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48 results about "Swarm behavior" patented technology
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Swarm behavior. Swarm behaviour, or swarming, is a collective behaviour exhibited by animals of similar size which aggregate together, perhaps milling about the same spot or perhaps moving en masse or migrating in some direction.
Mobile phone big data-based floating population classification identification analysis method
The invention provides a mobile phone big data-based floating population classification identification analysis method. According to the method, the limitation of conventional survey is broken through; objective time-space information is extracted from a behavior track by utilizing big data to perform analysis mining; the limitation of low sampling rate is broken through and multi-time full information extraction of different dimensions can be performed; population mobility is observed and identified in space and time to distinguish floating population groups; and floating population is classified into long-term floating population, short-term floating population and short-time immigration population by considering different categories of the floating population from the perspective of users based on behavior characteristics and staying durations of the groups, so that the application of data can generate values in different fields.
Owner:上海世脉信息科技有限公司
Crowd behavior model analysis and abnormal behavior detection method under geographical environment
The invention discloses a crowd behavior model analysis and abnormal behavior detection method under a geographical environment. The method comprises the following steps that: video monitoring signals can be captured, and crowd movement regions in a monitoring scene are set, and video monitoring crowd images are obtained, and geographic spatial mapping processing is performed on the crowd movement regions; measurable crowd movement fields are calculated through using an optical flow method under geographic reference, and the crowd movement fields are converted and mapped to polar coordinate reference; according to the distribution situation of the crowd movement fields under the polar coordinate reference, statistical analysis is performed on the crowd movement fields at each main direction of the polar coordinate reference, and then, crowd movement models and crowd movement trends under the geographical environment can be judged, and crowd movement rate at each main direction can be estimated; and based on the analysis results of the crowd movement models, movement trends and movement rate, detection on crowd abnormal behaviors such as movement rate mutation, movement trend mutation, reverse walking, sudden aggregation and sudden scatter is performed. The crowd behavior model analysis and abnormal behavior detection method of the invention can be widely used in areas where crowds are prone to aggregation.
Owner:NANJING NORMAL UNIVERSITY
Crowd evacuation path planning method based on artificial fish swarm algorithm
InactiveCN103679264ARealize the constructionImplement evacuation behaviorBiological modelsSpecial data processing applicationsAlgorithmCrowds
The invention discloses a crowd evacuation path planning method based on an artificial fish swarm algorithm. The crowd evacuation path planning method includes the steps: building an artificial fish swarm model and initializing relevant parameters; calculating the distance between each grid and a danger source and the crowdedness degree of each grid, and updating artificial fish positions if open exit evacuation is performed; calculating the distance between each grid and an exit and the crowdedness degree of each exit zone, and updating the artificial fish positions if fixed exit evacuation is performed; generating the optimal path of crowd evacuation simulated by individual artificial fishes. The crowd evacuation path planning method has the advantages that swarm adaptive path planning can be realized, a parameter setting panel is designed by the aid of a visual interface, evacuation behaviors under different situations are simulated, generated movement more conforms to swarm movement in a real world, so that unpredictable swarm behaviors are generated, and movement authenticity is improved.
Owner:SHANDONG NORMAL UNIV
Adaptive abnormal crowd behavior analysis method
ActiveCN103745230AAccurate detectionCharacter and pattern recognitionPattern recognitionAnomalous behavior
The invention discloses an adaptive abnormal crowd behavior analysis method, which is used for analyzing crowd behaviors in a video image. The method comprises the following steps of performing streak line calculation on the video image; calculating a streak line flow; detecting abnormal behaviors; performing foreground detection on the video image of abnormal crowd behaviors; performing adaptive crowd density estimation comprising pixel-counting-based density estimation and texture-analysis-based density estimation, and finally dividing estimated density into four density levels, i.e. a low density level, a medium density level, a high density level and an ultrahigh density level, thereby finishing grading the abnormal crowd behaviors. According to the method, the concepts of streak line and streak line flow are introduced to analyze whether a crowd in the video image is abnormal or not; the method has the advantage of detection accuracy; the densities of crowds involved in the abnormal crowd behaviors in different density scenarios are estimated in an adaptive way, and the detected abnormal crowd behaviors are graded by using density estimation results as main characteristics; the method is used for accurately grading the abnormal behaviors (such as mass brawl) in crowded public places, and giving alarms.
Owner:SICHUAN UNIV
Robot path planning method
ActiveCN105527964AImprove global search performanceReduce problemsPosition/course control in two dimensionsVehiclesImmunological memoryGenetic algorithm
The invention discloses a robot path planning method. A direction operator is introduced on the basis of an artificial fish swarm algorithm to improve the accuracy and the success rate of fish swarm behaviors such as clustering, tailgating and even foraging, and an immunological memory operation is added to improve the global searching capability of the algorithm and reduce the probability of local extreme values. Simulation experiments in two typical grid map environments show that compared with a fast genetic algorithm and an artificial fish swarm algorithm, the immunological-directional artificial fish swarm algorithm has the advantages of better result stability, shorter calculation time and feasible solution closer to the optimal path.
Owner:GUILIN UNIV OF ELECTRONIC TECH
Abnormal behavior detection method based on large-scale WiFi activity track
ActiveCN106792523ALock accuratelyGuaranteed stabilityCharacter and pattern recognitionAlarmsAnomaly detectionSwarm behavior
The invention provides an abnormal behavior detection method based on a large-scale WiFi activity track. The method comprises the following steps: on the basis of a collected MAC record, finding MACs with normal individual behaviors by using a frequent track mining algorithm, extracting the activity feature attributes of these MACs with normal individual behaviors to serve as the input of an SVDD algorithm, establishing a plurality of abnormal behavior detection models to filter a large number of MACs satisfying group behavior rules, thereby not only greatly shortening the time necessary for processing large-scale data, but also ensuring the stability of the abnormal behavior detection method, the feature of serious unbalance of positive and negative samples in the application environment can be well overcome, and accordingly time consistency and space consistency detection is carried out on a single MAC different from the group behavior rules to lock the MAC with abnormal activity more accurately. By adoption of the abnormal behavior detection method provided by the invention, the moving track of a moving object in the public security field can be monitored in real time, abnormal behaviors can be identified accurately in real time, auxiliary judgment is provided for the happening security events, and early warning is provided for the possible security events.
Owner:武汉白虹软件科技有限公司
Bionic swarm intelligence-based real-time positioning navigation and motion control method and system for moving vehicle
InactiveCN103632558AImproved real-time positioning and navigationStrong process controllabilityRoad vehicles traffic controlPosition fixationMobile vehicleRoad traffic control
The invention discloses a bionic swarm intelligence-based real-time positioning navigation and motion control method for a moving vehicle and is used for solving the technical problem of lower reliability of the existing real-time positioning navigation and motion control method for the moving vehicle. The technical scheme is that the method comprises the steps of firstly selecting the vehicle and information nodes of known coordinates in a complex road as the positioning reference nodes, converting the equation set positioning and solving problem into the extreme value optimizing problem, and adopting a bionic swarm algorithm to solve the positioning coordinates. For the control on driving among multiple vehicles, a bionic swarm motion model is established to control the motion among the vehicles by establishing the bionic swarm behaviors, and the controllability on the real-time positioning and navigation and the motion control for the moving vehicle is improved. The real-time positioning navigation and motion control system for the moving vehicle is formed by a vehicle-mounted terminal module, a road information node module and a road traffic control center module. The three modules cooperatively work to realize the real-time positioning navigation and motion control on the moving vehicle.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Swarming behavior in wagering game machines
InactiveUS20100173689A1Apparatus for meter-controlled dispensingKnowledge representationGame basedSwarm behavior
Apparatus, systems, and methods may operate to present a wagering game upon which monetary value may be wagered; to present an initial image including a subset of a swarm in space representing a portion of the wagering game; and to determine the actual outcome of the wagering game based on player input indications, swarm behavior modeling, and a selected statistical game outcome. An updated image may then be generated and presented, derived from the initial image and the actual outcome.
Owner:BALLY GAMING INC
Complex chemical process modeling method of DNA genetic algorithm based on swarm behavior
ActiveCN103279652AImprove fitting accuracyFast convergenceSpecial data processing applicationsDna geneticsChemical process modeling
Owner:ZHEJIANG UNIV
Information Handling System Application Decentralized Workload Management
ActiveUS20160072877A1Improve reliabilityImprove responseResource allocationDigital computer detailsHandling systemSwarm behavior
A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.
Owner:DELL SOFTWARE +2
Method for identifying key proteins with AFSO (artificial fish school optimization) algorithm
ActiveCN107784196AFully consider the topological characteristicsAccurate identificationArtificial lifeProteomicsUndirected graphProtein protein interaction network
The invention discloses a method for identifying key proteins with an AFSO (artificial fish school optimization) algorithm. The method comprises steps as follows: a protein-protein interaction networkis converted into an undirected graph, a purified protein-protein interaction network is constructed, RNA gene expression values corresponding to proteins, GO comment information and degrees of proteins in known compounds are obtained, edges and nodes of the purified protein-protein interaction network are treated, known key proteins are selected as initial artificial fishes, the artificial fishes execute foraging behavior, random behavior, following behavior and swarm behavior, and the key proteins are produced. According to the method, the key proteins can be identified accurately; a simulation experiment result indicates that performance of indexes such as sensitiveness, specificity, a positive predictive value, a negative predictive value and the like is better; compared with other methods for identifying the key proteins, the method has the advantages that optimizing characteristics of artificial fish schools are combined with topological characteristics of the protein-protein interaction network to realize the key protein identification process, and the accuracy rate of the key protein identification is increased.
Owner:SHAANXI NORMAL UNIV
Information Handling System Application Decentralized Workload Management
ActiveUS20120254437A1Rapid and reliable application responseImprove IQDigital computer detailsProgram controlProgram managementHandling system
A cloud application management infrastructure models biological swarm behaviors to assign application resources to physical processing resources in a decentralized manner. A balanced and highly automated management of cloud infrastructure has a predictable and reliable response to changing resource loads by using a limited local rule set to define how application instances interact with available resources. Digital pheromone signals at physical resources are applied locally by a swarm module to determine if the physical resources provide an acceptable environment for an application and, if not, the application swarms to other environments until a suitable environment is found.
Owner:DELL PROD LP
Neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication
ActiveCN109270905AReduce transmissionPromote evolutionTotal factory controlProgramme total factory controlNerve networkWorking environment
The invention relates to a neural network-based method for swarm robots to realize cooperative foraging through using pheromone-based communication. The method includes the following steps that: a neural network model is established; a pheromone volatilization model is designed; and a system overall behavior framework model is established. According to the method of the invention, the pheromone volatilization model of swarm robot cooperative foraging behaviors is put forward and is defined as Ii(t), that is, the external input of an i-th neuron at a time t, and in the formula, an attracting pheromone Pa has a large positive value, a repulsion pheromone Po and a repulsion pheromone Pe have small negative values; when a foraging robot finds food and transports the food back to a nest, the foraging robot releases the attracting pheromone Pa; when the robot avoids an obstacle, the robot releases the repulsion pheromone Po; when the robot searches for food randomly in a working environment,the robot releases the repulsion pheromone Pe; the neural network updates output at any time according to the change of the Ii(t); and the evolution of the neural network enables the swarm robots tocommunicate locally, and witness self-organized group behaviors during an interaction process.
Owner:SHANDONG UNIV
Circulating water culturing water quality intelligent early warning device and method based on fish swarm behavior space-time characteristics
ActiveCN111640139ASimple structureOptimal control methodImage enhancementImage analysisVisual technologyImage manipulation
The invention discloses a circulating water culturing water quality intelligent early warning device and method based on fish shoal behavior spatio-temporal characteristics. The device comprises a circulating water culture pond, a circulating water treatment system, a depth camera, an alarm, mobile equipment, a display and a server. The device mainly utilizes a computer vision technology and an image processing technology to construct a motion influence diagram capable of reflecting water quality change characteristics, and performs water quality abnormity early warning in time under the condition of not influencing normal growth and development of fishes through quantitative analysis of spatiotemporal characteristics of fish shoal behaviors. The device is simple in structure, the method is accurate, simple and convenient, the intelligent water quality early warning device and method can effectively solve the problems that existing common water quality detection equipment is not high in accuracy and low in reliability, it is guaranteed that the water quality of the aquaculture water body is within the adaptive range in a non-invasive mode, and fish aquaculture welfare is facilitated.
Owner:ZHEJIANG UNIV
Method for providing a safe operation of subsystems within a safety critical system
ActiveUS20200166933A1Effective functionProtection against multiple abusesKey distribution for secure communicationAutonomous decision making processDriver/operatorCritical system
Provided is a method for providing a safe operation of subsystems within a safety critical system (SCS), wherein a malfunctioning subsystem of the SCS sends a malfunction signal to the other subsystems of the SCS including a one-time cryptographic key unique to the malfunctioning subsystem, which is then decrypted by the other subsystems and collective safety management is initiated when the cryptographic key is valid. Also provided are traffic control systems, autonomous driving systems or automotive driver assistance systems. A swarm-like behavior of the subsystems collectively reacting to emergency situations is combined with a one-time cryptographic authentication and / or authorization procedure preventing repeated manipulation of the system by the same perpetrator.
Owner:SIEMENS MOBILITY GMBH
Systems and methods for industrial robotics
ActiveUS20210114219A1Improve abilitiesEasy to buildProgramme controlProgramme-controlled manipulatorControl engineeringDistributed control system
Systems and methods for industrial robotic platforms. Squads of industrial robots autonomously communicate and work together. A control center may monitor the autonomous operations. Software at the control center, squad, and robot levels forms a distributed control system that analyzes various data related to the platform for monitoring of the various systems. Artificial intelligence, such as machine learning, is implemented at the control center, squad, and / or robot levels for swarm behavior driven by intelligent decision making. Each robot includes a universal platform attached to a task-specific tooling system. The robots may be mining robots, with a mining-specific tooling system attached to the universal framework, and configured for mining tasks. The platform is modular and may be used for other industrial applications and / or robot types, such as construction, satellite swarms, fuel production, disaster recovery, communications, remote power, and others.
Owner:OFF WORLD INC
Information handling system application decentralized workload management
ActiveUS9195510B2Improve reliabilityImprove responseResource allocationMultiple digital computer combinationsSwarm behaviorApplication software
Owner:DELL PROD LP
Method for judging swarming behavior of bees by utilizing temperature change
InactiveCN107114323AReduce lossesAvoid economic loss of productionAnimal husbandryHoneycombSwarm behavior
The invention discloses a method for judging swarming behavior of bees by utilizing temperature change. The method comprises the following steps: as the activity of bees in a honeycomb before swarming causes the rise of temperature of a swarm, a sensitive temperature point, namely a swarming early-warning temperature threshold, is set by utilizing the temperature rise characteristic in the design, wherein the temperature change in the honeycomb corresponding to the temperature change is most sensitive; in a plurality of honeycombs of a beehive structure, two wireless temperature sensor monitoring nodes are set corresponding to each honeycomb, so as to realize the accurate temperature detection; swarming early-warning temperature threshold is acquired by adopting honeycomb temperature change algorithm through utilizing a K-means method for clustering analysis, the temperature threshold acquired by a wireless sensing network is compared with the swarming early-warning temperature threshold, if the temperature value is greater than the swarming early-warning temperature threshold, that swarming behavior occurs in the honeycomb can be judged.
Owner:HANGZHOU DIANZI UNIV
Bee swarming early-warning method
The invention relates to a bee swarming early-warning method. The bee swarming early-warning method comprises the steps that a temperature probe of a temperature sensor is arranged at the front portion of a honeycomb in a beehive; a swarming early-warning temperature threshold is set, the temperature value acquired by the temperature probe is compared with the swarming early-warning temperature threshold, it is judged that a swarming behavior occurs in the honeycomb and alarm information is sent to a bee keeper if the temperature value acquired by the temperature probe is greater than the swarming early-warning temperature threshold. According to the bee swarming early-warning method, the temperature probe is arranged in the area in which temperature change is the earliest and most sensitive in a front swarming honeycomb, namely the front portion of the honeycomb, occurrence of swarming can be early warned 15 minutes earlier, and bee-keeping production loss caused by swarming is effectively avoided.
Owner:FUJIAN AGRI & FORESTRY UNIV
Amorphous ad-hoc groups based on swarming behavior
ActiveUS20190158301A1Special service provision for substationServices signallingSwarm behaviorOperations research
A computer-implemented process for groups includes forming a group using a series of invitation, acceptance and confirmation handshake messages. A location center for the group is calculated as an average location for all members of the group as calculated by the computer from data included in at least one message of the messages. The computer calculates a perimeter for the group from the data. The computer calculates a time decay parameter for the group from the data. The computer calculates a group profile for the group based on at least the location center, the perimeter and the time decay parameter. The computer adds a new member to the group, by any member triggering an invitation process with the new member. The computer recalculates the group profile on acceptance by the new member and transmits the recalculated group profile to all members including a confirmation message to the new member.
Owner:KYNDRYL INC
Special group gathering behavior early detection and gathering place prediction method and system
InactiveCN108416293AQuick judgmentAutomatic removalCharacter and pattern recognitionVideo monitoringPrediction algorithms
The invention belongs to the field of group behavior management and control, and discloses a special group gathering behavior early detection and gathering place prediction method and system. The effective active members of the group are defined by using a gathering behavior detection algorithm based on the average sliding distance between the effective active members, and the interference of thenoise member on gathering behavior detection can be eliminated; as for the special group having the gathering behavior, the gathering tendency of the group is detected in the early stage of the groupactivity and early warning is given; and the potential gathering members are selected through screening by using a gathering place prediction algorithm based on the potential gathering member moving trace least square fitting straight line so as to perform gathering place prediction. Rapid judgment of the special group gathering behavior can be realized by only using the historical moving trace data of the group members without depending on the video monitoring system, early warning is given to the group having the gathering behavior in time and the gathering place can be accurately predicted.
Owner:UNIVERSITY OF CHINESE ACADEMY OF SCIENCES
Ocean wave height prediction method and system, computer equipment, storage medium, and terminal
PendingCN113722980AImprove accuracyLow costDesign optimisation/simulationNeural architecturesSea wavesEngineering
The invention belongs to the technical field of ocean wave height prediction, and discloses an ocean wave height prediction method and system, computer equipment, a storage medium, and a terminal. The method comprises the following steps: selecting a feature with a high correlation coefficient as an input feature for predicting an ocean wave height; establishing a chaos model according to particle swarm behavior characteristics to solve the problem of premature convergence of particle swarms, wherein the CDW performs optimization in an initialization stage for a BP model, and in a CPSO-BP model, a chaotic particle swarm optimization (CPSO) algorithm searches optimal particles in a solution space to optimize initial weights and threshold values of a BP network; using parameters optimized by the CPSO algorithm as initial weights and threshold values of an ELM network to be transmitted to an ELM network; carrying out wave height prediction in the ocean early warning field by using a CPSO-BP model or a CPSO-ELM model. The deep learning method is used for wave height prediction, and the method has the advantages of high accuracy, low cost and high operation speed.
Owner:OCEAN UNIV OF CHINA
Unmanned aerial vehicle swarm countering method based on swarm behavior characteristics
ActiveCN113507339AImplement extractionAchieve internal breakthroughCommunication jammingRadarSimulation
The invention discloses an unmanned aerial vehicle swarm countering method based on swarm behavior characteristics. According to the method, radar and infrared information and visible light images of an unmanned aerial vehicle swarm are collected through detection and recognition equipment arranged on a mobile carrier; the spatial position of the unmanned aerial vehicle is predicted by using a multi-source information fusion method, and swarm orientation and member position detection is realized; the formation and the motion trail of the unmanned aerial vehicle swarm are analyzed by using the swarm behavior characteristics, and recognizing a swarm countering key node; generating a navigation deception signal for the key unmanned aerial vehicle, transmitting an error signal to the whole swarm through the distributed interactive network, forcing the unmanned aerial vehicle swarm to deviate from an original flight path, and achieving the countering of the unmanned aerial vehicle swarm. According to the invention, through application of behavior characteristics of the unmanned aerial vehicle swarm, a problem of insufficient capability of countering the unmanned aerial vehicle swarm is solved, threats of omnidirectional defense penetration of the unmanned aerial vehicle swarm to important economic facilities are solved, and countering of the unmanned aerial vehicle swarm is effectively realized.
Owner:中国人民解放军火箭军工程大学
Amorphous ad-hoc groups based on swarming behavior
ActiveUS10348512B2Special service provision for substationServices signallingSwarm behaviorOperations research
A computer-implemented process for groups includes forming a group using a series of invitation, acceptance and confirmation handshake messages. A location center for the group is calculated as an average location for all members of the group as calculated by the computer from data included in at least one message of the messages. The computer calculates a perimeter for the group from the data. The computer calculates a time decay parameter for the group from the data. The computer calculates a group profile for the group based on at least the location center, the perimeter and the time decay parameter. The computer adds a new member to the group, by any member triggering an invitation process with the new member. The computer recalculates the group profile on acceptance by the new member and transmits the recalculated group profile to all members including a confirmation message to the new member.
Owner:KYNDRYL INC
A classification, identification and analysis method for floating population based on mobile phone big data
The invention provides a method for classifying, identifying and analyzing floating population based on mobile phone big data. The present invention breaks through the limitations of traditional surveys, uses big data to extract objective spatio-temporal information from behavioral trajectories for analysis and mining, breaks through the limitations of low sampling rates and can perform multiple and sufficient information extractions of different calibers, from the dimension of space and time, population flow Conduct observation and identification, distinguish floating population groups, and consider the different classifications of floating population based on the behavioral characteristics and length of stay of the group, and from the perspective of data users, and divide them into long-term floating population, short-term floating population and short-term immigration population, So that the application of this data can play a role in different fields.
Owner:上海世脉信息科技有限公司
Method and equipment for determining group behavior occurrence place
ActiveCN111278041AMeet high-speed and even real-time requirementsReduce the amount of calculationParticular environment based servicesLocation information based serviceEdge basedSwarm behavior
The invention discloses a method and equipment for determining the occurrence place of group behaviors, which are used for determining the occurrence place of the group behaviors in time and can be used for intelligently evacuating aggregated groups in time. The method comprises the steps that a monitored environment area is divided into grid areas corresponding to different environment attributes, and each grid area is divided into at least one fine grid; processing the sampling data of the terminal in the fine grid area based on an edge data center, determining a terminal behavior parameterwarning value corresponding to the fine grid, and determining a terminal behavior parameter in the fine grid area; and according to the determined terminal behavior parameter alert value correspondingto the fine grid and the terminal behavior parameters in the fine grid area, determining whether the fine grid has a user group aggregation behavior or not.
Owner:中国移动通信集团甘肃有限公司 +1
A special group aggregation behavior early detection and aggregation place prediction method and system
InactiveCN109697438AQuick judgmentAutomatic removalCharacter and pattern recognitionVideo monitoringMoving average
The invention belongs to the field of group behavior management and control, and discloses a special group aggregation behavior early detection and aggregation place prediction method and system, andthe method comprises the steps: defining effective active members in a group through employing an aggregation behavior detection algorithm based on the moving average distance between the effective active members, and eliminating the interference of noise members on the aggregation behavior detection; For special groups with aggregation behaviors, the aggregation tendency of the groups is detectedin the early stage of group activities, and early warning is sent out; and screening out potential aggregation members by utilizing an aggregation prediction algorithm based on a least square fittingstraight line of the movement track of the potential aggregation members, and carrying out aggregation prediction. The method does not depend on a video monitoring system, only utilizes the historical moving track data of the group members to realize the rapid judgment of the special group aggregation behavior, gives an early warning for the group with the aggregation behavior in time, and can accurately predict the aggregation place of the group.
Owner:UNIVERSITY OF CHINESE ACADEMY OF SCIENCES
Behavior trajectory sequence multi-feature simulation method based on quantum walk
The invention discloses a behavior trajectory sequence multi-feature simulation method based on quantum walk. The method comprises the following steps: (1) generating a complete set feature sequence; (2) screening a feature sequence; (3) constructing a feature sequence mapping mechanism; (4) executing the experimental verification. According to the method, on the basis of conversion combination characteristics between individual behaviors and group behaviors, the feature structures of similar individuals are simulated from the perspective of multi-scale analysis by utilizing quantum migration, and behavior tracks are simulated.
Owner:NANJING NORMAL UNIVERSITY
Multi-tenant-based safe configuration method of virtual machine in cloud data center
InactiveCN106992962AAllocation satisfiedImprove service qualityTransmissionQuality of serviceCloud data center
The invention discloses a multi-tenant-based safe configuration method of a virtual machine in a cloud data center. The method comprises the following steps: collecting idle resource in the cloud data center; collecting recourse usage requests of user equipment; safely allocating the virtual machine resources which all users apply for by employing an artificial fish swarm algorithm; initializing parameters of the artificial fish swarm algorithm; calculating the optimal fish position and the optimal value and recording the same in a bulletin board; for each artificial fish, choosing and executing the optimal behavior among a swarming behavior, a following behavior and a preying behavior; calculating the new position and fitness function value of each artificial fish, and then updating the bulletin board; judging whether the algorithm termination condition is met or not, if not, returning to the second step, and if so, then entering the next step; taking the obtained optimal fitness function value as the optimal artificial fish position; and repeating the second to sixth steps for Ng times to obtain the optimal safe allocation result of the virtual machine resources. The invention can significantly improve the quality of service of users and reduces the resource waste of the cloud data center.
Owner:NANJING UNIV OF SCI & TECH
Swarming behavior in wagering game machines
InactiveUS8157640B2Apparatus for meter-controlled dispensingKnowledge representationGame basedSwarm behavior
Owner:BALLY GAMING INC
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