Monitoring and resource management taxonomy in interconnected cloud infrastructures: a survey

Cloud users have recently expanded dramatically. The cloud service providers (CSPs) have also increased and have therefore made their infrastructure more complex. The complex infrastructure needs to be distributed appropriately to various users. Also, the advances in cloud computing have led to the development of interconnected cloud computing environments (ICCEs). For instance, ICCEs include the cloud hybrid, intercloud, multi-cloud, and federated clouds. However, the sharing of resources is not facilitated by specific proprietary technologies and access interfaces used by CSPs. Several CSPs provide similar services but have different access patterns. Data from various CSPs must be obtained and processed by cloud users. To ensure that all ICCE tenants (users and CSPs) benefit from the best CSPs, efficient resource management was suggested. Besides, it is pertinent that cloud resources be monitored regularly. Cloud monitoring is a service that works as a third-party entity between customers and CSPs. This paper discusses a complete cloud monitoring survey in ICCE, focusing on cloud monitoring and its significance. Several current open-source monitoring solutions are discussed. A taxonomy is presented and analyzed for cloud resource management. This taxonomy includes resource pricing, assignment of resources, exploration of resources, collection of resources, and disaster management

Kyamakya K.: Fusion of Neural Network positioning and Database Correlation in localizing a Mobile Terminal

Abstract- Mobile phone location activities have been intensified recently. This work will examine the possibility of combining the Neural Network (NN) positioning and the database correlation (DC) localization system in order to realize a robust RSS based positioning system within a GSM network context. The NN is trained first offline before it use in the positioning unit. Function approximation and classification properties of the NN will be investigated and the best NN architecture will be chosen from a series of candidates. During positioning phase both positioning results from NN and DC are fused with a robust tested method in order to increase the precision of the position estimate. Results show that, the fusion process reduces the positioning error. Keywords- data fusion, database correlation, localization, neural network, mobile positioning. I

An ICT-Based Diabetes Management System Tested for Health Care Delivery in the African Context

The demand for new healthcare services is growing rapidly. Improving accessibility of the African population to diabetes care seems to be a big challenge in most countries where the number of care centers and medical staff is reduced. Information and communication technologies (ICT) have great potential to address some of these challenges faced by several countries in providing accessible, cost-effective, and high-quality health care services. This paper presents the Mobil Diab system which is a telemedical approach proposed for the management of long-term diseases. The system applies modern mobile and web technologies which overcome geographical barriers, and increase access to health care services. The idea of the system is to involve patients in the therapy process and motivate them for an active participation. For validation of the system in African context, a trial was conducted in the Democratic Republic of Congo. 40 Subjects with diabetes divided randomly into control and intervention groups were included in the test. Results show that Mobil Diab is suitable for African countries and presents a number of benefits for the population and public health care system. It improves clinical management and delivery of diabetes care services by enhancing access, quality, motivation, reassurance, efficiency, and cost-effectiveness

Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany

Being able to manage and adjust insulin doses is a key part of managing type-1 diabetes. Children and adolescents with type-1 diabetes mellitus often have serious difficulties with this dosage adjustment. Therefore, this paper aims to investigate the impact of using novel mobile, web and communication technologies in assisting their therapy and treatment. A trial was conducted in the north-eastern part of Germany to evaluate the impact of the “Mobil Diab”, a mobile diabetes management system, on the clinical outcome. 68 subjects aged between 8 and 18 years, divided randomly into control and intervention groups, were included into the study. Metrics such as changes in the quality of metabolic control, changes in psychological parameters, usability and acceptance of the technology were used for evaluation purpose. Metabolic control was mainly assessed by the mean HbAlc. Analysis showed a good acceptance of the proposed system. An overall improvement in mean levels of HbA1c was observed, however further studies will be conducted to prove evidence of the weight and BMI improvements. Moreover, initial indications of positive impact on the improvement in psychological parameters were presumed based on the result of the conducted study. The system appeared to be an efficient and time saving tool in diabetes management

Development of a Telemedical Network Supporting an Automated Flow Cytometric Analysis for the Clinical Follow-up of Leukaemia

In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide

A Review of Evolutionary Trends in Cloud Computing and Applications to the Healthcare Ecosystem

Cloud computing is a technology that allows dynamic and flexible computing capability and storage through on-demand delivery and pay-as-you-go services over the Internet. %is technology has brought significant advances in the Information Technology (IT) domain. In the last few years, the evolution of cloud computing has led to the development of new technologies such as cloud federation, edge computing, and fog computing. However, with the development of Internet of %ings (IoT), several challenges have emerged with these new technologies. %erefore, this paper discusses each of the emerging cloud-based technologies, as well as their architectures, opportunities, and challenges. We present how cloud computing evolved from one paradigm to another through the interplay of benefits such as improvement in computational resources through the combination of the strengths of various Cloud Service Providers (CSPs), decrease in latency, improvement in bandwidth, and so on. Furthermore, the paper highlights the application of different cloud paradigms in the healthcare ecosyste

FEDARGOS-V1: A Monitoring Architecture for Federated Cloud Computing Infrastructures

Resource management in cloud infrastructure is one of the key elements of quality of services provided by the cloud service providers. Resource management has its taxonomy, which includes discovery of resources, selection of resources, allocation of resources, pricing of resources, disaster management, and monitoring of resources. Specifically, monitoring provides the means of knowing the status and availability of the physical resources and services within the cloud infrastructure. This results in making “monitoring of resources” one of the key aspects of the cloud resource management taxonomy. However, managing the resources in a secure and scalable manner is not easy, particularly when considering a federated cloud environment. A federated cloud is used and shared by many multi-cloud tenants and at various cloud software stack levels. As a result, there is a need to reconcile all the tenants’ diverse monitoring requirements. To cover all aspects relating to the monitoring of resources in a federated cloud environment, we present the FEDerated Architecture for Resource manaGement and mOnitoring in cloudS Version 1.0 (FEDARGOS-V1), a cloud resource monitoring architecture for federated cloud infrastructures. The architecture focuses mainly on the ability to access information while monitoring services for early identification of resource constraints within short time intervals in federated cloud platforms. The monitoring architecture was deployed in a real-time OpenStack-based FEDerated GENomic (FEDGEN) cloud testbed. We present experimental results in order to evaluate our design and compare it both qualitatively and quantitatively to a number of existing Cloud monitoring systems that are similar to ours. The architecture provided here can be deployed in private or public federated cloud infrastructures for faster and more scalable resource monitoring