  Erasure codes have been widely considered a promising solution to enhance
data reliability at low storage costs. However, in modern geo-distributed
storage systems, erasure codes may incur high data access latency as they
require data retrieval from multiple remote storage nodes. This hinders the
extensive application of erasure codes to data-intensive applications. This
paper proposes novel caching schemes to achieve low latency in distributed
coded storage systems. Experiments based on Amazon Simple Storage Service
confirm the positive correlation between the latency and the physical distance
of data retrieval. The average data access latency is used the performance
metric to quantify the benefits of caching. Assuming that the future data
popularity and network latency information is available, an offline caching
scheme is proposed to find the optimal caching solution. Guided by the optimal
scheme, an online caching scheme is proposed according to the measured data
popularity and network latency information in real time. Experiment results
demonstrate that the online scheme can approximate the optimal scheme well with
dramatically reduced computation complexity.
