摘要
分布异构计算资源通过网络连接形成算力网络(Computing power network,CPN),其以“连”和“算”为核心.针对广分布异构性导致可行解空间巨大、强不确定性导致可行解空间易变、高约束复杂性导致可行解孤岛繁多、多目标性导致冲突目标权衡优化难等挑战,提出一个多层次算力网络体系框架,包括参数化结构化业务管理、三阶段(计划、调度、执行)闭环调度模式、多模态资源管理三个功能.提出支持快速、高效、鲁棒的“算法+知识+数据+算力”的算力网络智慧调度框架,形式化分析可行解空间,解析调度策略关键参数,定性分析调度算法性能与效率的内在关系,详细综述调度算法类型,综述算力网络调度研究进展与发展方向.对比已有相关综述研究,展望算力网络调度未来理论和技术的难点与趋势.
Distributed heterogeneous computing resources are connected through the network to form a computing power network(CPN),in which“connection”and“computing”are the cores.There are several great challenges including the huge feasible solution space resulted from widely distributed heterogeneity,the variable feasible solution space caused by strong uncertainty,a large number of feasible solution islands resulted from highly constrained complexity,and the difficulty in optimizing multiple conflicting objectives.For these challenges,a multilevel computing power network framework is proposed in this paper,which contains three functions:Parameterized structural process management,three-phase(planning,scheduling,execution)closed-loop scheduling model,and multi-modal resource management.A computing power network intelligent scheduling framework with“algorithm+knowledge+data+computing power”is proposed to wisely schedule complex tasks to CPN resources effectively,efficiently and robustly.The feasible solution space is formally analyzed.The key parameters of scheduling strategy are introduced.The intrinsic relationship between effectiveness and efficiency of scheduling algorithms are qualitatively analyzed.Different types of scheduling algorithms are surveyed thoroughly.The state-of-the-art and future work are illustrated.The surveys on CPN scheduling algorithms are compared,followed by the theoretical and technical problems and tendency in CPN scheduling algorithms.
作者
李逸博
李小平
王爽
蒋嶷川
LI Yi-Bo;LI Xiao-Ping;WANG Shuang;JIANG Yi-Chuan(School of Computer Science and Engineering,Southeast University,Nanjing 211189;Key Laboratory of Computer Network and Information Integration,Ministry of Education,Southeast University,Nanjing 211189;School of Computer Science and Technology,Guangdong University of Technology,Guangzhou 510006)
出处
《自动化学报》
EI
CAS
CSCD
北大核心
2024年第6期1086-1103,共18页
Acta Automatica Sinica
基金
国家重点研发计划(2022YFB3305500)
国家自然科学基金(62273089)资助。
关键词
算力网络
云计算
边缘计算
资源调度
知识
Computing power network(CPN)
cloud computing
edge computing
resource scheduling
knowledge
