GECKO: Graph-Evolving aware ChecKpOinter for Intermittent Systems

Abstract

Graph workloads increasingly rely on large, continuously evolving datasets, where SSD data placement and migration strongly influence query and update efficiency. Prior SSD based graph management schemes, including log based designs that follow a read modify write pattern and GraphSSD, target servers and PCs with stable power. When deployed on intermittently powered systems, these power unaware designs often scatter frequently updated hub node edges across many flash pages, which increases over read and triggers excessive flash I/O. The resulting energy overhead is further amplified after each power recovery because the system must reload graph data from NAND into DRAM, repeatedly paying for unnecessary reads and reducing the number of graph queries completed per charge cycle. We propose Graph Evolving aware ChecKpOinter (GECKO), which leverages graph evolution awareness to improve hub edge locality and applies power aware I/O coordination to reduce redundant flash accesses under intermittent power. Across evolving graph updates and queries, GECKO significantly lowers flash I/O, enabling better energy efficiency on energy constrained intermittent systems.