Trusted Compute Meter for Granular Billing
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Solution Overview
Problem
Current systems for monetizing compute resources in data centers and IoT ecosystems lack granularity in resource usage measurement, leading to insecure and coarse-grained pricing models that do not accurately reflect the true cost of computing, resulting in inadequate remuneration for resource owners and inefficient billing for clients.
Innovation Solution
A Trusted Compute Meter (TCM) system utilizing bespoke sensors and a trusted execution environment (TEE) to securely measure and record compute and energy usage, ensuring accurate and secure data collection independent of the operating system, allowing for fine-grained billing based on actual resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If coarse-grained pricing models are used for monetizing compute resources, then billing simplicity is improved, but measurement precision deteriorates leading to inaccurate resource usage tracking
Solution Approach 1:
The patent segments resource usage measurement into fine-grained components by implementing separate sensors for compute resources (CPU, memory, storage) and energy resources (power, energy consumption). This segmentation enables precise tracking of individual resource consumption while maintaining billing simplicity through automated aggregation of these measurements into chargeable units.
Solution Approach 2:
The patent replaces manual or coarse-grained billing methods with an automated sensor-based measurement system. Bespoke sensors automatically collect and report resource usage data, eliminating the need for manual tracking and enabling precise, real-time measurement without increasing operational complexity for end users.
2Device complexity
If traditional sensor systems are used for resource measurement, then device complexity is reduced, but reliability deteriorates due to security vulnerabilities and OS dependency
Solution Approach 1:
The patent introduces a trusted execution environment (TEE) as an intermediary layer between the bespoke sensors and the operating system. This TEE acts as a secure mediator that validates sensor readings and protects measurement data from tampering, ensuring reliable and secure resource usage tracking without requiring complex changes to the underlying sensor hardware or OS architecture.
Solution Approach 2:
The patent extracts the measurement and validation logic from the general-purpose operating system into a dedicated trusted execution environment. This separation isolates the critical measurement functions from potential OS vulnerabilities, ensuring that resource usage data remains secure and accurate even when the host OS is compromised or untrusted.
3Measurement precision
If fine-grained resource measurement is implemented, then billing accuracy is improved, but device complexity increases due to additional sensors and measurement infrastructure
Solution Approach 1:
The patent implements universal bespoke sensors that can measure multiple types of resources (compute and energy) through a common interface and protocol. This multi-functionality reduces overall system complexity by using a standardized measurement framework rather than requiring separate specialized sensors for each resource type, while still enabling fine-grained tracking of individual resources.
Data Source
AI summary
In an example, there is disclosed a computing apparatus, having a computing resource; a bespoke sensor for measuring at least one parameter of usage of the computing resource; and one or more logic elements providing a trusted compute meter (TCM) agent to: receive an external workload; provision a workload enclave; execute the external workload within the TCM enclave; and measure resource usage of the external workload via the bespoke sensor. There is also disclosed a computer-readable medium having stored thereon executable instructions for providing a TCM agent, and a method of providing a TCM agent.