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Using adaptive resource allocation to implement an elastic MapReduce framework
Today, we are observing a transition of science paradigms from the computational science to data-intensive science. With the exponential increase of input and intermediate data, more applications are developed using the MapReduce programming model, ...
A traffic hotline discovery method over cloud of things using big taxi GPS data
Traffic hotline discovery is necessary for rational and scientific urban transportation planning in the new living quarters and economic zones. Cloud of Things CoT is a newly emerging concept, involving with two advanced technologies, that is, Cloud ...
PM2.5 forecasting with hybrid LSE model-based approach
PM2.5 time series have the features of non-stationary and nonlinear. Existing forecasting methods for PM2.5 cannot achieve high accuracy for they have ignored the potential characteristics of PM2.5 time series. Aiming at this problem, a hybrid approach ...
Is the data on your wearable device secure? An Android Wear smartwatch case study
The increasing convergence of wearable technologies and cloud services in applications, such as health care, could result in new attack vectors for the 'Cloud of Things', which could in turn be exploited to exfiltrate sensitive user data. In this paper, ...
Brain big data processing with massively parallel computing technology: challenges and opportunities
Brain data processing has been embracing the big data era driven by the rapid advances of neuroscience as well as the experimental techniques for recording neuronal activities. Processing of massive brain data has become a constant in neuroscience ...
CloudEyes: Cloud-based malware detection with reversible sketch for resource-constrained internet of things IoT devices
Because of the rapid increasing of malware attacks on the Internet of Things in recent years, it is critical for resource-constrained devices to guard against potential risks. The traditional host-based security solution becomes puffy and inapplicable ...
Ahab: A cloud-based distributed big data analytics framework for the Internet of Things
Smart city applications generate large amounts of operational data during their execution, such as information from infrastructure monitoring, performance and health events from used toolsets, and application execution logs. These data streams contain ...
XHAMI - extended HDFS and MapReduce interface for Big Data image processing applications in cloud computing environments
Hadoop distributed file system HDFS and MapReduce model have become popular technologies for large-scale data organization and analysis. Existing model of data organization and processing in Hadoop using HDFS and MapReduce are ideally tailored for ...
Resource requests prediction in the cloud computing environment with a deep belief network
Accurate resource requests prediction is essential to achieve optimal job scheduling and load balancing for cloud Computing. Existing prediction approaches fall short in providing satisfactory accuracy because of high variances of cloud metrics. We ...
Adaptable secure communication for the Cloud of Things
Cloud of Things CoT is a novel concept driven by the synergy of the Internet of Things IoT and cloud computing paradigm. The CoT concept has expedited the development of smart services resulting in the proliferation of their real world deployments. ...
