Cost-Aware Routing In Cloud Network Topology
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Solution Overview
Problem
Current network solutions and routing technologies do not account for egress costs when determining the lowest cost path or paths with the best SLA/service guarantees, leading to increased costs for customers using public cloud provider services.
Innovation Solution
The implementation of systems, methods, and devices that autonomously optimize traffic routing decisions based on real-time egress costs, using an egress-cost-based pricing model to reduce total egress charges levied against customers of cloud computing networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional routing protocols are used to determine the shortest path, then routing simplicity is maintained, but egress costs increase due to inadequate cost optimization
Solution Approach 1:
The patent modifies the routing decision parameters by incorporating egress cost metrics into the routing protocol. Instead of solely relying on traditional metrics like hop count or bandwidth, the system changes the parameters to include real-time egress cost data, allowing routers to make cost-optimized path selections while maintaining protocol simplicity through standardized metric integration.
Solution Approach 2:
The system implements feedback mechanisms where egress cost information is continuously collected from cloud service providers and fed back into the routing protocol. This feedback loop enables dynamic adjustment of routing paths based on current cost conditions, allowing the network to adapt to changing pricing models and traffic patterns while automatically optimizing for cost efficiency.
2Loss of energy
If multiple routing paths are evaluated based on comprehensive cost metrics, then cost optimization improves, but routing decision complexity increases
Solution Approach 1:
The patent segments the routing decision process into distinct modular components: cost metric collection, path evaluation, and route selection. Each component handles a specific aspect of the routing decision, allowing complex cost optimization to be broken down into manageable segments that can be processed independently, thereby reducing overall system complexity while maintaining comprehensive cost analysis.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and caching cost metrics for multiple potential routing paths before actual data transmission occurs. This advance preparation allows the routing decision to be made quickly based on pre-analyzed cost data, reducing the computational complexity during real-time routing decisions while still evaluating comprehensive cost factors.
Data Source
AI summary
Cost aware routing in a network topology to reduce costs within an egress-based pricing model. A method includes receiving telemetry data from one or more of a network device or a compute device within a cloud computing network, wherein the telemetry data is associated with a customer of the cloud computing network. The method includes retrieving an egress-based pricing scheme associated with a provider of the cloud computing network and provisioning one or more of the network device or the compute device to optimize routing decisions for the customer to reduce a predicted data egress charge for the customer.