of the proposed method are its high performance and requiring less memory compared to other methods. In order to extract image features, a Convolutional Neural Network (CNN), AlexNet, has been used. For image classification, we design a committee of four classifiers trained on graphics cards, narrowing the

In federated cloud environment, it is too hard for the consumers to manage the services as multiple services may be rendered from multiple providers. Finding the trustable cloud service provider is an important and tedious process for the consumers before acquiring the services. In this proposed work, the reputation of the service providers are calculated through two different scenarios such as reputation

Web services are becoming a major utility for accomplishing complex tasks over the Internet. In practice, the end-users usually search for Web service compositions that best meet the quality of service (QoS) requirements (i.e., QoS global constraints). Since the number of services is constantly increasing and their respective QoS is inherently uncertain (due to environmental conditions), the task of

Twister2 is an open-source big data hosting environment designed to process both batch and streaming data at scale. Twister2 runs jobs in both high-performance computing (HPC) and big data clusters. It provides a cross-platform resource scheduler to run jobs in diverse environments. Twister2 is designed with a layered architecture to support various clusters and big data problems. In this paper, we

A multiclass 3D object recognition has perceived a numerous evolution with respect to both accuracy and speed. This study introduces the implementation of modern YOLO algorithms (YOLOv3, YOLOv4, and YOLOv5) for multiclass 3D object detection and recognition. All YOLO algorithms have been tested according to a very large scaled dataset (Pascal VOC dataset). Performance evaluation has targeted the calculation

In order to improve the efficiency of domain ontology concept extraction, this paper proposes a method of semantic-weight ranking to extract core concepts. Firstly, we make segmentation processing for corpus texts and obtain the candidate concept set, and then analyze the correlation between the candidate concepts through the method of semantic similarity to form a mesh graph structure. We secondly

In stream cipher systems, random key sequence generation is the primary task. The concept of chaotic systems can be considered in generating a random key sequence due to its inherent randomness property. Though the chaotic real sequences are random, the randomness will be lost after converting them to binary sequences. In this context, the authors propose a technique which uses a non-linear feedback

Cloud services are open, shared, and complex. These characteristics will lead to many security risks and will affect the development of cloud services. Therefore, it is necessary to identify and measure the security risks of cloud services. However, there are still many deficiencies in this area. In light of this, this paper carries out an in-depth study from the perspective of technical security risk

Hybrid distributed computing software architectures gain great importance in data analysis workflows as the number of available underlying machine learning libraries and data storage systems increase. We argue that there is a need for novel approaches for software architecture designs that can enable machine learning data analysis workflows to run on top of different subsystem libraries. To address

Cloud computing has the advantage of providing flexibility, high-performance, pay-as-you-use, and on-demand service. One of the important research issues in cloud computing is task scheduling. The purpose of scheduling is to assign tasks to available resources while providing optimization on some objectives. Tasks have diversified characteristics, and resources are heterogeneous. These properties make

Any life event or action can be seen as a potential source of data to analyze. By analyzing such data, we can gain insights into the facts. The situation is no different in public transport. Researchers working in the fields of transport and traffic have stated that such an analysis would be invaluable in designing urban transport and particularly in adapting to current changes. In this study, a scalable

The importance of string matching is due to its applications in many fields, such as medicine and bioinformatics. Various string matching algorithms are developed to speed up the search. Especially, hash-based exact string matching algorithms are among the most time-efficient ones. The efficiency of hash-based approaches depends on the hash function. Hence, perfect hashing plays an essential role in

Parking vehicles in densely populated areas are often challenging, stressful, and sometimes it becomes a monotonous job for the drivers in jam-packed areas. There are several reasons for the delay in finding parking spaces such as scarcity of parking slots, disordered or unmanaged parking of vehicles, lacking or unaware of parking information at the destination, which further leads to the wastage of

Nowadays, a new paradigm named mobile edge computing (MEC) is capable of supplying some cloud-like functions at the edges of wireless networks, which enables vehicles to offload the computation intensive tasks on MEC servers with low latency. However, new challenges posed by the complex network environment and the mobility of vehicles are usually not covered by traditional offloading schemes. To solve

Digital document collections have been created with the transfer of a large number of documents to digital media. These digital archives have provided many benefits to users. As the diversity and size of digital image collections have grown exponentially, it has become increasingly important and difficult to obtain the desired image from them. The images on the document might contain critical information

Cloud computing is recognized as a cost-effective paradigm in outsourcing, where infrastructure, platforms, and software can be offered as a service. However, problems related to privacy and security are still challenging, especially in mobile cloud systems. Cloud end users are now using mobile systems for applications that fall under the data intensive paradigm, such as skyline queries, streaming

In recent years many user-oriented and personalized computing technologies have been developed, in which users are immersed in a virtual world and surrounded by processing units. Such computing technologies require distributed signals to be collected, and perform intelligent analysis with data fusion depending on user preferences and the surrounding environment. In such human-oriented analysis, it

We contribute to the optimization of the sparse matrix-vector product by introducing a variant of the coordinate sparse matrix format that balances the workload distribution and compresses both the indexing arrays and the numerical information. Our approach is multi-platform, in the sense that the realizations for (general-purpose) multicore processors as well as graphics accelerators (GPUs) are built

Machine learning (ML) continues to grow in importance across nearly all domains in modeling to learn from data. Often a tradeoff exists between a model's ability to minimize bias and variance. In this article, we utilize ensemble learning to combine linear, nonlinear, and tree-/rule-based ML methods to cope with the bias-variance tradeoff and result in more accurate models. We use the datasets collected

We present robust high-performance implementations of signal-processing tasks performed by a high-throughput wildlife tracking system called ATLAS. The system tracks radio transmitters attached to wild animals by estimating the time of arrival of radio packets to multiple receivers (base stations). Time-of-arrival estimation of wideband radio signals is computationally expensive, especially in acquisition

Cloud storage service has been in full swing in the industry. Delta synchronization technology as a key technology of cloud storage services has not made a key breakthrough. Almost all the existing researches are based on the synchronization process proposed by the Rsync algorithm and mix some optimization appropriately, but the particularity of cloud storage service is not fully considered. This paper

With rapid growth of mobile-based computing, reliable security and user authentication methods are necessary. This article proposes a proof-of-concept biometric authentication method utilizing hand images collected in different light spectra. An analysis of similarity between pattern of blood vessels extracted from near-infrared images and thermal images and assessment of the correlation between individual

Turmeric (Curcuma longa) is a popular food ingredient which is widely used in powdered form. Despite different food and medicinal advantages it is often adulterated. Metanil yellow (MET) is one such synthetic chemical which can be easily mixed with turmeric powder and such mixing is difficult to detect. This paper presents a computer vision framework using the potential of deep neural network towards

With the rapid growth of RDF (resource description framework) data volume, it is challenging to answer queries over dynamic RDF graphs of which the data frequently changes (by insertion/deletion) over time. This article presents QRDF, an efficient RDF graph processing system that supports not only efficient storage but also fast query of dynamic RDF graphs. QRDF (i) adopts a red-black (RB) tree for

Distributed heterogeneous systems have been widely adopted in industrial applications by providing high scalability and performance while keeping complexity and energy consumption under control. However, along with the increase in the number of computing nodes, the energy consumption of distributed heterogeneous systems dramatically grows and is extremely hard to predict. Energy-conscious task scheduling

Glioblastoma multiforme (GBM or glioblastoma) is a fast-growing glioma that are the most invasive type of glial tumors, rapidly growing and commonly spreading into nearby brain tissue. Due to its aggressive and fast growing nature, patients suffer from high grade glioma (GBM) survive very less time as compare to other tumors. Prediction of patient survival (OS) time helps the radiologist for better

Triple DES (3DES) is a NIST and ISO/IEC standard block cipher that is also used in some web browsers and several electronic payment applications. We propose an optimized bit-level parallelization of 3DES for GPU accelerated encryption to allow processing high volumes of data. Since the block size of 3DES is 64 bits, our approach considers a kernel block as a 64-bit 3DES block. Each kernel block performs

Text classification is one of the most important tasks to extract information from the Internet and identifying the best text representation settings. With the increase of data volume on the world wide web, the significance of text classification increases. This situation requires huge human efforts to understand and classify the digital data available on the Internet. Text classification is classifying

In the direction of arrival (DoA) estimation, typically sensor arrays are used where the number of required sensors can be large depending on the application. With the help of compressed sensing (CS), hardware complexity of the sensor array system can be reduced since reliable estimations are possible by using the compressed measurements where the compression is done by measurement matrices. After

In this article we study and evaluate combinatorial algorithms for exploring state spaces of prototypical artificial intelligence problems that are represented by very large state space graphs. We are interested in the modeling and analysis of such graphs, including their visualization and quantification. We consider Blocks World as a prototype artificial intelligence problem that is often employed

Text data have an important place in our daily life. A huge amount of text data is generated everyday. As a result, automation becomes necessary to handle these large text data. Recently, we are witnessing important developments with the adaptation of new approaches in text processing. Attention mechanisms and transformers are emerging as methods with significant potential for text processing. In this

Path planning is an essential step for mobile robots. This paper presents a novel shape parameter search- (SP-Search) based path planning algorithm for mobile robots using quintic trigonometric Bézier curve and its two shape parameters. The proposed search algorithm recursively divides the shape parameter space into a grid and uses a multi-objective function to determine the shape parameter values

The fast Fourier transform (FFT) has applications in almost every frequency related study, for example, in image and signal processing, and radio astronomy. It is also used as a Poisson operator inversion kernel in partial differential equations in fluid flows, in density functional theory, many-body theory, and others. The three-dimensional FFT has large time complexity . Hence, parallelization is

Two essential problems in computer algebra, namely polynomial factorization and polynomial greatest common divisor computation, can be efficiently solved thanks to multiple polynomial evaluations in two variables using modular arithmetic. In this article, we focus on the efficient computation of such polynomial evaluations on one single CPU core. We first show how to leverage SIMD (single instruction

With the rapid growth of the number of Web services on the Internet, how to classify Web services correctly and efficiently become particularly important in service management tasks, such as service discovery, service selection, service ranking, and service recommendation. Existing functionality-based service classification techniques have some drawbacks: (1) the keyword order and context information

Teaching learning-based optimization (TLBO) is a popular stochastic algorithm that has recently been widely applied in a variety of optimization problems since its start. In TLBO algorithm, the concept of chaos not only shows a vital effect in its convergence but also plays a substantial role to balance of exploration and exploitation through evolution. However, TLBO is quickly trapped in local optima

Aspect-category sentiment classification of microblog comments aims to identify the sentiment polarity of different opinion aspects in microblog comments, which is meaningful for the analysis of public opinion. At present, most of aspect-category sentiment classification methods need much annotation data, and regard comments as independent samples, without using of the relationship between comments

Computational grid is a pool of computational resources that is used by various organizations for storage purposes and execution of a large number of tasks. Load balancing and energy consumption are two core performance parameters in the computational grid. Since, performance of a computational grid is highly dependable to variations in load and energy consumption, therefore, it is important to pay

In big data mining, the K-prototypes has become a popular clustering method for mixed data owing to its simplicity and efficiency. However, the data clustering process of the K-prototypes method will cause the risk of user privacy leakage because user data usually contain sensitive information. To address this issue, general solutions introduce a trusted third-party model for privacy protection in

The internet has provided much information to the users, and the huge amount of information has caused the overhead information problem so that recommender systems, as a solution by recommending related items, try to find the users favorite items. Most recommender systems recommend specific items based on user profile settings and past privileges. Various approaches, such as collaborative refinement

Software defined networking (SDN) architecture is easily manageable, flexible, and dynamic where controller selection plays a major role. In SDN, the controlling functions are handled by control plane and forwarding functions are handled by data plane. In general, the centralized controller supervises the control plane, and it communicates with the data plane using “Open Flow” (south bound interface)

The load balancing (LB) may be used at different levels to reduce overhead for the decision-making process. In the past decade, cloud computing has drawn a lot of attention from both the academic and commercial communities to get demanded resources (machines, platforms, data, storage, software, and so forth) as a service on rent economically. Generally, a situation may arise when requests are not meeting

Agriculture plays a significant role in any country's wealth creation, fulfilling food security needs and employment generation thereby contributing immensely to the country's growth and GDP. However, certain characteristics such as climate and environmental changes have extensively become menacing factors in the agriculture output. As soil is an influential specification influencing the prediction

The main idea of this article is to propose a hardware design of block matching (BM) algorithm for an efficient motion estimation (ME) strategy in a field programmable gate array platform based on a parallel implemented genetic algorithm (GA). Easiness and the effectiveness of the BM algorithm while implementing have a major drawback of low quality and computationally cost expensive during the process

Software development effort estimation is an effective factor in the success or failure of software projects. There are several methods to estimate the effort of software projects, the most common of which is analogy-based estimation (ABE). In this article, a polynomial version of ABE (named PABE) is presented, in which, the project effort is calculated based on a polynomial ensemble of different ABE

Autism spectrum disorder (ASD) is a neurodevelopmental disorder caused by several nervous system problems that change the function of the brain. It is either congenital or occurs in the early years of life. Although the cause of ASD is not known exactly, it is generally thought to be genetic. Today, the relationship of ASD with other diseases is under investigation. One of these diseases is jaundice

The rapidly growing information technologies such as cloud computing, edge computing, artificial intelligence offer cutting-edge technical means for virtual reality of industrial manufacturing process. An efficient and accurate method for situation awareness (SA) to monitor the process of marginal layer plays an essential role to enhance the safety of industrial equipment. In this study, a manufacturing

Successful treatment of diseases depends on many important factors: correct diagnosis, choice and type of equipment, and the risk of infectious diseases. It is crucial to take into these factors, in particular, the risk of infection and the costs of equipment in catheter selection for invasive interventions in neonatal intensive care units (NICUs). Catheters have different lifetime, therefore, the

Today, modern healthcare systems rely on advanced computational technologies, including cloud-based systems, to gather and examine personal health data on a large scale. The use of advanced cloud services technologies, such as software as a service, application as a service, is challenging for end-users of cloud systems to protect sensitive data in their health applications. According to the importance

The revolutionary architecture termed Software-Defined Network provides flexible network management by detaching the control logic from the underlying data plane. The flow table resides in Ternary Content Addressable Memory imparts rules for the incoming flows with a limitation of high cost, limited storage, and consumes high power. In data center networks, when the traffic rate is high the overflow

Crowdsourcing is now one of the most important and transformative paradigms, with great success in a variety of application tasks. Crowdsourcing obtains knowledge and information to solve cognitive or intelligence-intensive tasks from an evolving group of participants via the Internet. Unfortunately, providing a hard privacy guarantee and query optimization is incompatible when a higher task acceptance

Exponential increase in the amount of textual data made available on the Internet results in new challenges in terms of accessing information accurately and quickly. Text summarization can be defined as reducing the dimensions of the expressions to be summarized without spoiling the meaning. Summarization can be performed as extractive and abstractive or using both together. In this study, we focus

This article investigates and analyzes the security aspects of 5G specifications from the perspective of IoT-based smart grids. As the smart grid requires high-speed and reliable communication to enable real-time grid monitoring via Internet of Things (IoT) devices, 5G can be considered a catalyst to transform the current power grid infrastructure into a smart grid. Thus, an understanding of what 5G

Designing a database cost model is one of the main research topics related to the physical design phase. It follows the evolution of database technology in order to evaluate and quantify the performance metrics (e.g., response time, energy consumption, etc.). Therefore, it makes the community researchers sensitive to the generated results. However, reusing and comparing database cost models require

Data caching is an effective method to reduce traffic and improve the quality of service in network. Traditionally, users' requests are offloaded to the cloud for centralized computing. However, due to security and privacy, these tasks are executed in the nearest server, so that the data and service needed by the task are also essential. After the task is completed, in case the next arriving request

GPUs only support simple coherence operations. For data integrity, heavyweight synchronization operations must be explicitly used. Scoped synchronization Hower et al. (2014) and Gaster et al. (2015) has been introduced to facilitate low overhead communication, when the communication is local across a subset of threads. Scoped synchronization can be used if the sharing is static. However, it is not

The ever increasing amount of generated data makes it more and more beneficial to utilize compression to trade computations for data movement and reduced storage requirements. Lately, dedicated accelerators have been introduced to offload compression tasks from the main processor. However, research is lacking when it comes to the system costs for incorporating compression. This is especially true for