An Efficient Data Storage Method of NoSQL Database for HEM Mobile Applications in IoT

Chen, Wei-Chen; Chen, Ya-Hung; Wu, Chen; Fu, Li‐Chen

doi:10.1109/ithings.2014.62

Cited by 8 publications

(1 citation statement)

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“…To relieve this problem, memory object caching system, such as Redis [12] [13], is deployed alongside with the database in cloud, for decoupling a portion of work from the traditional database system [14]. For example, Redis acts as a front-end cache layer for the back-end database system, storing a portion of SQL results for satisfying the following IoT queries [15]. When the same or similar IoT query arrives, it can directly return the results to devices, instead of handling on the back-end.…”

Section: Introductionmentioning

confidence: 99%

SEER-MCache: A Prefetchable Memory Object Caching System for IoT Real-Time Data Processing

Dong

Yuan

et al. 2018

IEEE Internet Things J.

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Memory object caching systems, such as Memcached and Redis, have been proved to be a simple and highefficient middleware for improving the performance of IoT (Internet of Things) devices querying the database in cloud. However, its performance guarantee is built on the fact that the target data, queried by the IoT device, will be accessed many times and hit in the caching system. Therefore, when database system is handling the unrepeated IoT queries, it usually presents the sub-optimal performance, which greatly impairs the efficiency of real-time data processing on IoT devices. To improve this issue, we propose Seer-MCache, the memory object caching system with a smart prefetching (read-ahead) function, to fill up the caching system with the desired data before the intensive IoT queries arriving. Seer-MCache includes a set of rules to launch the specific behaviors of read-head. These rules are able to be customized according to the workload characteristics and system load. We implement a prototype system in Redis (caching layer) and MySQL server (database system). Extensive experiments are conducted to verify the effectiveness of Seer-MCache, the results show that Seer-MCache can improve the performance of readintensive workload up to 61% (39.5% in average). Meanwhile, the cost of the read-ahead behavior is moderate and controllable.

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Section: Introductionmentioning

confidence: 99%