Wrist cracks are the most common sort of cracks with an excessive occurrence rate.For the routine detection of wrist cracks,conventional radiography(X-ray medical imaging)is used but periodically issues are presented ...Wrist cracks are the most common sort of cracks with an excessive occurrence rate.For the routine detection of wrist cracks,conventional radiography(X-ray medical imaging)is used but periodically issues are presented by crack depiction.Wrist cracks often appear in the human arbitrary bone due to accidental injuries such as slipping.Indeed,many hospitals lack experienced clinicians to diagnose wrist cracks.Therefore,an automated system is required to reduce the burden on clinicians and identify cracks.In this study,we have designed a novel residual network-based convolutional neural network(CNN)for the crack detection of the wrist.For the classification of wrist cracks medical imaging,the diagnostics accuracy of the RN-21CNN model is compared with four well-known transfer learning(TL)models such as Inception V3,Vgg16,ResNet-50,and Vgg19,to assist the medical imaging technologist in identifying the cracks that occur due to wrist fractures.The RN-21CNN model achieved an accuracy of 0.97 which is much better than its competitor`s approaches.The results reveal that implementing a correct generalization that a computer-aided recognition system precisely designed for the assistance of clinician would limit the number of incorrect diagnoses and also saves a lot of time.展开更多
Data centers are being distributed worldwide by cloud service providers(CSPs)to save energy costs through efficient workload alloca-tion strategies.Many CSPs are challenged by the significant rise in user demands due ...Data centers are being distributed worldwide by cloud service providers(CSPs)to save energy costs through efficient workload alloca-tion strategies.Many CSPs are challenged by the significant rise in user demands due to their extensive energy consumption during workload pro-cessing.Numerous research studies have examined distinct operating cost mitigation techniques for geo-distributed data centers(DCs).However,oper-ating cost savings during workload processing,which also considers string-matching techniques in geo-distributed DCs,remains unexplored.In this research,we propose a novel string matching-based geographical load balanc-ing(SMGLB)technique to mitigate the operating cost of the geo-distributed DC.The primary goal of this study is to use a string-matching algorithm(i.e.,Boyer Moore)to compare the contents of incoming workloads to those of documents that have already been processed in a data center.A successful match prevents the global load balancer from sending the user’s request to a data center for processing and displaying the results of the previously processed workload to the user to save energy.On the contrary,if no match can be discovered,the global load balancer will allocate the incoming workload to a specific DC for processing considering variable energy prices,the number of active servers,on-site green energy,and traces of incoming workload.The results of numerical evaluations show that the SMGLB can minimize the operating expenses of the geo-distributed data centers more than the existing workload distribution techniques.展开更多
In recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a n...In recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Internet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service(DDoS) attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.展开更多
The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of r...The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.展开更多
Over the past few years, numerous traffic safety applications have been developed using vehicular ad hoc networks(VANETs). These applications represent public interest and require network-wide dissemination techniques...Over the past few years, numerous traffic safety applications have been developed using vehicular ad hoc networks(VANETs). These applications represent public interest and require network-wide dissemination techniques. On the other hand, certain non-safety applications do not require network-wide dissemination techniques.Such applications can be characterized by their individual interest between two vehicles that are geographically apart. In the existing literature, several proposals of unicast protocols exist that can be used for these non-safety applications. Among the proposals, unicast protocols for city scenarios are considered to be most challenging.This implies that in city scenarios unicast protocols show minimal persistence towards highly dynamic vehicular characteristics, including mobility, road structure, and physical environment. Unlike other studies, this review is motivated by the diversity of vehicular characteristics and difficulty of unicast protocol adaption in city scenarios.The review starts with the categorization of unicast protocols for city scenarios according to their requirement for a predefined unicast path. Then, properties of typical city roads are discussed, which helps to explore limitations in efficient unicast communication. Through an exhaustive literature review, we propose a thematic taxonomy based on different aspects of unicast protocol operation. It is followed by a review of selected unicast protocols for city scenarios that reveal their fundamental characteristics. Several significant parameters from the taxonomy are used to qualitatively compare the reviewed protocols. Qualitative comparison also includes critical investigation of distinct approaches taken by researchers in experimental protocol evaluation. As an outcome of this review, we point out open research issues in unicast routing.展开更多
文摘Wrist cracks are the most common sort of cracks with an excessive occurrence rate.For the routine detection of wrist cracks,conventional radiography(X-ray medical imaging)is used but periodically issues are presented by crack depiction.Wrist cracks often appear in the human arbitrary bone due to accidental injuries such as slipping.Indeed,many hospitals lack experienced clinicians to diagnose wrist cracks.Therefore,an automated system is required to reduce the burden on clinicians and identify cracks.In this study,we have designed a novel residual network-based convolutional neural network(CNN)for the crack detection of the wrist.For the classification of wrist cracks medical imaging,the diagnostics accuracy of the RN-21CNN model is compared with four well-known transfer learning(TL)models such as Inception V3,Vgg16,ResNet-50,and Vgg19,to assist the medical imaging technologist in identifying the cracks that occur due to wrist fractures.The RN-21CNN model achieved an accuracy of 0.97 which is much better than its competitor`s approaches.The results reveal that implementing a correct generalization that a computer-aided recognition system precisely designed for the assistance of clinician would limit the number of incorrect diagnoses and also saves a lot of time.
文摘Data centers are being distributed worldwide by cloud service providers(CSPs)to save energy costs through efficient workload alloca-tion strategies.Many CSPs are challenged by the significant rise in user demands due to their extensive energy consumption during workload pro-cessing.Numerous research studies have examined distinct operating cost mitigation techniques for geo-distributed data centers(DCs).However,oper-ating cost savings during workload processing,which also considers string-matching techniques in geo-distributed DCs,remains unexplored.In this research,we propose a novel string matching-based geographical load balanc-ing(SMGLB)technique to mitigate the operating cost of the geo-distributed DC.The primary goal of this study is to use a string-matching algorithm(i.e.,Boyer Moore)to compare the contents of incoming workloads to those of documents that have already been processed in a data center.A successful match prevents the global load balancer from sending the user’s request to a data center for processing and displaying the results of the previously processed workload to the user to save energy.On the contrary,if no match can be discovered,the global load balancer will allocate the incoming workload to a specific DC for processing considering variable energy prices,the number of active servers,on-site green energy,and traces of incoming workload.The results of numerical evaluations show that the SMGLB can minimize the operating expenses of the geo-distributed data centers more than the existing workload distribution techniques.
基金Project supported by University of Malaya,Malaysia(No.FP034-2012A)
文摘In recent years, the Internet has enabled access to widespread remote services in the distributed computing environment; however, integrity of data transmission in the distributed computing platform is hindered by a number of security issues. For instance, the botnet phenomenon is a prominent threat to Internet security, including the threat of malicious codes. The botnet phenomenon supports a wide range of criminal activities, including distributed denial of service(DDoS) attacks, click fraud, phishing, malware distribution, spam emails, and building machines for illegitimate exchange of information/materials. Therefore, it is imperative to design and develop a robust mechanism for improving the botnet detection, analysis, and removal process. Currently, botnet detection techniques have been reviewed in different ways; however, such studies are limited in scope and lack discussions on the latest botnet detection techniques. This paper presents a comprehensive review of the latest state-of-the-art techniques for botnet detection and figures out the trends of previous and current research. It provides a thematic taxonomy for the classification of botnet detection techniques and highlights the implications and critical aspects by qualitatively analyzing such techniques. Related to our comprehensive review, we highlight future directions for improving the schemes that broadly span the entire botnet detection research field and identify the persistent and prominent research challenges that remain open.
基金Project supported by the Malaysian Ministry of Higher Education under the University of Malaya High Impact Research Grant(No.UM.C/HIR/MOHE/FCSIT/03)
文摘The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.
基金Project supported by the High Impact Research,University of Malaya and Ministry of Higher Education of Malaysia(No.UM.C/HIR/MOHE/FCSIT/09)
文摘Over the past few years, numerous traffic safety applications have been developed using vehicular ad hoc networks(VANETs). These applications represent public interest and require network-wide dissemination techniques. On the other hand, certain non-safety applications do not require network-wide dissemination techniques.Such applications can be characterized by their individual interest between two vehicles that are geographically apart. In the existing literature, several proposals of unicast protocols exist that can be used for these non-safety applications. Among the proposals, unicast protocols for city scenarios are considered to be most challenging.This implies that in city scenarios unicast protocols show minimal persistence towards highly dynamic vehicular characteristics, including mobility, road structure, and physical environment. Unlike other studies, this review is motivated by the diversity of vehicular characteristics and difficulty of unicast protocol adaption in city scenarios.The review starts with the categorization of unicast protocols for city scenarios according to their requirement for a predefined unicast path. Then, properties of typical city roads are discussed, which helps to explore limitations in efficient unicast communication. Through an exhaustive literature review, we propose a thematic taxonomy based on different aspects of unicast protocol operation. It is followed by a review of selected unicast protocols for city scenarios that reveal their fundamental characteristics. Several significant parameters from the taxonomy are used to qualitatively compare the reviewed protocols. Qualitative comparison also includes critical investigation of distinct approaches taken by researchers in experimental protocol evaluation. As an outcome of this review, we point out open research issues in unicast routing.
