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DevOps entails a series of software engineering tactics aimed at shortening the actionable operation of software design changes. One of these tactics is to harness infrastructure-as-code, that is, writing a blueprint that contains deployment specifications ready for orchestration in the cloud. This abstract briefly discusses all necessary elements and abstractions in writing and maintaining that blueprint,...
Hadoop is gaining more and more popularity in virtualized environments because of the flexibility and elasticity offered by cloud-based systems. Hadoop supports topology-awareness through topology-aware designs in all of its major components. However, there exists no service that can automatically detect the underlying network topology in a scalable and efficient manner, and provide this information...
In cloud system, the completion time of the slowest processing task is a significant metric when process the data-intensive application by the Map Reduce/Hadoop architectures. Thus an important problem that virtual machine placement for data node problem (VMPDN) is raised. In this paper, considering the successful application of ACO on combinatorial optimization problems, we firstly adopt Max-Min...
With the rapid pace of technological advancements in smart device, sensor and actuator technologies, the Internet of Things (IoT) domain has received significant attention. These advances have brought us closer to the ubiquitous computing vision. However, in order to fully realize this vision, devices and applications should rapidly adapt to the changes in the environment and other nearby devices...
In the last years, Internet of Things (IoT) and Big Data platforms are clearly converging in terms of technologies, problems and approaches. IoT workloads generate a vast amount of data that needs to be stored and processed, becoming a Big Data problem. IoT devices and sensors generate streams of data across a diversity of locations and protocols that in the end reach a central platform that is used...
Stream processing platforms allow applications to analyse incoming data continuously. Several use cases exist that make use of these capabilities, ranging from monitoring of physical infrastructures to pre selecting video surveillance feeds for human inspection. It is difficult to predict how much computing resources are needed for these stream processing platforms, because the volume and velocity...
Cloud-based big data platforms are being widely adopted in industry, due to their advantages of facilitating the implementation of big data processing and enabling elastic service framework. Alongside with the widespread adoption of cloud-based MapReduce frameworks, a series of solutions have been proposed to improve the performance of big data services over cloud. Majorities of the existing studies...
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