Network Cache Placement via Coverage Cost Thresholds
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The optimal deployment of network caches in communication networks is challenging due to the intractability of optimizing cache placement for minimum average delay, and existing methods lack effective approaches to reduce traffic volume and packet transmission delay.
Innovation Solution
A method and apparatus for providing network caches that utilize a cost threshold and coverage cost function to determine the optimal placement of caches, ensuring each client device location is within a predetermined number of hops from at least one cache, thereby optimizing cache deployment and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If caches are deployed to reduce packet transmission delay, then network performance is improved, but the complexity of optimizing cache placement increases
Solution Approach 1:
The patent segments the network into multiple regions or zones, each with its own cache placement strategy. Instead of optimizing cache placement globally across the entire network, the problem is divided into smaller sub-problems for individual network regions, making the optimization more manageable and less complex while still reducing overall packet transmission delay.
Solution Approach 2:
The patent applies local quality by tailoring cache placement strategies to specific network regions based on their unique characteristics such as traffic patterns, node capacities, and demand profiles. Each region receives customized cache placement recommendations rather than a uniform approach, optimizing performance locally while simplifying the overall problem structure.
2Loss of time
If more caches are deployed to improve network performance, then packet delay is reduced, but deployment cost increases
Solution Approach 1:
The patent implements partial action by deploying caches selectively in only those network regions where they provide the most benefit, rather than uniformly across the entire network. The system identifies critical regions with high traffic volumes or long transmission paths and places caches there, achieving significant delay reduction with fewer total caches, thus lowering deployment costs.
Solution Approach 2:
The patent uses parameter changes by adjusting cache placement decisions based on varying network conditions, traffic patterns, and performance requirements. The optimization algorithm dynamically modifies placement parameters such as cache capacity, location, and content distribution to achieve the desired delay reduction at minimal cost, adapting to different operational scenarios.
3Productivity
If caches are placed to minimize average delay, then network throughput is improved, but the problem becomes intractable for general cases
Solution Approach 1:
The patent segments the intractable global optimization problem into smaller, tractable sub-problems by dividing the network into manageable regions. Each region's cache placement can be optimized independently using simpler algorithms, avoiding the computational intractability of the general case while still improving overall network throughput through coordinated regional optimizations.
Solution Approach 2:
The patent applies preliminary action by performing preprocessing steps such as network characterization, traffic pattern analysis, and region identification before the actual cache placement optimization. This preliminary work simplifies the subsequent optimization problem by reducing the search space and identifying key constraints, making the throughput optimization tractable for practical network sizes.
Data Source
AI summary
A method and apparatus for deploying a set of network caches in a communication network is provided. A set of network nodes is identified such that, for each of a set of client device locations, and for at least a number c of the set of nodes, output of a coverage cost function is no greater than a threshold. The coverage cost function receives as input a client location and one of the nodes. The set of network caches are then located at the respective set of nodes. The set of network nodes can be selected from plural candidate sets based on a utility criterion. The candidate sets can be generated by successive addition and/or removal of nodes. Information obtained from a Traffic Engineering function can be used to direct selection of the set of nodes. A cache-client association can be generated for directing clients to particular caches.