With the exponential proliferation of cloud services, the decision of trustworthy cloud service selection has become tremendously challenging nowadays. It demands an accurate decision system to carry out a comprehensive assessment of cloud services from various aspects. The immense complexity and limitations of existing approaches reduce the credibility of the service selection process; thus, further

The cheque based banking transactions are widely used all over the world. The reason is that it is a hustle free and trusted way of money transaction. The existing cheque settlement process involves manual processing of submitted cheques, and large amounts of time for clearance. This paper proposes a framework to automate the cheque settlement process. This framework proposes cheque generation, cheque

Access to a variety of Internet of Things networks can be achieved through end-user devices such as smartphones or tablets. However, these devices are susceptible to theft, loss or unauthorized access. Although end-user devices are equipped with different means of authentication such as fingerprint readers, these methods are only employed at the time of access. Hence, an effective authentication mechanism

One of the technology for increasing the safety and welfare of humans in roads is Vehicular Cloud Computing (VCC). This technology can utilize cloud computing advantages in the Vehicular Ad Hoc Network (VANET). VCC by utilizing modern equipment along with current vehicles, can play a significant role in the area of smart transportation systems. Given the potential of this technology, effective methods

Cluster computing technologies are rapidly advancing and user-generated online reviews are booming in the current Internet and e-commerce environment. The latest question–answering (Q&A)-style reviews are novel, abundant and easily digestible product reviews that also contain massive valuable information for customers. In this paper, we mine valuable aspect information of products contained in these

It is essential to ensure the data security of data analytical frameworks as any security vulnerability existing in the system can lead to a data loss or data breach. This vulnerability may occur due to attacks from live attackers as well as automated bots. However inside attacks are also becoming more frequent because of incorrectly implemented security requirements and access control policies. Thus

High-performance storage devices, such as Non-Volatile Memory express Solid-State Drives (NVMe SSDs), have been widely adopted in data centers. Especially, multiple storage devices provide higher I/O performance compared with a single device. However, the performance can be reduced in the case of workloads with mixed read and write requests (e.g., key-value stores) even though multiple storage devices

The cloud evolved into an attractive execution environment for parallel applications, which make use of compute resources to speed up the computation of large problems in science and industry. Whereas Infrastructure as a Service (IaaS) offerings have been commonly employed, more recently, serverless computing emerged as a novel cloud computing paradigm with the goal of freeing developers from resource

High energy consumption (EC) is one of the leading and interesting issue in the cloud environment. The optimization of EC is generally related to scheduling problem. Optimum scheduling strategy is used to select the resources or tasks in such a way that system performance is not violated while minimizing EC and maximizing resource utilization (RU). This paper presents a task scheduling model for scheduling

Cloud Computing is referred to as a set of hardware and software that are being combined to deliver various services of computing. The cloud keeps the services for delivery of software, infrastructure, and platform over the Internet based on the user’s demand. In the IT industry, cloud computing plays an important role to access services anywhere in the world. With increasing demand and popularity

Collaborative filtering which is the most successful technique of the Recommender System, has recently attracted great attention, especially in the field of e-commerce. CF is used to help users find their preferred items by assessing the preferences of other users to find most similar to the active one. Sparse datasets defend the efficiency of CF. Therefore this paper proposes two new methods that

The elasticity characteristic of cloud services attracts application providers to deploy applications in a cloud environment. The scalability feature of cloud computing gives the facility to application providers to dynamically provision the computing power and storage capacity from cloud data centers. The consolidation of services to few active servers can enhance the service sustainability and reduce

The problem of minimizing the execution monetary cost of applications on cloud computing platforms has been studied recently, and satisfying the deadline constraint of an application is one of the most important quality of service requirements. Previous method of minimizing the execution monetary cost of deadline-constrained applications was the “upward” approach (i.e., from exit to entry tasks) rather

Data centers are growing densely and providing various services to millions of users through a collection of limited servers. That’s why large-scale data center servers are threatened by the overload phenomenon. In this paper, we propose a framework for data centers that are based on Software-defined networking (SDN) technology and, taking advantage of this technology, seek to balance the load between

This paper presents a novel “Distributed Deep Learning Framework” for a heterogeneous multi-GPU cluster that can effectively improve overall resource utilization without sacrificing training accuracy. Specifically, we employ a hybrid aggregation approach using a parameter-server and all-reduce schemes in order to address potential performance degradation problems in running deep learning applications

As Bitcoin and other cryptocurrencies become widely popular recently, the underlying concept—Blockchain—gets unprecedented attentions. One popular usage of Blockchain is a distributed replicated database. In this paper, we present initial studies on the challenges and opportunities of using Blockchain as a database for Internet-of-Things (IoT) applications. For IoT applications, latency is an important

Ensemble learning is increasingly used in sentiment analysis. Determining the parameter settings of ensemble models, however, is not easy. Besides its own parameters, an ensemble model has base-predictors that have their individual parameters. Some ensemble models use a specific base-predictor and could be optimised using standard metaheuristics such as the Particle Swarm Optimisation (PSO) approach

The MapReduce (MR) scheduling is a prominent area of research to minimize energy consumption in the Hadoop framework in the era of green computing. Very few scheduling algorithms have been proposed in the literature which aim to optimize energy consumption. Moreover, most of them are only designed for the slot-based Hadoop framework, and hence, there is a need to address this issue exclusively for

Cloud infrastructures are suitable environments for processing large scientific workflows. Nowadays, new challenges are emerging in the field of optimizing workflows such that it can meet user’s service quality requirements. The key to workflow optimization is the scheduling of workflow tasks, which is a famous NP-hard problem. Although several methods have been proposed based on the genetic algorithm

Multi-core systems has evolved enormously during the last decade with the improvement in the integration technology which makes it possible to house large number of transistors on a single chip. Keeping large number of cores on a single chip results in heat dissipation, which is a serious problem and cannot be overlooked. To handle this, not only the green hardware but energy-efficient software techniques

The Internet unfolded enormous opportunities to the modern computing world where not only humans but also computers and machines, as well as any tiny sensing devices, can communicate and collaborate. The Internet of Things (IoT) is still a new concept in its early stages after 20 years of successful usage in various application domains. Nowadays, the "Internet of Things Ecosystem" term is being used

High-density, high-sampling rate EEG measurements generate large amounts of measurement data. When coupled with sophisticated processing methods, this presents a storage, computation and system management challenge for research groups and clinical units. Commercial cloud providers offer remote storage and on-demand compute infrastructure services that seem ideal for outsourcing the usually burst-like

This paper proposes a new version of the power of two choices, SQ(d), load balancing algorithm. This new algorithm improves the performance of the classical model based on the power of two choices randomized load balancing. This model considers jobs that arrive at a dispatcher as a Poisson stream of rate \(\lambda n,\)\(\lambda < 1,\) at a set of n servers. Using the power of two choices, the dispatcher

Advances in data acquisition have generated an enormous amount of data that captures business, commercial, technological and scientific information. However, some occurrences are rare or unusual, irrespective of a large amount of data available. These rare occurrences in data mining are usually referred to as outliers or anomalies. All these rare occurrences are infrequent. Sometimes it varies from

METAFONT is a parameterized font that can generate different font styles by changing its parameters. It generates bitmaps fonts (Generic Font and TeX Font Metric) that are commonly used in TeX-based environment. The bitmap fonts generated from METAFONT can be utilized in devices of any size or resolution without creating a new font file for each. However, these fonts cannot be used outside the TeX

The low capacity of main memory has become a critical issue in the performance of systems. Several memory schemes, utilizing multiple classes of memory devices, are used to mitigate the problem; hiding the small capacity by placing data in proper memory devices based on the hotness of the data. Memory tracers can provide such hotness information, but existing tracing tools incur extremely high overhead

Software-defined networking (SDN) is a state-of-the-art architectural approach to network management that allows more flexible management of a complicated large-scale network. For providing services with high performance, availability, and scalability, server clustering is widely used. This study develops a server cluster based on OpenFlow, which is the most common SDN protocol. To utilize cluster

Over the past few years, cloud computing model (e.g., Spark) has aroused huge attention. Differential evolution (DE) has been applied to cloud computing models by a number of researchers for its merits in solving large-scale global optimization problems (LSGO), and remarkable results have been achieved. Moreover, we noticed that a combination of better topology and migration strategy is critical to

Software-defined networking (SDN) is an approach in the network that provides many advantages with the help of separating the intelligence of the network (controller) with the underlying network infrastructure (data plane). But this isolation also gives birth to many security concerns; therefore, the need to protect the network from various attacks is becoming mandatory. Distributed Denial of Service

Chronic patients are adapting to an emerging healthcare system assisted by the wireless body area network (WBAN). Medical data are not normal at all times; hence, the preference for critical data is expected to be high, and the requirement of security has become essential. This paper addresses a novel healthcare monitoring system (HMS) that adopts the IEEE 802.15.6 standard for WBAN. A modified IEEE

Traditional network intrusion detection algorithm is based on pattern matching, which has made great progress in network intrusion detection system, but the efficiency of this algorithm for data packet matching is quite low. With the rapid increase of Internet scale and capacity, the general information security problem appears, and it brought hidden danger for an open network security. In this paper

Urban computing is one of the effective fields that have ability to collect the large volume of data, integrate and analyze the data in urban space. The urban space faces several issues such as traffic congestion, more energy consumption, air pollution and so on. Among the several problems, air pollution is one of the major issues because it creates several health issues. So, this paper introduces

Fuzzy C-means clustering integration algorithm is a method to improve clustering quality by using integration ideas, but as the amount of data increases, its time complexity increases. A parallel FCM clustering integration algorithm based on MapReduce is proposed. The algorithm uses a random initial clustering centre to obtain differentiated cluster members. By establishing an overlapping matrix between

In energy-constrained wireless sensor networks (WSNs), geographic routing (GR) also known as location-aware routing has been developed because it uses neighbourhood locality data as an alternative of overall topology information for routing. But, this protocol frequently suffers from the energy holes in the data transmission resulting in path failure. To avoid this problem, energy-aware dual-path GR

Waste management is one of the crucial issues in the creation of smart cities. Because of population growth, keeping urban areas clean is a challenge. The Internet of things (IoT) has played a vital role in urban computing because it facilitates the collection, integration, and processing of various types of information. Thus, the aim of this research is to develop an Internet of Things-Based Urban

Robotics are effectively utilized in the field of speech therapy because, most of the people affected by the apraxia speech problem which is one of the neurological disorder. This disorder occurred due to the Alzheimer disease, stroke that affects the movement of mouth severely. These neurological disease affected people requires more attention while training the speech therapy. Traditional approaches

The problem of securely outsourcing computation to cloud servers has attracted a large amount of attention in recent years. The verifiable computation of Gennaro, Gentry, Parno (Crypto’10) allows a client to verify the server’s computation of a function with substantially less time than performing the outsourced computation from scratch. In a multi-function model (Parno, Raykova, Vaikuntanathan; TCC’12)

Email services nowadays are flooded by spam and phishing attacks. Email service providers build their own email filters to protect the final users from such attacks resulting in an overall better experience. However, the attacks come mainly from the same problem in the email protocols, i.e., the lack of authentication mechanism. In this work, we attempt to minimize some of the most common problems

With the rapid development of Internet of Things (IoT), more and more devices are connected to IoT, leading to an exponential increase in IoT data. However, two problems stand in the way of the further development of IoT. First, IoT data is uploaded directly to the cloud, and the service provider obtains huge profits by analyzing IoT data. However, users can't get benefits, and they have to bear the

Infrastructure interdependency is a bidirectional interconnection between entities of two infrastructures. These Critical Infrastructures (CIs) suffer from several attacks, vulnerabilities, and failures. Indeed a failure in one CI could lead to serious consequences on physical security, economic security, or public health. However, the protection of these infrastructures is essential. The clustering

Like other emerging fields, Stream Processing Engines (SPEs) pose several challenges to the researchers e.g., resource awareness, dynamic configurations, heterogeneous clusters, load balancing, and topology awareness. All of these aspects play a major role in the job scheduling process. Currently, SPEs ignore topology’s structure while scheduling. Due to this, frequently communicating tasks may end

Denial of service (DoS) attack is the menace to private cloud computing environment that denies services provided by cloud servers leading to huge business losses. Efficient DoS attack detection mechanisms are demanded which necessitates the extraction of features for its best performance. The lacuna in the existing feature extraction based detection systems is the sensitiveness of initial cluster

Cloud computing is emerging as an increasingly popular computing paradigm, allowing dynamic scaling of resources available to users as needed. This requires a highly accurate demand prediction and a resource allocation methodology. The existing methodologies for dynamic resource allocation do not provide effective performance isolation between the VM and Artificial Demand Analysis machines since it

The recent years have witnessed significant interest in migrating different applications into the cloud platforms. In this context, one of the main challenges for cloud applications providers is how to ensure high availability of the delivered applications while meeting users’ QoS. In this respect, replication techniques are commonly applied to efficiently handle this issue. From the literature, according

Time sensitive virtual machines that run real-time control tasks are constrained by hard timing requirements. Optimal resource management and guarantee the hard timing requirements of virtual machines are critical goals. Basically, cloud resource usage predicting and resource reservation play a crucial role to achieve these two goals. So, we propose a predicting approach based on two-phase decomposition

The cloud computing (CC) model is diverse as well as has broad phenomena because of which it is being preferred widely. Due to security challenges, the user cannot utilize CC to its full potentials. Storing their sensitive data in an insecure place is not even an option for these users. Many techniques were posited for securely amassing the data in the cloud; however, during massive transmission, none

The nodes in wireless sensor networks (WSNs) are responsible for communicating data which is primarily of three types viz. video, audio and text. In literature, a large number of energy aware and shortest path based route selection approaches have been proposed to enhance the routing efficiency in WSNs. Most of these route selection approaches are designed by assuming fixed type and size of data packets

Clouds are heterogeneous service-oriented systems which are increasingly considered as platforms of choice for scientific workflow applications. Because resource and communication failures are inevitable in large complex distributed systems, insuring the reliability of heterogeneous service-oriented systems poses a major challenge. As it affects the quality of user service requirements, reliability

In recent years, cloud computing paradigm has emerged as an internet-based technology to realize the utility model of computing for serving compute-intensive applications. In the cloud computing paradigm, the IT and business resources, such as servers, storage, network, and applications, can be dynamically provisioned to cloud workloads submitted by end-users. Since the cloud workloads submitted to

General-purpose graphics processing units (GPGPUs) have been widely adapted to the industry due to the high parallelism of graphics processing units (GPUs) compared with central processing units (CPUs). Especially, a GPGPU device has been adopted for various scientific workloads which have high parallelism. To handle the ever increasing demand, multiple applications are often run simultaneously in

Electronic health records (EHRs) are increasingly employed to maintain, store and share varied types of patient data. The data can also be utilized for various research purposes, such as clinical trials or epidemic control strategies. With the increasing cost and scarcity of healthcare services, healthcare organizations feel at ease in outsourcing these services to cloud-based EHRs. That serves as

Despite the rapid improvement in dental health over the last few decades, a significant portion of our population continue seek dental care every year. Estimates show that 13% of adults seek dental care for dental infection or fatigue within four years. The Social and individual burden of this disease can be reduced by its early detection. However, the symptoms of teeth infection in the early stages

The rapid development of communications networks facilitate our lives but bring severe energy consumption problems. As an emerging network structure, software-defined networking can realize flexible scheduling of network traffic demands. In this paper, we exploit the above feature and adopt the idea that is powering down unnecessary links and improving links bandwidth’s utilization to formulate an

Serverless computing and a function execution model, Function-as-a-Service (FaaS), are currently receiving considerable attention from both academia and industry. One of the reasons for the success of serverless computing is its straightforward interface that abstracts complex internals of cloud computing resource usage and configurations. However, this approach may result in hiding too much information

There is a sustained and changing voltage between living trees and soil, which may be related to transpiration. If the data of bioelectricity, transpiration characteristics and environmental factors can be observed continuously, thereby finding the relationship between the voltage and transpiration, a new method for transpiration measurement can be provided. In order to carry out long-term observations

Cloud computing is the fastest growing distributed computing paradigm that provides online IT resources on demand by following a pay-as-you-go billing model. The success of this computing paradigm enables cloud providers to offer an extensive collection of parallel computing resources to deal with Big Data workflow scheduling problems. Although, workflow scheduling has been extensively studied, however

The difficulty of sports video detection technology lies in how to detect the end point segment from the complex video speech environment, and the artificial intelligence technology is still in the research stage. Based on this, this study builds a model based on the hidden Markov model. At the same time, the video file noise reduction processing is performed by the spectral subtraction noise reduction

As an emerging and efficient paradigm for multimedia systems, fog networking has attracted widespread attention over the last few years. However, an increasing number of attacks in the current virtualized environments underlines the importance of secure data sharing. Unfortunately, existing multimedia data sharing schemes are not suitable for the networking systems because of the heavy computational

Nowadays, a lot of people have the oral health problems due to continuous changes in the lifestyle such as the person’s speech which can be affected by the malocclusion in teeth and the crooked teeth. The dental problems can cause cavity and bacterial infection. The dental and speech problems mostly can be related to the Alzheimer disease, and cognitive changes. Therefore, the dental information is

Digital communication developed into an imperative element of infrastructure now-a-days. Many applications that operate infrastructure systems are internet-centered. Because of the nontrivial risks of information/data leakage, communication in the systems ought to be secured. Many techniques like cryptography are being employed on a large scale to furtively transmit information. But in the data transmission