It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clu...It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clustering tasks according to spatio-temporal attributes,the clustered groups are linked into task sub-chains according to similarity.Then,based on the correlation between clusters,the child chains are connected to form a task chain.Therefore,the limitation is solved that the task chain in the bee colony algorithm can only be connected according to one dimension.When a sudden task occurs,a method of inserting a small number of tasks into the original task chain and a task chain reconstruction method are designed according to the relative relationship between the number of sudden tasks and the number of remaining tasks.Through the above improvements,the algorithm can be used to process tasks with spatio-temporal coupling and burst tasks.In order to reflect the efficiency and applicability of the algorithm,a task allocation model for the unmanned aerial vehicle(UAV)group is constructed,and a one-to-one correspondence between the improved bee colony double suppression division algorithm and each attribute in the UAV group is proposed.Task assignment has been constructed.The study uses the self-adjusting characteristics of the bee colony to achieve task allocation.Simulation verification and algorithm comparison show that the algorithm has stronger planning advantages and algorithm performance.展开更多
The microservices architecture has been proposed to overcome the drawbacks of the traditional monolithic architecture.Scalability is one of the most attractive features of microservices.Scaling in the microservices ar...The microservices architecture has been proposed to overcome the drawbacks of the traditional monolithic architecture.Scalability is one of the most attractive features of microservices.Scaling in the microservices architecture requires the scaling of specified services only,rather than the entire application.Scaling services can be achieved by deploying the same service multiple times on different physical machines.However,problems with load balancing may arise.Most existing solutions of microservices load balancing focus on individual tasks and ignore dependencies between these tasks.In the present paper,we propose TCLBM,a task chainbased load balancing algorithm for microservices.When an Application Programming Interface(API)request is received,TCLBM chooses target services for all tasks of this API call and achieves load balancing by evaluating the system resource usage of each service instance.TCLBM reduces the API response time by reducing data transmissions between physical machines.We use three heuristic algorithms,namely,Particle Swarm Optimization(PSO),Simulated Annealing(SA),and Genetic Algorithm(GA),to implement TCLBM,and comparison results reveal that GA performs best.Our findings show that TCLBM achieves load balancing among service instances and reduces API response times by up to 10%compared with existing methods.展开更多
An agile supply chain can be defined as a dynamic s up ply network of some autonomous or semi-autonomous business entities, which can well adapt to the competitive, cooperative and dynamic market environment Agile sup...An agile supply chain can be defined as a dynamic s up ply network of some autonomous or semi-autonomous business entities, which can well adapt to the competitive, cooperative and dynamic market environment Agile supply chain needs quick response ability to the unpredictable and ever-changin g market environment, and the entities in agile supply chain have complex relati onships of competition, cooperation and dynamics, which make agile supply chain management a very complex process that includes a lot of no-linear, dynamic and uncertain factors. There is a common opinion that applying multi-agent collaborative work environm ent is an appropriate method to solve agile supply chain management problem. We have presented a model based on coordination of Multi-Agent System (MAS) two ye ars ago, and it has already been proved to be a rather better model by practical project. In the model, we apply MAS structure, and agents negotiate each other to achieve coordination, so the communication among agents becomes very impo rtant. Task allocation is a very common problem in agile supply chain management, and t here are many complex task re-allocation problems at the transaction level. In such situations, agents need to negotiate with others to produce effective alloc ation results. But traditional negotiation mechanisms often cease to work as a r esult of communication or computational complexities. Auctions provide an effici ent way of resolving one-to-many negotiations, so in this paper, we choose Eng lish auction to design a sufficient negotiation mechanism, and use combinatorial auction to solve the complex task re-allocation problems. We first analyze the features of task allocation problems in agile supply chain and build a problem model, and then design a comprehensive task allocation mechanism based on auctio n theories. Finally, by examining our results for what it is, essentially, an ap plication of game-theory and mechanism design to existing application, we draw some general conclusions on how such concepts can be operationalized in automate d agents. Some further research on the problem is also discussed.展开更多
基金This work was supported by the National Natural Science and Technology Innovation 2030 Major Project of Ministry of Science and Technology of China(2018AAA0101200)the National Natural Science Foundation of China(61502522,61502534)+4 种基金the Equipment Pre-Research Field Fund(JZX7Y20190253036101)the Equipment Pre-Research Ministry of Education Joint Fund(6141A02033703)Shaanxi Provincial Natural Science Foundation(2020JQ-493)the Military Science Project of the National Social Science Fund(WJ2019-SKJJ-C-092)the Theoretical Research Foundation of Armed Police Engineering University(WJY202148).
文摘It is difficult for the double suppression division algorithm of bee colony to solve the spatio-temporal coupling or have higher dimensional attributes and undertake sudden tasks.Using the idea of clustering,after clustering tasks according to spatio-temporal attributes,the clustered groups are linked into task sub-chains according to similarity.Then,based on the correlation between clusters,the child chains are connected to form a task chain.Therefore,the limitation is solved that the task chain in the bee colony algorithm can only be connected according to one dimension.When a sudden task occurs,a method of inserting a small number of tasks into the original task chain and a task chain reconstruction method are designed according to the relative relationship between the number of sudden tasks and the number of remaining tasks.Through the above improvements,the algorithm can be used to process tasks with spatio-temporal coupling and burst tasks.In order to reflect the efficiency and applicability of the algorithm,a task allocation model for the unmanned aerial vehicle(UAV)group is constructed,and a one-to-one correspondence between the improved bee colony double suppression division algorithm and each attribute in the UAV group is proposed.Task assignment has been constructed.The study uses the self-adjusting characteristics of the bee colony to achieve task allocation.Simulation verification and algorithm comparison show that the algorithm has stronger planning advantages and algorithm performance.
文摘The microservices architecture has been proposed to overcome the drawbacks of the traditional monolithic architecture.Scalability is one of the most attractive features of microservices.Scaling in the microservices architecture requires the scaling of specified services only,rather than the entire application.Scaling services can be achieved by deploying the same service multiple times on different physical machines.However,problems with load balancing may arise.Most existing solutions of microservices load balancing focus on individual tasks and ignore dependencies between these tasks.In the present paper,we propose TCLBM,a task chainbased load balancing algorithm for microservices.When an Application Programming Interface(API)request is received,TCLBM chooses target services for all tasks of this API call and achieves load balancing by evaluating the system resource usage of each service instance.TCLBM reduces the API response time by reducing data transmissions between physical machines.We use three heuristic algorithms,namely,Particle Swarm Optimization(PSO),Simulated Annealing(SA),and Genetic Algorithm(GA),to implement TCLBM,and comparison results reveal that GA performs best.Our findings show that TCLBM achieves load balancing among service instances and reduces API response times by up to 10%compared with existing methods.
文摘An agile supply chain can be defined as a dynamic s up ply network of some autonomous or semi-autonomous business entities, which can well adapt to the competitive, cooperative and dynamic market environment Agile supply chain needs quick response ability to the unpredictable and ever-changin g market environment, and the entities in agile supply chain have complex relati onships of competition, cooperation and dynamics, which make agile supply chain management a very complex process that includes a lot of no-linear, dynamic and uncertain factors. There is a common opinion that applying multi-agent collaborative work environm ent is an appropriate method to solve agile supply chain management problem. We have presented a model based on coordination of Multi-Agent System (MAS) two ye ars ago, and it has already been proved to be a rather better model by practical project. In the model, we apply MAS structure, and agents negotiate each other to achieve coordination, so the communication among agents becomes very impo rtant. Task allocation is a very common problem in agile supply chain management, and t here are many complex task re-allocation problems at the transaction level. In such situations, agents need to negotiate with others to produce effective alloc ation results. But traditional negotiation mechanisms often cease to work as a r esult of communication or computational complexities. Auctions provide an effici ent way of resolving one-to-many negotiations, so in this paper, we choose Eng lish auction to design a sufficient negotiation mechanism, and use combinatorial auction to solve the complex task re-allocation problems. We first analyze the features of task allocation problems in agile supply chain and build a problem model, and then design a comprehensive task allocation mechanism based on auctio n theories. Finally, by examining our results for what it is, essentially, an ap plication of game-theory and mechanism design to existing application, we draw some general conclusions on how such concepts can be operationalized in automate d agents. Some further research on the problem is also discussed.
