# US 11,444,862 B2 · Network-traffic predictor and method > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,444,862 B2 - Document ID: US11444862B2 - Status: Granted - Kind: B2 - Application number: 17/020,286 - Filed: 2020-09-14 - Published: 2020-12-31 - Granted: 2022-09-13 - Earliest claimed: 2018-04-04 - Assignees: Cable Television Laboratories, Inc. - Applicants: Cable Television Laboratories, Inc. - Inventors: Bernardo Huberman; Scott H. Clearwater - Web page: https://patentgrep.com/patent/US11444862B2 ## CPC - H04L 43/0882: Utilisation of link capacity - H04L 41/147: for predicting network behaviour - H04L 41/5025: by proactively reacting to service quality change, e.g. by reconfiguration after service quality degradation or upgrade - Y04S 40/00: Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - Y04S: SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS ## Abstract A method for predicting network-traffic bursts includes identifying, in data received by a networking device, a plurality of network-traffic bursts, each of the plurality of network-traffic bursts occurring at a respective one of plurality of burst-times {tN, tN−1, . . . , t0}. The method includes determining a time-interval τn of a next burst occurring at τn after burst-time t1 by determining respective values of τn, a parameter ξ, and a parameter η, that minimize, to within a tolerance, a quantity (ƒk(ξ,η,k)−(τn−tk)) for at least three values of a integer k. Parameters ξ and η are, respectively, a real and imaginary part of a power-law exponent of a power law relating predicted time-interval τn to any of the plurality of burst-times. The method includes determining, from a cumulative distribution function of a normal distribution of previously-identified network-traffic bursts, a time-duration during which the networking device may reallocate bandwidth. ## Claims ### Claim 1 A method for allocating bandwidth in a communication network, comprising: identifying a plurality of network-traffic bursts in data being transported by the communication network; determining a time interval between network-traffic bursts in which data transmission can be reallocated in the communication network, at least partially based on the plurality of network-traffic bursts in data being transported by the communication network; and reallocating bandwidth in the communication network during the time interval. ### Claim 2 (depends on 1) The method of claim 1, wherein determining the time interval comprises determining the time interval at least partially based on a power law distribution for cumulative data that flows between network-traffic bursts. ### Claim 3 (depends on 1) The method of claim 1, wherein determining the time interval comprises determining the time interval at least partially from a mean-value and a standard deviation of a plurality of normal distributions of measured network-traffic bursts with respect to predicted network-traffic bursts. ### Claim 4 (depends on 1) The method of claim 1, further comprising determining the time interval as a function of a desired Quality of Service (QoS) to be provided by the communication network. ### Claim 5 (depends on 4) The method of claim 4, wherein the desired QoS is related to a cumulative density function evaluated at the time interval. ### Claim 6 (depends on 5) The method of claim 5, wherein the desired QoS is proportional to a difference between the cumulative density function and unity. ### Claim 7 (depends on 5) The method of claim 5, wherein the desired QoS is a decreasing function of the cumulative density function. ### Claim 8 (depends on 1) The method of claim 1, wherein reallocating bandwidth in the communication network during the time interval comprises reallocating bandwidth according to at least one of traffic type, a subnet mask, and an Internet Protocol (IP) address. ### Claim 9 A method for allocating bandwidth in a communication network, comprising: identifying a plurality of network-traffic bursts in data being transported by the communication network; determining a first time interval of a next network-traffic burst; determining a cumulative distribution function of a normal distribution of previously-identified network-traffic bursts at least partially based on the first time interval; determining, from the cumulative distribution function, a second time interval in which data transmission can be reallocated in the communication network; and reallocating bandwidth in the communication network during the second time interval. ### Claim 10 (depends on 9) The method of claim 9, wherein the data being transported by the communication network comprises data received by a networking device. ### Claim 11 (depends on 9) The method of claim 9, wherein determining the first time interval comprises determining best-fit components of a power law distribution function exponent. ### Claim 12 (depends on 11) The method of claim 11, wherein the best-fit components of the power law distribution exponent comprise a real component and an imaginary component. ### Claim 13 (depends on 11) The method of claim 11, wherein the power law distribution function represents cumulative data that flows between network traffic bursts. ### Claim 14 (depends on 9) The method of claim 9, wherein determining the second time interval comprises determining a mean-value and a standard deviation of a plurality of normal distributions of measured network-traffic bursts with respect to predicted network traffic bursts. ### Claim 15 (depends on 14) The method of claim 14, wherein determining the second time interval further comprises determining the second time interval at least partially from the mean-value and the standard deviation. ### Claim 16 (depends on 9) The method of claim 9, wherein reallocating bandwidth in the communication network during the second time interval comprises reallocating bandwidth according to at least one of traffic type, a subnet mask, and an Internet Protocol (IP) address. ### Claim 17 A method for allocating bandwidth in a communication network, comprising: predicting timing of network-traffic bursts in the communication network based at least partially on a power law distribution; and reallocating bandwidth in the communication network during time intervals between predicted network-traffic bursts. ### Claim 18 (depends on 17) The method of claim 17, wherein predicting timing of network-traffic bursts comprises determining best-fit components of an exponent of the power law distribution. ### Claim 19 (depends on 17) The method of claim 17, wherein predicting timing of network-traffic bursts comprises predicting timing of network-traffic bursts as a function of a desired Quality of Service (QoS) to be provided by the communication network. ### Claim 20 (depends on 17) The method of claim 17, wherein reallocating bandwidth in the communication network during time intervals between predicted network-traffic bursts comprises reallocating bandwidth according to at least one of traffic type, a subnet mask, and an Internet Protocol (IP) address.