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Emerging Zoned Namespace (ZNS) SSDs, providing the coarse-grained zone abstraction, hold the potential to significantly enhance the cost efficiency of future storage infrastructure and mitigate performance unpredictability. However, existing ZNS SSDs have a static zoned interface, making them in-adaptable to workload runtime behavior, unscalable to underlying hardware capabilities, and interfering with co-located zones. Applications either under-provision the zone resources yielding unsatisfied throughput, create over-provisioned zones and incur costs, or experience unexpected I/O latencies.

We propose eZNS, an elastic-ZNS interface that exposes an adaptive zone with predictable characteristics. eZNS comprises two major components: a zone arbiter that manages zone allocation and active resources on the control plane, and a hierarchical I/O scheduler with read congestion control and write admission control on the data plane. Together, eZNS enables the transparent use of a ZNS SSD and closes the gap between application requirements and zone interface properties. Our evaluations over RocksDB demonstrate that eZNS outperforms a static zoned interface by 17.7% and 80.3% in throughput and tail latency, respectively, at most.

 

Relational network verification is a new approach for validating network changes. In contrast to traditional network verification, which analyzes specifications for a single network snapshot, it analyzes specifications that capture similarities and differences between two network snapshots (e.g., pre- and post-change snapshots). Relational specifications are compact and precise because they focus on the flows and paths that change between snapshots and then simply mandate that all other network behaviors "stay the same", without enumerating them. To achieve similar guarantees, single-snapshot specifications would need to enumerate all flow and path behaviors that are not expected to change in order to enable checking that nothing has accidentally changed. Such specifications are proportional to network size, which makes them impractical to generate for many real-world networks. We demonstrate the value of relational reasoning by developing Rela, a high-level relational specification language and verification tool for network changes. Rela compiles input specifications and network snapshot representations to finite state automata, and it then verifies compliance by checking automaton equivalence. Our experiments using data from a global backbone with over 103 routers find that Rela specifications need fewer than 10 terms for 93% of the complex, high-risk changes. Rela validates 80% of the changes within 20 minutes. 

Published at FPGA'24.