Data stream processing is an increasingly important topic due to the prevalence of smart devices and the demand for realtime analytics. One estimate suggests that we should expect nine smart-devices per person by the year 2025 . These devices generate data which might include sensor readings from a smart home, event or system logs on a device, or video feeds from surveillance cameras. As the number of devices increases, the cost of streaming the device data to the cloud over the wide-area network (WAN) will also increase substantially. Transferring and querying this data efficiently has become the focus of much academic research -. Edge computation affords us the opportunity to address this problem by utilizing resources close to the devices. Edge resources have many different use cases, including minimizing end-to-end latency or maximizing throughput , . We restrict our focus to minimizing the required WAN bandwidth, which is an effort to address the increase in data volume.
|Original language||English (US)|
|Title of host publication||Proceedings - 2020 IEEE/ACM Symposium on Edge Computing, SEC 2020|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||3|
|State||Published - Nov 2020|
|Event||5th IEEE/ACM Symposium on Edge Computing, SEC 2020 - Virtual, San Jose, United States|
Duration: Nov 11 2020 → Nov 13 2020
|Name||Proceedings - 2020 IEEE/ACM Symposium on Edge Computing, SEC 2020|
|Conference||5th IEEE/ACM Symposium on Edge Computing, SEC 2020|
|City||Virtual, San Jose|
|Period||11/11/20 → 11/13/20|
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