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The exponential growth of digital data sources has the potential to transform all aspects of society and our lives. However, to achieve this impact, the data has to be processed promptly to extract insights that can drive decision making. Further, traditional approaches that rely on moving data to remote data centers for processing are no longer feasible. Instead, new approaches that effectively leverage...
The popularity and proliferation of the Internet of Things (IoT) paradigm is resulting in a growing number of devices connected to the Internet. These devices are generating and consuming unprecedented amounts of data at the edges of the infrastructure, and are enabling new classes of data-drivenapplications, however, current approaches typically rely on cloud platforms located at the core of the...
Service-based access models coupled with recent advances in application deployment technologies can support emerging dynamic and data-driven applications. However, due to evolving application requirements and the dynamicity of the underlying resources, it is necessary to support flexible and opportunistic composition of services in order to satisfy application needs. The goal of this work is to provide...
Emerging lightweight cloud technologies, such as Docker containers, are gaining wide traction in IT due to the fact that they allow users to deploy applications in any environment faster and more efficiently than using virtual machines. However, current Docker-based container deployment solutions are aimed at managing containers in a single-site, which limits their capabilities. As more users look...
Specific architectures for different low level vision modalities have been developed and described using reconfigurable hardware. Each of them tries to solve a single low level vision problem: optical flow, disparity, segmentation, tracking, etc. We introduce a novel architecture that includes multiple processing engines in a massively parallel low level vision processing engine of very high complexity...
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