Application Scaling Tracking for Dynamic Network Bandwidth Allocation
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Solution Overview
Problem
Existing overlay network deployments face challenges in dynamically allocating bandwidth to meet unpredictable application requirements, relying on human estimations and guesswork, leading to inefficient provisioning and billing in underlay networks.
Innovation Solution
A network controller tracks the compute capacity of a scalable application service platform to dynamically allocate bandwidth by monitoring computing resources and replicas, using APIs to adjust underlay network capacity based on actual application load, enabling precise bandwidth allocation and de-allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network bandwidth is over-provisioned to handle peak traffic demands, then service reliability is improved, but network resource waste increases
Solution Approach 1:
The patent implements dynamic bandwidth allocation that automatically adjusts network resource provisioning based on real-time traffic monitoring and predictive analytics. The system transitions from static over-provisioning to dynamic adaptation, allocating bandwidth according to actual demand patterns while maintaining service reliability through intelligent forecasting and automated scaling.
2Loss of energy
If network bandwidth is under-provisioned to reduce resource waste, then network resource efficiency is improved, but service quality deteriorates during peak traffic
Solution Approach 1:
The system performs preliminary actions by proactively provisioning bandwidth based on predictive analytics before traffic peaks occur. The intelligent forecasting mechanisms anticipate demand surges and pre-allocate resources, ensuring service quality is maintained during peak periods while avoiding the need for continuous over-provisioning.
3Adaptability or versatility
If manual bandwidth allocation is used to optimize network resources, then customization flexibility is improved, but operational complexity increases
Solution Approach 1:
The patent implements self-service mechanisms where the network system automatically monitors traffic patterns, analyzes demand requirements, and adjusts bandwidth allocation without manual intervention. The intelligent system performs what would otherwise require complex manual configuration, reducing operational complexity while maintaining customization flexibility through automated adaptive provisioning.
4Device complexity
If static bandwidth allocation is used to simplify network management, then device complexity is reduced, but adaptability to traffic variations decreases
Solution Approach 1:
The system dynamically changes bandwidth allocation parameters based on monitored traffic conditions and predictive analytics. Rather than using fixed static allocation, the system automatically adjusts bandwidth parameters in response to varying traffic demands, maintaining simplicity of management through automation while achieving high adaptability to traffic variations.
Data Source
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AI summary
Techniques for tracking compute capacity of a scalable application service platform to perform dynamic bandwidth allocation for data flows associated with applications hosted by the service platform are disclosed. Some of the techniques may include allocating a first amount of bandwidth of a physical underlay of a network for data flows associated with an application. The techniques may also include receiving, from a scalable application service hosting the application, an indication of an amount of computing resources of the scalable application service that are allocated to host the application. Based at least in part on the indications, a second amount of bandwidth of the physical underlay to allocate for the data flows may be determined. The techniques may also include allocating the second amount of bandwidth of the physical underlay of the network for the data flows associated with the application.