NEC has been granted a patent for an intent-based computing job assignment framework that optimizes virtual topology design and mapping in mobile edge computing. The method employs Integer Linear Programming and a modified Steiner tree-based heuristic to minimize bandwidth consumption for client job requests. GlobalData’s report on NEC gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on NEC, Battery management systems was a key innovation area identified from patents. NEC's grant share as of June 2024 was 34%. Grant share is based on the ratio of number of grants to total number of patents.
Intent-based computing job assignment in mobile edge infrastructure
The granted patent US12047242B2 outlines a computer-implemented method for intent-based network computing job assignment. The method begins with the receipt of an intent-based computing job request, which prompts the computer to identify all potential candidate virtual nodes for execution. For each candidate, an augmented graph is constructed, which incorporates a topology of the physical infrastructure and a set of stand-alone virtual nodes. The process involves creating a Steiner tree that encompasses all virtual nodes in the augmented graph, mapping these nodes and their corresponding virtual links, and determining bandwidth consumption based on a computing model specified in the job request. Ultimately, the method selects a virtual topology that minimizes bandwidth consumption and outputs the selected topology and its mapping for deployment.
Further claims detail enhancements to the method, including the use of a modified Steiner tree and the ability to reconfigure the intent-based job request. Additionally, the construction of the augmented graph can involve establishing augmented links with physical nodes that are within a specified number of hops from the ingress access point of the network associated with the job request. This structured approach aims to optimize network resource allocation and improve the efficiency of executing intent-based computing tasks within a network infrastructure.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
