Scheduling-Aware Data Prefetching for Data Processing Services in Cloud
Journal
31st IEEE International Conference on Advanced Information Networking and Applications (AINA-2017)
Date Issued
2017
Author(s)
Abstract
Cloud computing services provide flexible computing and storage resources to process large amount of datasets. In-memory techniques keep the frequently used data into faster and more expensive storage media for improving performance of data processing services. Data prefetching aims to move data to low-latency storage media to meet requirements of performance. However, existing mechanisms do not consider how to benefit the data processing applications which do not frequently access the same datasets. Another problem is how to reclaim memory resources without affecting other running applications. In this paper, we provide a Scheduling-Aware Data Prefetching (SADP) mechanism for data processing services in a cloud data center. The SADP includes data prefetching and data eviction mechanisms. It firstly evicts the data from memory to release resources for hosting other data blocks, and then it caches the data that will be used in near future. Finally, real-testbed experiments are performed to show the effectiveness of the proposed SADP.
SDGs
Type
conference paper