Abstract: —Cloud computing is an Internet-based computing pattern through which shared resources are provided to devices on-demand. It is an emerging but promising paradigm to integrating mobile devices into cloud computing, and the integration performs in the cloud based hierarchical multi-user data-shared environment. With integrating into cloud computing, security issues such as data confidentiality and user authority may arise in the mobile cloud computing system, and it is concerned as the main constraints to the developments of mobile cloud computing. In order to provide safe and secure operation, a hierarchical access control method using modified hierarchical attribute-based encryption (M-HABE) and a modified three-layer structure is proposed in this paper. In a specific mobile cloud computing model, enormous data which may be from all kinds of mobile devices, such as smart phones, functioned phones and PDAs and so on can be controlled and monitored by the system, and the data can be sensitive to unauthorized third party and constraint to legal users as well. The novel scheme mainly focuses on the data processing, storing and accessing, which is designed to ensure the users with legal authorities to get corresponding classified data and to restrict illegal users and unauthorized legal users get access to the data, which makes it extremely suitable for the mobile cloud computing paradigms.

Abstract: Unmanned Aerial Vehicle (UAV) technology has been widely applied in both military and civilian applications. Recent researches on UAV systems feature in the dramatic augment of the variety and number of equipped sensors, which results in such an issue that multiple UAVs cannot afford to handle the big data generated by a range of sensors in the air. Considering this practical problem, in this paper, we propose a cloud-based UAV system which incorporates the computing capability of the terrestrial cloud into the UAV systems. Relying on proposed cloud-based UAV system, one critical theoretic issue is how to acquire the big data generated by the sensors while guaranteeing a stable operation state of the system. First, we analyze the cloud-based system's on-demand service ability as well as its impact on UAVs’ control procedure. Second, the UAV cloud control system is modeled as a network control system. Moreover, the stable condition of the UAV cloud control system is derived, which reveals the relationship between the acquisition rate of sensor data and the stability of the cloud-based UAV system. Finally, simulations are conducted to verify the effectiveness of our theoretical analysis.

Abstract: While High Performance Computing (HPC) centers continuously evolve to provide more computing power to their users, we observe a wish for the convergence between Cloud Computing (CC) and High Performance Computing (HPC) platforms, with the commercial hope to see Cloud Computing (CC) infrastructures to eventually replace in-house facilities. If we exclude the performance point of view where many previous studies highlight a non-negligible overhead induced by the virtualization layer at the heart of every Cloud middleware when running a HPC workload, the question of the real cost-effectiveness is often left aside with the intuition that, most probably, the instances offered by the Cloud providers are competitive from a cost point of view. In this article, we wanted to assert (or infirm) this intuition by analyzing what composes the Total Cost of Ownership (TCO) of an in-house HPC facility operated internally since 2007. This Total Cost of Ownership (TCO) model is then used to compare with the induced cost that would have been required to run the same platform (and the same workload) over a competitive Cloud IaaS offer. Our approach to address this price comparison is three-fold. First we propose a theoretical price-performance model based on the study of the actual Cloud instances proposed by one of the major Cloud IaaS actors: Amazon Elastic Compute Cloud (EC2). Then, based on the HPC facility TCO analysis we propose a hourly price comparison between our in-house cluster and the equivalent EC2 instances. Finally, based on the experimental benchmarking on the local cluster and on the Cloud instances we propose an update of the former theoretical price model to reflect the real system performance. The results obtained advocate in general for the acquisition of an in-house HPC facility, which balances the common intuition in favor of Cloud Computing platforms, would they be provided by the reference Cloud provider worldwide.

Abstract: Cloud computing provides on-demand access to affordable hardware (eg, multi-core CPUs, GPUs, disks, and networking equipment) and software (eg, databases, application servers and data processing frameworks) platforms with features such as elasticity, pay-per-use, low upfront investment and low time to market This has led to the proliferation of business critical applications that leverage various cloud platforms Such applications hosted on single/multiple cloud provider platforms have diverse characteristics requiring extensive monitoring and benchmarking mechanisms to ensure run-time Quality of Service (QoS) (eg, latency and throughput) This paper proposes, develops and validates CLAMBS—Cross-Layer Multi-Cloud Application Monitoring and Benchmarking as-a-Service for efficient QoS monitoring and benchmarking of cloud applications hosted on multi-clouds environments The major highlight of CLAMBS is its capability of monitoring and benchmarking individual application components such as databases and web servers, distributed across cloud layers (*-aaS), spread among multiple cloud providers We validate CLAMBS using prototype implementation and extensive experimentation and show that CLAMBS efficiently monitors and benchmarks application components on multi-cloud platforms including Amazon EC2 and Microsoft Azure

Abstract: Quality of cloud service (QoS) is one of the crucial factors for the success of cloud providers in mobile cloud computing. Context-awareness is a popular method for automatic awareness of the mobile environment and choosing the most suitable cloud provider. Lack of context information may harm the users’ confidence in the application rendering it useless. Thus, mobile devices need to be constantly aware of the environment and to test the performance of each cloud provider, which is inefficient and wastes energy. Crowdsourcing is a considerable technology to discover and select cloud services in order to provide intelligent, efficient, and stable discovering of services for mobile users based on group choice. This article introduces a crowdsourcing-based QoS supported mobile cloud service framework that fulfills mobile users’ satisfaction by sensing their context information and providing appropriate services to each of the users. Based on user's activity context, social context, service context, and device context, our framework dynamically adapts cloud service for the requests in different kinds of scenarios. The context-awareness based management approach efficiency achieves a reliable cloud service supported platform to supply the Quality of Service on mobile device.

Abstract: The expanding cloud computing services offer great opportunities for consumers to find the best service and best pricing. Meanwhile, it also raises new challenges for consumers who need to select the best service out of such a huge pool since it will be time-consuming for consumers to collect the necessary information and analyze all service providers to make the decision. Therefore, in this paper, we propose a novel brokerage-based architecture in the cloud, where the cloud brokers is responsible for the service selection. We also design an efficient indexing structure, called B $^{cloud}$ -tree, for managing the information of a large number of cloud service providers. We then develop the service selection algorithm that recommends most suitable cloud services to the cloud consumers. We carry out extensive experimental studies on real and synthetic cloud data, and demonstrate a significant performance improvement over previous approaches.

Abstract: Today’s medical industry can be represented by a human-centered u-healthcare paradigm that is available and accessible anywhere, where high-tech IT can serve as the basis at any time and any place. In addition, in the medical industry, studies of many of the developments and applications are actively conducted based on the development of information communication technology. The aim of medical-information systems is the construction of an advanced IT and integrated u-healthcare system that evolves in the direction of integrated medical-based IT-convergence systems. Accordingly, to resolve the problems of telemedicine, in terms of the remote access to medical data, some public and private initiatives have been proposed, ranging from patient-mobility approaches to medical data. In addition, regarding GENICloud, which provides links with the existing future Internet testbeds and the Eucalyptus Cloud, two out of the seven GENIAM APIs have been announced as the common APIs of the future Internet testbeds in GENI, and they have been implemented and are provided. In the present GENI Cloud system, due to the provision of limited APIs, restrictions may occur in the future Internet testbeds and the Eucalyptus Cloud system management. Therefore, this study proposes a cloud-based mobile health service for the enhancement of the quality of service (QoS) including factors such as reliability and response time to resolve the problems of the broadband-communication infrastructure in the existing mobile health service and the delay problem on the wireless body area network. In this paper, we propose the cloud-based u-healthcare network with a QoS-guaranteed mobile health service. For this method, the TMO-distribution object model that was used in the existing research to implement a reliable and efficient cloud system for users was not used, and instead, a cloud-platform environment was built up through the construction of a distributed system based on a cluster-based mobile object. For this purpose, this study considered the characteristics of the wireless-communication environments between the terminals and the cloud servers in the mobile cloud environment and the proposed cloud mobility services and the specialized mobile cloud-control software. Later, for linkages with cloud computing environments and testbeds was proposed. In addition, this study carried out a cloud mobility-control design to provide a service in the mobile cloud environment that is based on the actual future Internet testbeds. Lastly, based on the structured cloud-platform environment, this study designed access interfaces to provide a mobile healthcare service in consideration of the user convenience. For the mobile-service access interfaces, since the same service interfaces can be used to access the characteristics and functions of all of the applications from browsers and device clients, the model-view-controller structure of the platform was designed, including the components for the further improvement of the requirements, reuse, and maintenance of the codes in medium and large distributed systems.

Abstract: In order to improve simulation performance and to integrate simulation resources among geographically distributed locations, the concept of distributed simulation is proposed. Several types of distributed simulation standards, such as DIS and HLA, are established to formalize simulations and achieve reusability and interoperability of simulation components. To implement these distributed simulation standards and to manage the underlying system of distributed simulation applications, we employ grid computing and cloud computing technologies. These tackle the details of operation, configuration, and maintenance of simulation platforms in which simulation applications are deployed. However, for modelers who may not be familiar with the management of distributed systems, it is challenging to make a simulation-run-ready environment among different types of computing resources and network environments. In this article, a new multi-layered cloud-based scheme is proposed for enabling modeling and simulation based on different distributed simulation standards. This scheme is designed to ease the management of underlying resources and to achieve rapid elasticity that can provide unlimited computing capability to end users; it considers energy consumption, security, multi-user availability, scalability, and deployment issues. A mechanism for handling diverse network environments is described; by adopting it, idle public resources can be easily configured as additional computing capabilities for the local resource pool. A fast deployment model is built to relieve the migration and installation process of this platform. An energy-saving strategy is utilized to reduce the consumption of computing resources. Security components are implemented to protect sensitive information and block malicious attacks in the cloud. In the experiments, the proposed scheme is compared with its corresponding grid computing platform; the cloud computing platform achieves similar performance, but incorporates many advantages that the Cloud can provide.

Abstract: How can applications be deployed on the cloud to achieve maximum performance? This question is challenging to address with the availability of a wide variety of cloud Virtual Machines (VMs) with different performance capabilities. The research reported in this paper addresses the above question by proposing a six step benchmarking methodology in which a user provides a set of weights that indicate how important memory, local communication, computation and storage related operations are to an application. The user can either provide a set of four abstract weights or eight fine grain weights based on the knowledge of the application. The weights along with benchmarking data collected from the cloud are used to generate a set of two rankings—one based only on the performance of the VMs and the other takes both performance and costs into account. The rankings are validated on three case study applications using two validation techniques. The case studies on a set of experimental VMs highlight that maximum performance can be achieved by the three top ranked VMs and maximum performance in a cost-effective manner is achieved by at least one of the top three ranked VMs produced by the methodology.

Abstract: Cloud computing is an information technology paradigm enabling companies to sell computing resources more dynamically. Software and hardware are now commodities leased on demand. Because computer systems leased from a cloud service provider, virtual machines, are typically connected to internet, they can host web services, which are frequently components of service oriented architectures (SOAs). Such architectures have recently been adopted in factory automation, as they allow systems to reach high levels of decentralization and loose-coupling. SOA-based Factory automation systems combine physical production equipment with web services that belong to the information processing (cyber) domain, and they are therefore highly cyber-physical. When some of the services are deployed on cloud resources, SOA-based factory automation systems can be classified cloud-based cyber-physical systems. Each service in such a system is typically able to perform rather simple, atomic operations, whereas achievement of complex goals requires that the services be composed to collaboratively carry out workflows. This article investigates the use of cloud resources in automatic service workflow composition. To facilitate the acquisition and utilization of cloud resources, a system of two specialized web services is proposed. The system includes a web service that dynamically deploys virtual machines to carry out planning processes, thereby exhibiting artificial intelligence. Finally, this paper demonstrates the integration of the system with a previously proposed semantic web service composition framework.

Abstract: Software testing is a challenge for several software development companies, particularly for companies involved in large-scale projects. To cope with these challenges employing Cloud computing (CC) technology would be the best choice. Testing-as-a-service (TaaS) is a pay-for-use model of testing for cloud-based applications, SaaS, and clouds itself that provide internet-based testing services for software development organization (SDO). However, moving testing to the CC environment is not free of cost, nor it is the best possible solution for all testing problems. Moreover, recent studies confirm lack of a comprehensive model for assessing the suitability of CC for software testing. To guide SDO on the adoption of CC for software testing, the proposed study aims at developing a cloud testing adoption assessment model, an application of multi-attribute decision-making method, based on the codified knowledge of field expert. The proposed model will provide decision support to SDO in the form of various predictors and determinants that will guide SDO towards CC adoption.

Abstract: Cloud computing emerges as one of the most promising technologies and is widely used in many fields. Cloud computing has been considered as an appropriate environment for telecommunication services. However, more threats appear in the migration of applications and telecommunication services from a traditional computing environment to a cloud platform. Traditional device-centric security systems are not effective as resources in the cloud are out of the users control. Data storage and processing for a telecommunication service in the cloud can be structured as a data service in PaaS (Platform-as-a-Service) level. Upper-level applications exchange data with the data service. In this paper, we propose a domain-divided security model in which different security policies are separately applied for three domains: the data storage domain, the data processing domain and the data transmission domain. In addition, security policies can be configured for upper-level applications based on their security requirements. Experimental results show that our proposed security model is both practical and lightweight as it can provide differentiated security protection for cloud computing-based telecommunication service with a low overhead.

Abstract: This paper presents the framework of cloud‐based software test data generation service (CSTS) that caters to cost‐effective test data generation service in a cloud environment. In contrast to existing conventional or cloud‐based testing frameworks, CSTS has a number of unique benefits. First, CSTS is designed to facilitate test data generation in minimum time and cost. Second, unlike existing frameworks which mandates clients to opt for resources to test their jobs, CSTS guides customer for selecting best cluster configuration in order to minimize the cost. While the existing models do not provide any solution for trust establishment in cloud computing services, CSTS delivers it by implementing security mechanism with the provision of role based access control. The security mechanism proposed in this paper ensures the protection of data and code of different users. Third, CSTS provides a mathematical pricing model to fulfill the expectations of customers and also to maximize the net profit of service providers. Cloud service request model has also been designed that postulates service level agreements between customers and service providers. We have evaluated, compared, and analyzed our framework and have found that it outperforms other existing cloud‐based frameworks.

Abstract: Testing is a vital activity in software development. The ISO/IEC has defined a standard for system and software quality models called ISO/IEC 25010:2011 to be a guideline and scope for testing any applications. Testing of mobile applications according to this standard, however, is more challenging than other types of software. The diversity of Android devices and various versions of Android operating system, for example, has created a large fragmentation of the Android platform. This fragmentation hinders testing of Android applications especially in relation to portability and compatibility. Existing solutions are either neglecting portability and compatibility issues or lack flexibility in fulfilling needs of the different organizations. We propose a cloud testing model to address the fragmentation of Android platform and provide automated application testing services on the actual devices. The model can be configured in the public, private or hybrid setups to suit individual organizations' needs and budget. A prototype was built based on the model. 10 Android testers used the prototype and the Android Emulator to perform mobile application testing. Results show that the model has the potential to manage the challenging portability and compatibility testing on the Android platform in a flexible and scalable manner.

Abstract: Mobile devices may offload their applications to a virtual machine running on a cloud host. This application may fork new tasks which require virtual machines of their own on the same physical machine. Achieving satisfactory performance level in such a scenario requires flexible resource allocation mechanisms in the cloud data center. In this paper we present two such mechanisms which use prioritization: one in which forked tasks are given full priority over newly arrived tasks, and another in which a threshold is established to control the priority so that full priority is given to the forked tasks if their number exceeds a predefined threshold. We analyze the performance of both mechanisms using a Markovian multiserver queueing system with two priority levels to model the resource allocation process, and a multi-dimensional Markov system based on a Birth-Death queueing system with finite population, to model virtual machine provisioning. Our performance results indicate that the threshold-based priority scheme not only performs better, but can also be tuned to achieve the desired performance level.

Abstract: As earliest the software defects uncovered and fixed in STLC, the lesser the amount required to fix it. With the advent of cloud computing a lot of new opportunities for business opens, especially in the field of software testing & maintenance. The cloud testing methodology is the set of techniques, tools and process to be followed while undergoing tests for cloud service. A new methodology is proposed to test the cloud which is known as SUPerB methodology, deals with cloud security, user acceptance, performance and business requirements. Successful implementation of SUPerB methodology for cloud testing might establish a strong foundation for an organization to lead in the market. Software vulnerabilities give rise to the cyber-crime and related risk associated with it just due to lapses in security policies, which increases the security breaches in the business. Efficiency of a system can be measured in terms of performance testing. While selecting a test tool, users must keep certain characteristics of cloud testing tool in consideration, like platform compatibility, available support, flexibility and service cost. It might be possible that an organization has to deal with a number of challenges while adopting cloud computing services.

Abstract: In the fast-changing world of information technology (IT), IT teams in higher education are facing a growing challenge to provide the necessary IT infrastructure to support teaching and learning ac...

Abstract: Testing large-scale distributed systems (also known as testing in the large) is a challenge that spreads across different technical domains and areas of expertise. Current methods and tools provide some minimal guarantees in relation to the correctness of their functional properties and have serious limitations when evaluating their extra-functional properties in realistic conditions, such as scalability, availability and performance efficiency. Cloud Testing and more specifically "testing in the cloud'' has arisen to tackle those challenges. In this new paradigm, cloud-based environment and infrastructure are used to run realistic end-to-end and/or system-level tests, collect test data and analyse them. In this paper we present a set of cloud-native services to take from the tester the responsibility of managing the resources and complementary services required to simulate realistic operational conditions and production environments. Specifically, they provide cloud testing capabilities such as logs and measurements collection from both testing jobs and system under test; test data analytics and visualization; provisioning and operation of additional services and processes to replicate realistic production ecosystems; support to scalability and diversity of underlying testing infrastructure; and replication of the operational conditions of the software under test through its instrumentation. We present the architecture of the cloud testing solution and the detailed design of each of the services; we also evaluate their relative contribution to satisfy different needs in the context of test execution.

Abstract: Cloud computing is attracting the interest of many businesses around the world by offering feasible solutions towards hosting software applications and providing convenient development and testing environments. Cloud computing has developed enormously that it changed the management practices of dealing with computer systems and services. Because of cloud computing; testing as a service (TaaS) was created. Despite the facilities provided by TaaS, it produced some issues and challenges, particularly in cloud-based testing environments. Those issues are needed to be addressed and fixed. This paper reviews and addresses a set of challenges and benefits of cloud testing among with a theoretical comparison between cloud-based testing environment and traditional testing for regular systems.

Abstract: As the cloud computing is spreading round the world, want of inter cloud communication is turning into a growing in the organizations. It’s inflicting the researchers to specialize in first, creating it potential to communicate between two or additional clouds and second security of communication is to considered up to utmost level. Hybrid cloud storage may be a storage technique that uses internal and external cloud applications, infrastructure and storage systems to create integrated storage design. Hybrid cloud may be a classification in cloud computing atmosphere that utilizes a collaboration of on-premises, private cloud and third-party, public cloud services with orchestration between the two platforms. By permitting workloads to transfer between private and public clouds, the computing requirements and prices modification, hybrid cloud offers businesses larger flexibility and additional information deployment choices. Hybrid cloud is especially valuable for dynamic or extremely changeable workloads. This paper describes the needs, deployment, storage, applications and issues of hybrid cloud.

Abstract: Runtime testing of large-scale systems running in dynamic and distributed environments is a costly and a resource consuming task. With the aim of handling such runtime validation activity in a cost...

Abstract: The emergence of new service oriented distributed models has raised a number of challenges particularly in relation to the management of distributed infrastructures in dynamic environments, such as the Cloud with changing availability of resources, services and quality of services. In such an environment it is very important that users and applications have some level of assurance that their requirements can be satisfied while trying to optimize the usage of the available resources. This paper presents a new requirement-driven decision making mechanism that is based on a quality assured load balancer for distributed computing systems. We evaluate the approach and demonstrate how it can adapt to user requirements and to the capacity of available resources.

Abstract: with the rapid development of V2X technology, intelligent network connected vehicle combines multidisciplinary emerging technology, where the function, performance and security characters present new features, thus it is necessary to put forward higher requirements on software quality. New combination of multi software testing methods on intelligent connected vehicle is discussed in this paper. In combination with cloud testing platform, software testing framework based on cloud computing is proposed, and the function of each module is elaborated. Finally software quality of safety and reliability evaluation system is summarized to apply on the intelligent connected vehicle, which provides further guidance on the accuracy and efficiency of the software testing.

Abstract: With the rapid growth in information technology, there is a significant increase in research activities in the field of cloud computing. Cloud testing can be interpreted as (i) testing of cloud applications, which involves continuous monitoring of cloud application status to verify Service Level Agreements, and (ii) testing as a cloud service which involves using the cloud as a testing middleware to execute a large-scale simulation of real-time user interactions. This study aims to examine the methodologies and tools used in cloud testing and the current research trends in cloud computing testing.

Abstract: The invention relates to the technical field of cloud testing, in particular to an analysis method and device before SVN resource library testing and computer equipment. The method comprises: detecting whether version submission exists in an SVN resource library or not; if it is detected that the version submission exists in the SVN resource library, obtaining a submitted target version; comparingthe target version with the to-be-compared version to obtain a change file; judging the change category of the change file; according to the change category of the change file, matching a corresponding strategy in a strategy library to obtain a target strategy; analyzing the change file according to a target strategy before testing, and analyzing a character string rule in the change file to obtain a target character string rule; and matching the target character string rule, and marking the matched output information in a corresponding character string to form a report file. The problems that in an existing testing mode, no analysis before testing exists, the whole new version is tested, the testing range is wide, and the testing time is long are solved.

Abstract: The invention relates to a testing device, and in particular relates to a system about a cloud testing method of a low-voltage plastic-shell switch. The system comprises the low-voltage plastic-shellswitch, a transformer terminal unit TTU, a tester, a mobile terminal, a light alarm module and a wireless communication module, and further comprises an instant messaging module; the transformer terminal unit TTU is connected with the low-voltage plastic-shell switch, and used for receiving working state information of the low-voltage plastic-shell switch; the tester is connected with the low-voltage plastic-shell switch and the transformer terminal unit TTU, and used for analyzing test information of the low-voltage plastic-shell switch and sending a test result to a cloud server; the mobileterminal establishes wireless communication with the cloud server through the wireless communication module; the tester comprises a voice prompt module used for performing voice prompt on the test information; the light alarm module is used for giving a light alarm according to the test result; the wireless communication module is used for establishing wireless communication with the cloud server;and the instant messaging module is used for establishing instant messaging between a field staff and a remote technical support staff. By means of the technical scheme provided in the invention, thedisadvantages that testing is not safe and convenient enough and the test efficiency is relatively low in the prior art can be effectively overcome.

Abstract: Mobile operating systems are very lightweight so that the mobiles hardware can easily support the operating system and apps running on it. Some operating systems include additional features like sensor embedding and OTG aka On-The-Go. In this paper, we are going to focus on the performance of heavy applications running on both Android and iOS platforms and their processing delay causes. The performance testing is done with the help of a cloud testing platform i.e. bitbar.cloud. It is basically testing as a service provider which tests the Android and iOS applications with the help of simulated virtual mobile phones which uses Appcrawler and AI Testbot for testing these applications. The file packages need to be uploaded on the cloud platform which should be in the form of .apk and .ipa extension. The uploaded files are then tested by using either AI Testbot or Appcrawler by creating a new test in the Test Run Creator. With the results generated by these methods, we will compare the performance of these heavy applications on the different and their performance delays on the different devices and their underlying operating systems.

Abstract: As Internet technology gradually penetrates into people's life, more and more software applications appear to meet people's needs. Testing is a critical phase in Software Life Cycle. In view of the traditional testing platform, which costs too high and over depends on labor. The software testing platform based on cloud computing is a new testing scheme with high efficiency and low cost. This paper introduces the three-tier architecture of cloud testing platform and the cloud-based test flow. We proposes SoC FPGA as one of the computing resources of cloud testing platform. Cloud platform based on SoC FPGA has the advantages of high speed, low power consumption and low cost. In addition, this paper focuses on the key technology of introducing the SoC FPGA into cloud platform: the elastic scaling mechanism of the SoC FPGA, and finally verifies the superiority of the SoC FPGA computing platform in computing performance and power consumption through experiments.

Abstract: A systematic literature review is presented that surveyed the topic of cloud testing over the period 2012--2017. Cloud testing can refer either to testing cloud-based systems (testing of the cloud) or to leveraging the cloud for testing purposes (testing in the cloud): both approaches (and their combination into testing of the cloud in the cloud) have drawn research interest. An extensive paper search was conducted by both automated query of popular digital libraries and snowballing, which resulted in the final selection of 147 primary studies. Along the survey, a framework has been incrementally derived that classifies cloud testing research among six main areas and their topics. The article includes a detailed analysis of the selected primary studies to identify trends and gaps, as well as an extensive report of the state-of-the-art as it emerges by answering the identified Research Questions. We find that cloud testing is an active research field, although not all topics have received enough attention and conclude by presenting the most relevant open research challenges for each area of the classification framework.