Workload Placement Using Conflict Cost for Datacenter Security
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Solution Overview
Problem
Existing security measures for shared memory architectures in software-defined datacenters, such as those involving multithreading, UMA, and NUMA, often require disabling these features to prevent vulnerabilities like L1TF, which negates their benefits and leads to processor inefficiencies.
Innovation Solution
Implementing workload placement using conflict costs to accurately predict and minimize inefficiencies while maintaining security, allowing for the concurrent execution of compatible workloads and preventing unauthorized information disclosure across shared memory levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multithreading is disabled to prevent L1TF vulnerabilities, then security is improved, but processor efficiency deteriorates
Solution Approach 1:
The patent applies local quality by differentiating security requirements across different workloads and cache levels. Instead of uniformly disabling multithreading, the system assigns security attributes to individual workloads and applies isolation measures selectively at specific cache levels (L1, L2, L3) where vulnerabilities exist, allowing multithreading to continue for workloads that don't require isolation.
Solution Approach 2:
The system changes parameters by dynamically adjusting workload placement decisions based on security attributes and conflict costs. The scheduler modifies workload assignment parameters in real-time, considering security requirements and efficiency metrics, rather than using a fixed configuration that disables multithreading entirely.
2Reliability
If shared memory architectures are disabled to prevent vulnerabilities, then security is improved, but system resource utilization deteriorates
Solution Approach 1:
The patent applies local quality by implementing security isolation at specific memory hierarchy levels (L1, L2, L3 caches) rather than disabling shared memory entirely. Workloads are assigned security attributes that determine which cache levels require isolation, allowing shared memory to be used efficiently for workloads that don't require isolation while maintaining security where needed.
Solution Approach 2:
The system introduces a scheduling service as an intermediary that manages workload placement across shared memory resources. This intermediary calculates conflict costs and makes intelligent placement decisions, enabling efficient resource utilization while preventing unauthorized information disclosure through proper workload separation.
3Ease of operation
If workload placement does not consider conflict costs, then scheduling simplicity is maintained, but security vulnerabilities arise
Solution Approach 1:
The system applies self-service by enabling workloads to self-identify their security requirements through attributes assigned during workload creation. The scheduling service automatically reads these attributes and makes placement decisions without requiring manual configuration or complex security policies, maintaining operational simplicity while ensuring security.
Solution Approach 2:
The scheduling service implements feedback by continuously monitoring workload placement outcomes and adjusting future decisions based on conflict cost calculations. The system learns from placement results and refines its scheduling decisions to balance security requirements with resource utilization efficiency.
Data Source
AI summary
Disclosed are various embodiments that utilize conflict cost for workload placements in datacenter environments. In some examples, a protected memory level is identified for a computing environment. The computing environment includes a number of processor resources. Incompatible processor workloads are prohibited from concurrently executing on parallel processor resources. Parallel processor resources share memory at the protected memory level. A number of conflict costs are determined for a processor workload. Each conflict cost is determined based on a measure of compatibility between the processor workload and a parallel processor resource that shares a particular memory with the respective processor resource. The processor workload is assigned to execute on a processor resource associated with a minimum conflict cost.