Virtualization in clouds is promoting the current trend of sharing the storage with multiple tenants. This brings us two fundamental design issues when considering SSDs as a shared storage cache. (i) How can we choose the hierarchy cache model to reduce I/O latency? (ii) How can we design the dynamic cache space allocation strategy to maximize utilization of SSDs space? This paper mainly proposes the corresponding solutions to address the above two issues. (i) We design a cache-awareness model to avoid the useless network latency for querying. (ii) With using the weighted max-min fair share algorithm, measuring the weighted value of each tenant through recording the states of four multi-dimensional factors, can be beneficial to make wise decisions on SSD space allocation. Our experimental results validate that the cache-awareness model outperforms the other two models (cache-unawareness model and without cache) by 1× to 4× in latency. Meanwhile, compared to the static weighted value initializations of the max-min algorithm, our method with dynamically measuring weight value on a tenant basis can achieve much better space utilization.
|Original language||English (US)|
|Number of pages||12|
|Journal||Journal of Computers (Taiwan)|
|State||Published - Apr 1 2016|
- Cache model
- Weighted max-min fair share