The Storage vs Repair Bandwidth Trade-off for Multiple Failures in Clustered Storage Networks
We study the trade-off between storage overhead and inter-cluster repair bandwidth in clustered storage systems, while recovering from multiple node failures within a cluster. A cluster is a collection of $m$ nodes, and there are $n$ clusters. For data collection, we download the entire content from...
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Zusammenfassung: | We study the trade-off between storage overhead and inter-cluster repair
bandwidth in clustered storage systems, while recovering from multiple node
failures within a cluster. A cluster is a collection of $m$ nodes, and there
are $n$ clusters. For data collection, we download the entire content from any
$k$ clusters. For repair of $t \geq 2$ nodes within a cluster, we take help
from $\ell$ local nodes, as well as $d$ helper clusters. We characterize the
optimal trade-off under functional repair, and also under exact repair for the
minimum storage and minimum inter-cluster bandwidth (MBR) operating points. Our
bounds show the following interesting facts: $1)$ When $t|(m-\ell)$ the
trade-off is the same as that under $t=1$, and thus there is no advantage in
jointly repairing multiple nodes, $2)$ When $t \nmid (m-\ell)$, the optimal
file-size at the MBR point under exact repair can be strictly less than that
under functional repair. $3)$ Unlike the case of $t=1$, increasing the number
of local helper nodes does not necessarily increase the system capacity under
functional repair. |
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DOI: | 10.48550/arxiv.1708.05474 |