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With the advancements of Internet-of-Things (IoT) and Machine-to-Machine Communications (M2M), the ability to generate massive amount of streaming data from sensory devices in distributed environment is inevitable. A common practice nowadays is to process these data in a high-performance computing infrastructure, such as cloud. Cloud platform has the ability to deploy Hadoop ecosystem on virtual clusters...
People monitoring and tracking activities in surveillance system usually generate massive amount of data from Internet-of-Things (IoT) devices such as cameras. Several issues need to be addressed, including data migration over limited bandwidth and high latency in communication networks. This paper presents an initiative to develop a decentralized face recognition scheme for distributed surveillance...
Obstacle avoidance is one of the important considerations in developing a vision-based robot navigation system. For flying robots, the ability to learn the above-and-below relationship for obstacle avoidance is necessary. This paper presents a conceptual work in developing a learning mechanism to identify the above-and-below relationship for obstacle avoidance in vision-based robot navigation system...
Continuous monitoring activities in surveillance system generate massive amount of data to be transferred from Internet-of-Things (IoT) devices (i.e., cameras and sensors) to a centralized processing unit for analysis. However, several issues need to be addressed, including data migration over bandwidth limited and high latency communication networks, and the heterogeneous nature of data obtained...
The implementation of client polling as a weak cache coherence mechanism has two major drawbacks: Firstly, the cache may return a stale copy if the object is changed in the origin server while the cached copy is considered valid. Secondly, the cache can invalidate a cached copy that is still valid in the server. Therefore, we propose a multilevel pre-fetching (MLP) in conjunction with the client polling...
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