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Cloud computing provides scalable computing resources on demand. Monitoring cloud computing resources is important so that resources can be dynamically allocated, migrated, or shut down to meet users' requirements. Challenges in cloud computing monitoring systems include detecting patterns that might lead to failure of the cloud system, detecting m...
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... event transferred to the client application indicates the status of the virtual machine that requires an autoscaling or preventive maintenance. Table 1 shows descriptions of metrics collected from the Ceilometer module of the OpenStack that runs the virtual machines. Table 2 shows some example rules that are created dynamically according to threshold ...Citations
... Bulut bilişim ve hibrit bulut yapıları, modern bilişim sistemlerinin önemli bir parçası haline gelmiştir. Hibrit bulut bilişim izleme yazılım mimarileri [1], bulut hizmetlerinin verimliliğini ve güvenliğini artırma yönünde önemli adımlar atmıştır. Ayrıca, büyük sosyal provenans verileri kullanılarak geliştirilen özel gizlilik politikası ihlal tespiti yaklaşımları [2], veri güvenliği ve mahremiyet konularında yeni ufuklar açmıştır. ...
Bu çalışma, dijital cüzdan için yenilikçi bir altyapı geliştirme hedefini taşımaktadır. Projede, hem kurumsal hem de bireysel kullanıcıların ihtiyaçlarına yönelik bir çözüm geliştirilmesi amaçlanmaktadır. Ana odak, dijital bir cüzdan geliştirerek dijital varlıkların yönetiminin ve saklanmasının kolaylaştırılması üzerinedir. Bu bağlamda, projenin temel hedefleri arasında, yüksek işlem ücretlerine alternatif olarak yerli çözümler sunmak, dijital cüzdan ile varlıkların yerli bulut sistemleri üzerinde güvenle saklanmasını sağlamak ve Paycell ile iş ortaklarının ihtiyaçlarını karşılayacak uygulama geliştirmek bulunmaktadır. Projede, kullanıcıların dijital varlık yönetim yazılımları üzerindeki etkileşimlerinin gerçek zamanlı olarak izlenmesi ve bu verilerin analizi yoluyla anlık eylemler üretmek de bu çalışmanın kapsamı içerisindedir. Böylece, dijital varlık işlemlerinin güvenliğini, verimliliğini ve maliyet etkinliğini artırmak ve genel olarak dijital cüzdan kullanımında kullanıcı deneyimini iyileştirmek amaçlanmaktadır. Sonuç olarak, bu proje, dijital varlık yönetimi ve saklama alanında, güvenlik, kullanılabilirlik ve maliyet etkinliği gibi önemli avantajlar sunmayı hedefleyen, kapsamlı bir çözüm sunmayı amaçlamaktadır. Bu girişimin, dijital cüzdan ekosisteminin genişlemesine ve kullanıcıların dijital varlık yönetimindeki deneyimlerine önemli katkılar sağlaması beklenmektedir.
... Furthermore, nowadays, with the proliferation of cloud services, traditional network and data center environments must be complemented with cloud network monitoring tools in order to keep track of performance indicators. This is accomplished by deploying some lightweight monitoring software agents that collect statistics on physical or virtual servers and physical or virtual network devices [4]. Then, each of these agents will send their data to a repository that typically provides big databased analytics for alerting, diagnostics and displaying summarized information. ...
... Once we have estimated values forλ,μ 1 ,μ 2 , M and N, we obtain λ, µ 1 and µ 2 following Equation (1)-(3), respectively. We also calculate the length of each time slot of the simulated discrete time model, t s , invoking (4). ...
The evolution of commodity hardware makes it possible to use this type of equipment to implement traffic monitoring systems. A preliminary empirical evaluation of a network traffic probe based on Linux indicates that the system performance has significant losses as the network rate increases. To assess this issue, we consider a model with two tandem queues and a moving server. In this system, we formulate a three-dimensional Markov Decision Process in continuous time. The goal of the proposed model is to determine the position of the server in each time slot so as to optimize the system performance which is measured in terms of throughput. We first formulate an equivalent discrete-time Markov Decision Process and we propose a numerical method to characterize the solution of our problem in a general setting. The solution we obtain in this problem has been tested for a wide range of scenarios and, in all the instances, we observe that the optimality is close to a threshold type policy. We also consider a real probe and we validate the good performance of threshold policies in real applications.
... Moreover, other contributions spend time explaining how to use machine learning and artificial intelligence for software monitoring such as A. Norouzi et al. [678], S. Kuutti et al. [679] and G. Georgakos et al. [680] or discussing the effects of software aging D. L. Parnas et al. [681] or J. Costa et al. [682]. On the other hand, from IT, we can highlight some papers about software monitoring in cloud computing, such as M. Aktas et al. [683], J. Spring et al. [684], D. Tamburri et al. [685] or J. Shao et al. [686], in IoT, such as T. Maksymyuk et al. [687] or A. Razzag et al. [688], or even more safety critical domains such as Industry from I. Rakhmonov et al. [689] or S. He et al. [690]. ...
Over the last few decades, automotive embedded Information and Communication Technology (ICT) systems have been used to enhance vehicle performance and enrich people’s driving experience, increasing the panel of software features within them. However, even though until now automakers have kept up with the innovation pace in terms of the functionalities that have been offered to passengers, the majority of automakers’ efforts have concentrated on bringing in these new functionalities by adding an unceasingly larger set of ECUs. All of this has been done without evolving any of the embedded software architecture consequently, due to budgetary constraints, legislative limitations, retro-compatibility problems, and a lack of awareness of the trending IT innovation. This unbalanced progress has then led to a substantial increase in in-vehicle architectural complexity, which has become a major concern for automakers nowadays as it makes the vehicle repairing process more complex, decreases software traceability and clashes with the objective of having higher business flexibility, modularity, and dynamicity within the vehicles. In this paper, we are going to go through literature, both academic and industrial, and propose a comprehensive study into automotive system transformation. We begin by giving a detailed analysis of the causes of evolution under five axes - i.e., society, business, industry, application, and technical. Then, we discuss the convergence of cars and software life cycles and propose a three-layered analysis of automotive ICT systems consisting of architecture design, software pipelines, and run-time management. Finally, we are going to propose certain detailed guidelines on the evolution perspectives for automotive systems through deriving from the convergence of advances in IT, as well as current and future automotive environmental constraints.
... Figure 2 represents the architectural overview of a hybrid cloud model. The features of a hybrid cloud system are listed as follows [4,5]. Similarly, service level agreement explores the facility that is given by the cloud vendor. ...
Cloud storage systems are widely employed in many applications due to their improvement in cost, storage availability and security. Hybrid cloud platform refers to the architecture of a cloud system that combines more than one computing environments at a time. It can be either with one public and one private platform or the combination of two private or two public platforms. The hybrid cloud platform has the ability to share the information among the connected systems and that can be processed parallelly while accessing the data. The data that are stored in cloud platforms are mostly in unstructured format that could not be used for any applications like prediction, recommendation, and estimations. This paper reviews the attainments of the previous works that were used for data distribution and partitioning in a hybrid cloud platform, by ensuring the privacy and security of the stored data. The work also explores the future directions on the unstructured data processing by summarizing the research issues observed from the review analysis.
... A hybrid cloud mixes a private cloud with public cloud services, with one or more points of contact between the two. The goal is to establish a uniform, predictable, and very well computing environment by combining data and services from several cloud models [20]. Amazon, Microsoft, Google, Cisco, and NetApp are the top five hybrid cloud providers [21]. ...
The emergence of several computing paradigms, the most recent cloud computing, has resulted from significant technological advances in the information and communication technologies (ICT) sector in the last decades, with the most significant improvements in internet services and virtualization techniques. Individuals and businesses may access various cloud services and solutions from some big cloud service providers worldwide. As a result, more businesses are migrating to the cloud, causing the cloud services industry to expand. Organizations can profit from cloud technology in various ways, but there are also dangers and issues connected with this phrase. Cloud computing is a way to improve Ecommerce by making it easier for people to buy and sell things. This paper explains the concept and features of cloud computing and how cloud computing can help Ecommerce.
... Computational and Mathematical Methods in Medicine informatization development and wisdom tourism industry layout can effectively achieve mutual benefit and win-win situation. To strengthen rural tourism informatization of wisdom tourism synergistic development mainly tourism development marketing, service management and tourism project design, and other levels to achieve synergistic development and wisdom tourism as a carrier to rural tourism service information conduction, the process of rural tourism informatization construction mainly plays a terminal service management role, that is, to achieve offline tourism services and management planning [14][15][16][17]. Rural tourism information development background and intelligent tourism industry integration should give rural tourism certain help in tourism development innovation. ...
Although the “Internet+” technologies (big data and cloud computing) have been implemented in many industries, each industry involved in rural tourism economic information services has its own database, and there are still vast economic information resources that have not been exploited. Z travel agency through rural tourism enterprise third-party information services and mobile context-awareness-based Z travel has achieved good economic and social benefits by deep value mining and innovative application of the existing data of the enterprise through the third-party information service of rural tourism enterprises and mobile context-aware travel recommendation service. It clearly demonstrates that, in order to maximise the benefits of economic data, rural tourist businesses should focus not only on the application of new technologies and methodologies but also on the core of demand and data-driven and thoroughly investigate the potential value of current data. This paper mainly analyzes the problems related to how rural tourism can be upgraded under the smart tourism platform, with the aim of improving the development of China’s rural tourism industry with the help of an integrated smart tourism platform, and proposes a hybrid cloud-based integrated system of smart scenic rural tourism information services, which can meet the actual use needs of rural tourism, with good shared service effect and platform application performance, and promote the development of rural tourism and resource utilization rate.
... Studies that propose a monitoring framework approach to task scheduling include [9], [14], [25], [26]. Liu and Li utilize agent technology but present no experiments on the implementation and evaluation of the model and its efficiency. ...
... Azumah et al. [9], [14] present a process mining monitoring mechanism that can influence scheduling in the hybrid cloud towards achieving a more desirable and proportionate VM spawning. Aktas [25] proposes a monitoring software architecture and its capacity to handle large volumes of events, but the monitoring rules are preset. Awada [30] presented a hybrid cloud federation approach that focuses on packing application onto a resource in order to maximize its utilization, rather than allowing the default scheduler to only award resources based on their availability. ...
—The hybrid cloud inherits the best aspects of both the public and private clouds. One such benefit is maintaining control of
data processing in a private cloud whilst having nearly elastic resource availability in the public cloud. However, the public and private
cloud combination introduces complexities such as incompatible security and control mechanisms, among others. The result is a
reduced consistency of data processing and control policies in the different cloud deployment models. Cloud load-balancing is one
control mechanism for routing applications to appropriate processing servers in compliance with the policies of the adopting
organization. This paper presents a process-mining influenced load-balancer for routing applications and data according to dynamically
defined business rules. We use a high-level Colored Petri Net (CPN) to derive a model for the process mining-influenced load-balancer
and validate the model employing live data from a selected hospital.
... Upon examination the literature, we observe different distributed software architectures designed for managing data or metadata. [16][17][18] Examples of these architectures are designed in for different domains such as provenance management, 16 social networks, 17 and cloud computing. 18 There exists also some work in workflow-based distributed data analysis studies. ...
... [16][17][18] Examples of these architectures are designed in for different domains such as provenance management, 16 social networks, 17 and cloud computing. 18 There exists also some work in workflow-based distributed data analysis studies. An XML-based workflow mechanism can dramatically improve the orchestration process for data analysis. ...
... 21 Moreover, our early work on distributed workflows was presented at another conference. 22 There exists a number of studies focusing on distributed software architecture that are designed to manage and process large scale metadata in different domains such as social media, 23,24 weather forecasting, 25 cloud monitoring systems, 18 and information systems. 26 These studies mainly focus on designing and implementing scalable and high-performance systems that work with negligible processing overheads. ...
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 this need, we propose a hybrid distributed software architecture in this manuscript. The proposed architecture manages machine learning models for both supervised and unsupervised machine learning data analysis workflows. To show the usability of the proposed architecture, we implement a prototype for the banking sector as a case study. The prototype application includes two data analysis workflows: a workflow for predicting the loan usage tendency of customers, and a workflow for clustering the customers based on the usage patterns of banking loans. The prototype is tested on a large scale banking dataset. Performance tests were carried out to investigate the performance in terms of both responsiveness and scalability of the system. The results obtained reveal the usability of the proposed architecture.
... We observe some studies that focus on systems that are designed for large-scale distributed data and metadata management in different domains [18][19][20]. These studies focus on designing and implementing scalable and high-performance systems focusing on large-scale management of data/metadata. ...
... We focus on user's behavioral data and analyze the behavioral data to detect the sequential patterns of interests. Some serviceoriented scientific applications emphasize large-scale distributed data and metadata management in different domains [22][23][24]. These studies mainly focus on designing and implementing scalable and high-performance systems that concentrate on large-scale management of data/metadata. ...
