Cloud applications are implemented on top of different distributed systems to provide online service.A service request is decomposed into multiple sub-tasks,which are dispatched to different distributed systems compon...Cloud applications are implemented on top of different distributed systems to provide online service.A service request is decomposed into multiple sub-tasks,which are dispatched to different distributed systems components.For cloud providers,monitoring the execution of a service request is crucial to promptly find problems that may compromise cloud availability.In this paper,we present AgamottoEye,to automatically construct request flow from existing logs.AgamottoEye addresses the challenges of analyzing interleaved log instances,and can successfully extract request flow spread across multiple distributed systems.Our experiments with Hadoop2/YARN show that AgamottoEye can analyze 25,050 log instances in 57.4s,and the extracted request flow information is helpful with error detection and diagnosis.展开更多
为了保证服务质量(quality of service,QoS),进入网络中的数据流可被赋予不同的优先级。在未来到达流请求信息未到达的情况下,进行在线优先级流调度,以最大化网络吞吐量是一项挑战。基于网络带宽资源、请求流的优先级和带宽需求的约束...为了保证服务质量(quality of service,QoS),进入网络中的数据流可被赋予不同的优先级。在未来到达流请求信息未到达的情况下,进行在线优先级流调度,以最大化网络吞吐量是一项挑战。基于网络带宽资源、请求流的优先级和带宽需求的约束研究了软件定义网络(software defined networking,SDN)中的在线流请求调度策略。首先,提出了流路由成本和利润的概念,并创新性地设计了一个考虑边际成本的模型来描述链路资源和路由路径的使用成本。然后,将优先级流请求调度问题刻画为混合整数线性规划模型(mixed integer linear programming,MILP),提出在线优先级流调度算法(online priority traffic scheduling algorithm,OPTSA)来求解,最后分析了OPTSA的竞争比。仿真结果显示,与基准算法相比,所提出的算法可以确保网络负载均衡,同时有效提高网络的累积带宽和吞吐量。展开更多
文摘Cloud applications are implemented on top of different distributed systems to provide online service.A service request is decomposed into multiple sub-tasks,which are dispatched to different distributed systems components.For cloud providers,monitoring the execution of a service request is crucial to promptly find problems that may compromise cloud availability.In this paper,we present AgamottoEye,to automatically construct request flow from existing logs.AgamottoEye addresses the challenges of analyzing interleaved log instances,and can successfully extract request flow spread across multiple distributed systems.Our experiments with Hadoop2/YARN show that AgamottoEye can analyze 25,050 log instances in 57.4s,and the extracted request flow information is helpful with error detection and diagnosis.
文摘为了保证服务质量(quality of service,QoS),进入网络中的数据流可被赋予不同的优先级。在未来到达流请求信息未到达的情况下,进行在线优先级流调度,以最大化网络吞吐量是一项挑战。基于网络带宽资源、请求流的优先级和带宽需求的约束研究了软件定义网络(software defined networking,SDN)中的在线流请求调度策略。首先,提出了流路由成本和利润的概念,并创新性地设计了一个考虑边际成本的模型来描述链路资源和路由路径的使用成本。然后,将优先级流请求调度问题刻画为混合整数线性规划模型(mixed integer linear programming,MILP),提出在线优先级流调度算法(online priority traffic scheduling algorithm,OPTSA)来求解,最后分析了OPTSA的竞争比。仿真结果显示,与基准算法相比,所提出的算法可以确保网络负载均衡,同时有效提高网络的累积带宽和吞吐量。
