Title
GroupAware Stream Filtering: Towards Collaborative Data Reduction in Stream Processing Systems,Used
Delivery time: 8-12 business days (International)
In this dissertation, we (the author and her research collaborators) consider a distributed system that disseminates highvolume event streams to many simultaneous monitoring applications over a lowbandwidth network. For bandwidth efficiency, we propose a groupaware stream filtering'' approach, used together with multicasting, that exploits two overlooked, yet important, properties of monitoring applications: 1) many of them can tolerate some degree of slack'' in their data quality requirements, and 2) there may exist multiple subsets of the source data satisfying the quality needs of an application. We can thus choose the best alternative'' subset for each application to maximize the data overlap within the group to best benefit from multicasting. Here we provide a general framework for the groupaware stream filtering problem, which we prove is NPhard. We introduce a suite of heuristicsbased algorithms that ensure data quality (specifically, granularity and timeliness) while preserving bandwidth. Our evaluation shows that groupaware stream filtering is effective in trading CPU time for bandwidth savings, compared with selfinterested filtering.
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Shipping & Returns
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We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
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We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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