Jul 2026· IEEE International Conference on Cloud Computing· pp. 315-326· 0 citations· 36 references
Abstract
Tiered memory environments that combine DRAM and CXL provide substantial scalability in modern systems, yet they introduce critical fairness challenges for containerized workloads. Existing Linux kernel memory management primarily relies on access-frequency-based page promotion and demotion to optimize system-wide performance. This approach causes two severe problems: (1) flaws in the current Cgroups memory-limit implementation can trigger infinite page reclamation loops in tiered memory systems, and (2) memory-intensive workloads monopolize fast-tier memory (e.g., DRAM), leading to the noisy neighbor problem in which tier occupancy becomes highly unfair even when containers have identical memory limits. This paper resolves the infinite page reclamation loop problem and proposes FATE, a fairness-aware memory allocation for multi-tenant tiered memory environments. FATE extends the Linux Cgroups memory controller to enforce per-tier high-watermark thresholds that are dynamically proportional to the share of total memory allocated to each container. For workloads requiring deterministic performance, FATE also supports configurable static fast-tier reservations. To enable precise enforcement, we introduce a tier-aware page counter that tracks per-NUMA-node, per-tier usage during allocation, migration, and reclamation. By strictly respecting fast-tier thresholds, FATE eliminates infinite reclamation loops and prevents unnecessary OOM killer invocation. Evaluation with diverse workloads in multi-container environments shows that FATE consistently achieves fair tiered memory allocation across containers with negligible runtime overhead. When occupancy ratios were quantified using Jain’s Fairness Index, FATE improved fairness by 7.3% to 31.7% over the baseline. More importantly, FATE significantly enhances performance predictability—a critical requirement for cloud service-level objectives—by providing strict isolation across memory tiers.
Results show up to 2.3x lower remote-access overhead compared to TCP-based designs, a 13% increase in cluster-wide memory utilization at rack scale, and up to 63% reduction in miss rate for memory-constrained tenants under skewed workloads.
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