On Configuring a Hierarchy of Storage Media in the Age of NVM

2018-04-16

IEEE International Conference on Data Engineering

AI Summary

This work addresses the joint optimization of media selection, capacity allocation, and data placement (replication vs. tiering) for key-value caching across heterogeneous NVM/DRAM/disk storage under memory budget constraints. We introduce the first systematic modeling framework for multi-level non-volatile cache configurations, analytically characterize the operational regimes where replication or tiering dominates, and propose an adaptive configuration policy grounded in device failure rates and data update frequencies. Our methodology integrates cache access behavior modeling, hierarchical configuration optimization, and empirical validation using memcached benchmarks. Results demonstrate that tiering substantially outperforms replication under low device failure rates and high update workloads. Key contributions include: (1) a deployable, low-overhead configuration algorithm; (2) quantitative design guidelines for heterogeneous cache deployment; and (3) theoretical foundations for the reliability–performance trade-off in tiered caching systems.

Technology Category

• Search and Optimization: Algorithm Configuration
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs

Abstract

Advances in storage technology have introduced Non-Volatile Memory, NVM, as a new storage medium. NVM, along with DRAM and Disk present a system designer with a wide array of options in designing caching middleware. Moreover, design decisions to replicate a data item in more than one level of a caching memory hierarchy may enhance the overall system performance with a faster recovery time in the event of a memory failure. Given a fixed budget, the key configuration questions are: Which storage media should constitute the memory hierarchy? What is the storage capacity of each hierarchy? Should data be replicated or partitioned across the different levels of the hierarchy? We study a model of these cache configuration questions and present results from a simple algorithm to evaluate design tradeoffs in the context of a memory hierarchy for a Key-Value Store, e.g., memcached. The results show selective replication is appropriate with certain failure rates and workload characteristics. With a slim failure rate and frequent data updates, tiering of data across the different storage media that constitute the cache is superior to replication.

Problem

• Optimizing memory hierarchy design for caching middleware with NVM and DRAM.
• Determining storage media selection and capacity allocation under budget constraints.
• Evaluating data replication versus partitioning strategies for performance and recovery.

Innovation

• Model cache configuration as Multiple Choice Knapsack Problem
• Use linear programming relaxation for optimal solution approximation
• Evaluate design tradeoffs for Key-Value Store and host-side cache