A High-Availability Cloud for Research Computing

Riley, Justin; Noss, John; Dillingham, Wes; Cuff, James; Llorente, Ignacio

doi:10.1109/mc.2017.182

Cited by 6 publications

(5 citation statements)

References 3 publications

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“…APCS assumes that the state of a shared-storage database layer does not change, and therefore focuses on the protection of the application layer of a threetier architecture. In many other approaches, the layer protected by different types of HA solutions is the database layer [53], as in the case of Riley et al's HA cloud for research computing [54]. Built using the OpenNebula cloud computing platform, this solution employs an active-active HA MariaDB cluster (layer 3) to support the storage of cloud objects.…”

Section: Enterprise Application Layersmentioning

confidence: 99%

High-availability clusters: A taxonomy, survey, and future directions

Somasekaram

Călinescu

Buyya

2022

Journal of Systems and Software

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Section: Enterprise Application Layersmentioning

confidence: 99%

High-availability clusters: A taxonomy, survey, and future directions

Somasekaram

Călinescu

Buyya

2022

Journal of Systems and Software

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“…Data replication and load balancing are effective techniques to address the availability and efficiency challenges when sharing information in a cloud-based Content Delivery and Sharing (CDS) systems [13], [14], [15], [12]. However, obtaining a good tradeoff between storage consumption (replication) and user experience (performance) is not trivial [16], [17].…”

Section: Related Workmentioning

confidence: 99%

Improving Performance and Capacity Utilization in Cloud Storage for Content Delivery and Sharing Services

Sosa-Sosa¹,

Barron

Gonzalez-Compeán

et al. 2022

IEEE Trans. Cloud Comput.

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Content delivery and sharing (CDS) is a popular and cost effective cloud-based service for organizations to deliver/share contents to/with end-users, partners and insider users. This type of service improves the data availability and I/O performance by producing and distributing replicas of shared contents. However, such a technique increases overhead on the storage/network resources. This paper introduces a threefold methodology to improve the trade-off between I/O performance and capacity utilization of cloud storage for CDS services. This methodology includes: i) Definition of a classification model for identifying types of users and contents by analyzing their consumption/ demand and sharing patterns, ii) Usage of the classification model for defining content availability and load balancing schemes, and iii) Integration of a dynamic availability scheme into a cloud-based CDS system. Our method was implemented on both a simulator and a real-world CDS service, supporting information sharing operations performed in a cloud storage. An experimental evaluation, conducted in a private cloud through simulation and emulation of workloads, showed the feasibility of this methodology in terms of storage capacity utilization, whereas the real-world implementation revealed the efficiency of applying a classification model to information sharing patterns in terms of I/O performance.

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“…The HA is defined as the ability that keeps system functioning after software or hardware failure. 38 In the case of master server failure, one of the secondary servers takes its place and system continues its execution uninterrupted. The failure between the servers is detected through the exchange of heartbeat messages (as shown in Figure 3).…”

Section: The Proposed System Architecturementioning

confidence: 99%

A multi-agent framework for cloud-based management of collaborative robots

Samad

Iqbal

Malik

et al. 2018

International Journal of Advanced Robotic Systems

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This article presents a cloud-based multi-agent architecture for the intelligent management of aerial robots in a disaster response situation. In a disaster scenario, a team of highly maneuverable quadcopters is deployed to carry out surveillance and decision support in disaster-affected areas. In Pakistan, such events usually result from sudden unpredictable calamities such as earthquakes. The aim of this work is to develop a robust mechanism to autonomously manage and react to sensory inputs received in soft real time from an unstructured environment. The immediate goal is to locate the maximum number of trapped, injured people within a large area, and help first responders plan rescue activities accordingly. To evaluate the proposed framework, a number of simulations are carried out using GAMA platform to emulate a disaster environment. Subsequently, algorithms are developed to survey an affected geographical area through the use of small flight drones. The key challenges in this work are related to the combination of the domains of multi-agent technology, robotics, and cloud computing for effectively bridging the cyber world with the physical world. Therefore, the proposed work demonstrates the effective use of a limited number of drones to capture inputs from a disaster situation in the physical world, and such inputs are used for timely planning of rescue efforts. The results of fixed resource assignment are compared with the proposed reactive assignment strategy, and it clearly shows a significant improvement in terms of resource usage compared to traditional approach.

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A High-Availability Cloud for Research Computing

Cited by 6 publications

References 3 publications

High-availability clusters: A taxonomy, survey, and future directions

High-availability clusters: A taxonomy, survey, and future directions

Improving Performance and Capacity Utilization in Cloud Storage for Content Delivery and Sharing Services

A multi-agent framework for cloud-based management of collaborative robots

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