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Abstract

Cloud computing is rapidly emerging as a new model for service delivery, including for telecommunications services (cloud telephony). Although many solutions are now available, cloud management and monitoring technology has not kept pace, partially because of the lack of open source solutions. To address this limita- tion, this article describes our experience with a private cloud, and discusses the design and implementation of a private cloud monitoring system (PCMONS) and its application via a case study for the proposed architecture. An impor- tant finding of this article is that is possible to deploy a private cloud within the organization using only open source solutions and integrating with traditional tools like Nagios. However, there is significant development work to be done while integrating these tools. With PCMONS we took the first steps toward this goal, opening paths for new development opportunities as well as making PCMONS itself an open-source tool.
Toward'an'Architecture'for'
Monitoring'Private'Clouds'
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Shirlei'Aparecida'de'Chaves,'Rafael'Brundo'Uriarte,'
Carlos'Becker'Westphall'
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Networks'and'Management'Laboratory'
Federal'University'of'Santa'Catarina'
DECEMBER'2011' IEEE'COMMUNICATIONS'MAGAZINE' "!
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... The private cloud monitoring system (PCMONS) [14] was developed as a modular monitoring system for private clouds. Basically, it gathers and prepares information relevant for data visualization and can be integrated with other cloud management toolkits such as Nagios [9]. The optimized infrastructure services (OPTIMIS) scheme, introduced in [8] for private clouds, allows interaction with a rich ecosystem of public clouds and many cloud providers. ...
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Delivering electronic health care (eHealth) services across multi-cloud providers to implement patient-centric care demands a trustworthy brokering architecture. Specifically, such an architecture should aggregate relevant medical information to allow informed decision-making. It should also ensure that this information is complete and authentic and that no one has tampered with it. Brokers deployed in eHealth services may fall short of meeting such criteria due to two key behaviors. The first involves violating international health-data protection laws by allowing user anonymity and limiting user access rights. Second, brokers claiming to provide trustworthy transactions between interested parties usually rely on user feedback, an approach vulnerable to manipulation by malicious users. This paper addresses these data security and trust challenges by proposing HealthyBroker, a novel, trust-building brokering architecture for multiple cloud environments. This architecture is designed specifically for patient-centric cloud eHealth services. It enables care-team members to complete eHealth transactions securely and access relevant patient data on a “need-to-know” basis in compliance with data-protection laws. HealthyBroker also protects against potential malicious behavior by assessing the trust relationship and tracking it using a neutral, tamper-proof, distributed blockchain ledger. Trust is assessed based on two strategies. First, all transactions and user feedback are tracked and audited in a distributed ledger for transparency. Second, only feedback coming from trustworthy parties is taken into consideration. HealthyBroker was tested in a simulated eHealth multi-cloud environment. The test produced better results than a benchmark algorithm in terms of data accuracy, service time, and the reliability of feedback received as measured by three malicious behavior models (naïve, feedback isolated, and feedback collective). These results demonstrate that HealthyBroker can provide care teams with a trustworthy, transparent ecosystem that can facilitate information sharing and well-informed decisions for patient-centric care.
... Private Cloud MONitoring System (PCMONS) ( Chaves et al., 2011 ) is a monitoring system aimed at meeting the need of opensource monitoring technologies for private clouds. The monitoring approach is compatible with the Eucalyptus IaaS platform. ...
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Recently, a promising trend has evolved from previous centralized computation to decentralized edge computing in the proximity of end-users to provide cloud applications. To ensure the Quality of Service (QoS) of such applications and Quality of Experience (QoE) for the end-users, it is necessary to employ a comprehensive monitoring approach. Requirement analysis is a key software engineering task in the whole lifecycle of applications; however, the requirements for monitoring systems within edge computing scenarios are not yet fully established. The goal of the present survey study is therefore threefold: to identify the main challenges in the field of monitoring edge computing applications that are as yet not fully solved; to present a new taxonomy of monitoring requirements for adaptive applications orchestrated upon edge computing frameworks; and to discuss and compare the use of widely-used cloud monitoring technologies to assure the performance of these applications. Our analysis shows that none of existing widely-used cloud monitoring tools yet provides an integrated monitoring solution within edge computing frameworks. Moreover, some monitoring requirements have not been thoroughly met by any of them.
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Grid computing is a technology for distributed computing. To manage a large scale of Grid resources for dynamic access, resource management is a key component. In this paper, a Grid Resource Information Monitoring (GRIM) prototype is introduced. To support the constantly changing resource states in the GRIM prototype, the push-based data delivery protocol named Grid Resource Information Retrieving (GRIR) is provided.There is a trade-off between information fidelity and updating transmission cost. The more frequent the reporting is, the more precise the information will be. But there will be more overheads. The offset-sensitive mechanism, the time-sensitive mechanism, and the hybrid mechanism in GRIR are used to achieve a high degree of data accuracy while decreasing the cost of updating messages. Experimental results show that the proposal alleviates both the update transmission cost and the loss of data accuracy compared to prior methods.
Rapid and Automated Deployment of Monitoring Services in Grid Environments
  • M Yiduo
M. Yiduo et al., "Rapid and Automated Deployment of Monitoring Services in Grid Environments," APSCC, 2007.-­-[9] L. Wang et al., "Scien=fic Cloud Compu=ng: Early Defini=on and Experience," IEEE Int'l. Conf. High Perf. Compu=ng and Commun., 2008. DECEMBER 2011