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基于ICN的数据中心服务调度方法优化设计

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虚拟化技术使得数据中心的服务可以在任意位置灵活部署,同时也引入如何合理调度用户的服务请求到这些位置的问题.本文提出一种基于信息中心网络(ICN)技术的数据中心服务调度方法——ICSS.基于ICN标识与地址分离特性,ICSS可直接在网络层数据平面级别提供分布式服务调度功能,网络层数据平面支持线速转发,能实时快速处理服务请求的调度决策,避免传统调度方案在路径延伸和传输时延方面的不足.ICSS考虑服务请求大小及虚拟机资源负载情况,基于PSO-GA算法进行服务调度,以优化服务响应时间和虚拟机负载均衡程度,提高网络的扩展性.为实现与现有数据中心IP业务的无缝承接,本文设计一种ICN协议与IP网络协议的转换方法,确保ICSS对客户端和服务端透明.实验表明,相较于传统的加权最小连接算法(WLC),ICSS的服务完成时间平均减少约21%,CPU、内存资源利用率方差分别平均减少约10%、10%;相较于网络层分布式服务调度方法——分布式计算感知调度算法(CArDS),ICSS在服务请求数量较多时具有更少的服务完成时间,CPU、内存资源利用率方差分别平均减少约32%、29%,转发表表项平均减少约97%,控制开销数量平均减少约98%.ICSS在服务完成时间、负载均衡以及可扩展性方面具有明显优势.
Optimized Design of Data Center Service Scheduling Method Based on ICN
Virtualization technology enables flexible deployment of data center services at any location,introducing challenges in effi-ciently scheduling service requests to these potential locations.This paper proposes a data center service scheduling method based on Information Centric Networking(ICN)called ICSS(Service Scheduling Based on ICN).Leveraging the ICN's identifier-address sepa-ration,ICSS provides distributed service scheduling directly at the network layer's data plane,supporting line-speed forwarding to make real-time decisions on service request scheduling.This approach addresses the shortcomings of traditional scheduling methods re-garding path extension and transmission latency.ICSS considers service request size and virtual machine resource loads,employing the Particle Swarm Optimization and Genetic Algorithm(PSO-GA)for service scheduling to optimize service response time,enhance virtu-al machine load balancing and improving network scalability.To seamlessly integrate with existing data center IP services,this paper designs a method for the conversion between ICN and IP network protocols,ensuring transparency for ICSS to clients and servers.Ex-periments demonstrate that compared to the traditional Weighted Least Connection Algorithm(WLC),ICSS reduces the average service completion time by approximately 21%,and variances in CPU and memory resource utilization are reduced by an average of approxi-mately 10%and 10%.Compared to the network-layer distributed service scheduling method CArDS(Compute-Aware Distributed Scheduling),ICSS exhibits lower service completion times,with average reductions of approximately 32%and 29%in CPU and mem-ory resource utilization variances,respectively.Additionally,ICSS achieves an average reduction of approximately 97%in forwarding table entries and an average reduction of approximately 98%in control overhead.ICSS demonstrates significant advantages in service completion time,load balancing,and scalability.

information-centric networkingdata center networkservice schedulingload balancing methodsprotocol conversion

王婷、尤佳莉、韩锐

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中国科学院声学研究所 国家网络新媒体工程技术研究中心 北京 100190

中国科学院大学 北京 100049

信息中心网络 数据中心网络 服务调度 负载均衡 协议转换

国家重点研发计划课题

2023YFB2906404

2024

网络新媒体技术
中国科学院声学研究所

网络新媒体技术

CSTPCD
影响因子:0.208
ISSN:2095-347X
年,卷(期):2024.13(5)