Abstract
Wide-area stream analytics is commonly being used to extract operational or business insights from the data issued from multiple distant datacenters. However, timely processing of such data streams is challenging because wide-area network (WAN) bandwidth is scarce and varies widely across both different geo-locations (i.e., spatially) and points of time (i.e., temporally). Stream analytics desirable under a WAN setup requires the consideration of path diversity and the associated bandwidth from data source to sink when performing operator task placement for the query execution plan. It also has to enable fast adaptation to dynamic resource conditions, e.g., changes in network bandwidth, to keep the query execution stable.
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