# US 12,118,404 B2 · Predictive resource allocation in an edge computing network utilizing beacons > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,118,404 B2 - Document ID: US12118404B2 - Status: Granted - Kind: B2 - Application number: 17/090,421 - Filed: 2020-11-05 - Published: 2021-05-06 - Granted: 2024-10-15 - Earliest claimed: 2019-11-06 - Assignees: CenturyLink Intellectual Property LLC - Applicants: CenturyLink Intellectual Property LLC - Inventors: Steven M. Casey; Felipe Castro; Stephen Opferman; Kevin M. McBride - Web page: https://patentgrep.com/patent/US12118404B2 ## CPC - G06F 9/5072: {Grid computing} - G06F 9/505: {considering the load} - G06F 9/5077: {Logical partitioning of resources; Management or configuration of virtualized resources (specific details on emulation or internal functioning of virtual machines G06F9/455)} - G06F 11/3409: {for performance assessment} - G06N 3/0499: Feedforward networks - G06N 3/0895: Weakly supervised learning, e.g. semi-supervised or self-supervised learning - G06N 3/09: Supervised learning - G06N 3/092: Reinforcement learning - G06N 20/00: Machine learning - H04L 43/0882: Utilisation of link capacity - H04L 43/12: Network monitoring probes - H04L 43/16: Threshold monitoring - H04L 47/83: based on usage prediction - H04L 61/50: Address allocation - H04L 67/10: in which an application is distributed across nodes in the network (software deployment G06F8/60; multiprogramming arrangements G06F9/46) - H04L 67/1008: based on parameters of servers, e.g. available memory or workload (monitoring of computer activity G06F11/30) - H04L 67/1021: based on client or server locations - H04L 67/146: Markers for unambiguous identification of a particular session, e.g. session cookie or URL-encoding - H04L 67/60: Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources (admission control or resource allocation H04L47/70) - H04L 67/63: Routing a service request depending on the request content or context - G06F 2209/5019: Workload prediction - H04L 2101/622: Layer-2 addresses, e.g. medium access control [MAC] addresses - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract The present technology relates to improving computing services in a distributed network of remote computing resources, such as edge nodes in an edge compute network. In an aspect, the technology relates to a system that includes a plurality of edge nodes and a beacon. The system performs operations that may include collecting traffic data from the beacon over a period of time, wherein the traffic data includes at least an amount of devices sending probe requests to the beacon; comparing the amount of devices to a predetermined threshold for traffic data; and based on the comparison of the amount of devices to the predetermined threshold for traffic data, generating a recommendation for installation of a new edge node in addition to the plurality of edge nodes. ## Claims ### Claim 1 A system for allocating hardware resources in a network, the system comprising: a plurality of edge nodes having different physical locations; a beacon having a different physical location than the plurality of edge nodes; at least one processor; and memory, operatively connected to the at least one processor and storing instructions that, when executed by the at least one processor, cause the at least one processor to perform a set of operations comprising: collecting traffic data from the beacon over a period of time, wherein the traffic data includes at least a number of devices sending probe requests to the beacon, wherein the number of devices is a numerical count of unique devices; comparing the number of devices to a predetermined threshold for traffic data; and based on the comparison of the number of devices to the predetermined threshold for traffic data, generating a recommendation for installation of a new edge node in addition to the plurality of edge nodes. ### Claim 2 (depends on 1) The system of claim 1, wherein the operations further comprise: extracting unique device identifiers from a plurality of the probe requests; and based on the extracted unique device identifiers, determining device types that send the plurality of the probe requests. ### Claim 3 (depends on 2) The system of claim 2, wherein the unique device identifiers are media access control (MAC) addresses. ### Claim 4 (depends on 2) The system of claim 2, wherein the operations further comprise generating, based on the determined device types, predicted service types for requests generated by the devices sending the probe requests to the beacon. ### Claim 5 (depends on 4) The system of claim 4, wherein the operations further comprise generating, based on the predicted services types, a recommendation for a hardware allocation for the new edge node. ### Claim 6 (depends on 1) The system of claim 1, wherein the beacon includes at least one of a WiFi radio or a Bluetooth radio. ### Claim 7 (depends on 1) The system of claim 1, wherein the beacon includes at least one of a wired interface or a cellular data interface. ### Claim 8 (depends on 1) The system of claim 1, wherein the beacon is environmentally hardened. ### Claim 9 (depends on 8) The system of claim 8, wherein the beacon comprises at least one rechargeable battery and a solar panel for recharging the at least one rechargeable battery. ### Claim 10 (depends on 1) The system of claim 1, wherein the beacon is configured to receive requests from one or more mobile computing devices and forward the received requests to at least one of the plurality of edge nodes for processing of the received requests. ### Claim 11 (depends on 10) The system of claim 10, wherein the beacon is further configured to extract, from the received requests, a service type requested. ### Claim 12 (depends on 11) The system of claim 11, wherein the beacon is further configured to extract, from the received requests, a user identifier associated with the user requesting the service. ### Claim 13 (depends on 11) The system of claim 11, wherein the operations further comprise generating, based on the services types, a recommendation for a hardware allocation for the new edge node. ### Claim 14 A computer-implemented method for allocating hardware resources in a network, the method comprising: collecting traffic data from a beacon over a period of time, wherein the traffic data includes at least a number of devices sending probe requests to the beacon, wherein the number of devices is a numerical count of unique devices; comparing the number of devices to a predetermined threshold for traffic data; and based on the comparison of the number of devices to the predetermined threshold for traffic data, generating a recommendation for installation of a new edge node in addition to a plurality of existing edge nodes. ### Claim 15 (depends on 14) The computer-implemented method of claim 14, further comprising: extracting unique device identifiers from a plurality of the probe requests; and based on the extracted unique device identifiers, determining device types that send the plurality of the probe requests. ### Claim 16 (depends on 15) The computer-implemented method of claim 15, wherein the unique device identifiers are media access control (MAC) addresses. ### Claim 17 (depends on 15) The computer-implemented method of claim 15, further comprising generating, based on the determined device types, predicted service types for requests generated by the devices sending the probe requests to the beacon. ### Claim 18 (depends on 17) The computer-implemented method of claim 17, further comprising generating, based on the predicted services types, a recommendation for a hardware allocation for the new edge node. ### Claim 19 (depends on 14) The computer-implemented method of claim 14, further comprising receiving requests from one or more mobile computing devices and forward the received requests to at least one of the plurality of existing edge nodes for processing of the received requests.