API Traffic Processing with Dynamic Cache and Bandwidth Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for processing API traffic fail to provide equitable distribution of bandwidth, leading to underutilization of processing capacity and inefficient cache memory usage, resulting in suboptimal user experience and revenue for API providers.
Innovation Solution
A method that determines API traffic intensity in each data channel, assigns priority values based on traffic volume and service level agreements, and allocates cache memory and bandwidth accordingly to ensure high-priority data sets are processed efficiently, using prediction algorithms and caching techniques like simplex and linear programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional caching methods are used based on frequency and TTL, then response time is improved, but cache memory utilization is inefficient
Solution Approach 1:
The patent implements dynamic cache allocation where cache memory is not statically assigned but dynamically adjusted based on real-time API traffic patterns, data set access frequency, and priority levels. The system continuously monitors traffic and reallocates cache resources to high-priority data sets, making the cache memory utilization adaptive and efficient rather than static and wasteful.
Solution Approach 2:
The system changes the parameters of cache allocation from fixed TTL-based expiration to priority-based dynamic retention. High-priority data sets maintain cache residency longer based on their importance and access patterns, while low-priority data sets are evicted sooner, optimizing overall cache utilization without compromising response times for critical data.
2Reliability
If bandwidth is allocated based on SLA with pre-defined numbers, then service level agreement is met, but equitable distribution and processing capacity utilization are suboptimal
Solution Approach 1:
The patent implements dynamic bandwidth allocation that adjusts bandwidth distribution in real-time based on API traffic intensity, data set priorities, and processing capacity availability. Instead of rigid SLA-based pre-defined allocations, the system dynamically scales bandwidth to match actual demand and priority requirements, maximizing processing capacity utilization while maintaining equitable distribution among API developers.
Solution Approach 2:
The system changes bandwidth allocation parameters from fixed SLA quotas to dynamic priority-based rates. Bandwidth is allocated based on real-time assessment of traffic patterns, data set importance, and system capacity, allowing flexible adjustment of allocation rates to optimize both fairness and overall system productivity.
3Ease of operation
If conventional bandwidth allocation is used based on SLA, then pre-defined request limits are enforced, but equitable bandwidth distribution is not achieved
Solution Approach 1:
The patent applies different bandwidth allocation qualities to different data channels and API developers based on their specific traffic patterns, priority levels, and performance requirements. Instead of uniform allocation, each data channel receives bandwidth tailored to its local characteristics and priority, achieving equitable distribution that accounts for individual needs while maintaining overall system fairness.
Data Source
AI summary
A method and system for processing application programming interface (API) traffic includes determining corresponding API traffic at a time interval, assigning a corresponding priority value and allocating a cache memory to store a data set that corresponds to a high priority value. The method also includes receiving a plurality of sets of API requests, comparing corresponding precedence value associated with the sets of API requests, determining a set of API requests and allocating bandwidth to the set of API requests. The method further includes receiving a first set of API requests, determining a total number of processed API requests and predicting a second constant number API requests that is included in a second set of API requests. The system includes an electronic device, a communication interface, a memory and a processor.