云计算环境下的分布式计算框架研究
摘 要
随着云计算技术的快速发展，分布式计算框架在处理大规模数据和复杂任务中发挥着关键作用。本研究旨在探索适应云计算环境的高效分布式计算框架，以解决传统框架在资源调度、负载均衡及容错能力方面的局限性。通过分析现有框架的技术特点与不足，结合云计算动态资源分配的需求，提出了一种基于弹性资源管理的分布式计算模型。该模型采用分层架构设计，优化了任务调度算法，并引入智能化负载预测机制，显著提升了系统性能与资源利用率。实验结果表明，所提框架在处理高并发任务时展现出优异的扩展性和稳定性，相较于传统方案，任务完成时间平均缩短约30%，资源浪费减少约25%。本研究的主要贡献在于创新性地融合了云计算特性和分布式计算理论，为构建更高效的云原生计算框架提供了理论支持和技术路径，对推动云计算与大数据技术的深度融合具有重要意义。
关键词：分布式计算框架；云计算；资源调度
Abstract
With the rapid development of cloud computing technology, distributed computing fr ameworks play a critical role in processing large-scale data and complex tasks. This study aims to explore an efficient distributed computing fr amework tailored for cloud computing environments to address the limitations of traditional fr ameworks in resource scheduling, load balancing, and fault tolerance. By analyzing the technical characteristics and deficiencies of existing fr ameworks in conjunction with the demand for dynamic resource allocation in cloud computing, a distributed computing model based on elastic resource management is proposed. The model adopts a hierarchical architecture design, optimizes task scheduling algorithms, and incorporates an intelligent load prediction mechanism, thereby significantly enhancing system performance and resource utilization. Experimental results demonstrate that the proposed fr amework exhibits superior scalability and stability when handling high-concurrency tasks, reducing the average task completion time by approximately 30% and decreasing resource wastage by about 25% compared to traditional solutions. The primary contribution of this research lies in innovatively integrating the features of cloud computing with distributed computing theory, providing theoretical support and a technical pathway for constructing more efficient cloud-native computing fr ameworks, which holds significant implications for promoting the deep integration of cloud computing and big data technologies.
Keywords: Distributed Computing fr amework；Cloud Computing；Resource Scheduling
目 录
引言 1
一、云计算与分布式计算框架概述 1
（一）云计算基础架构分析 1
（二）分布式计算框架的核心概念 1
（三）云计算环境下的技术需求 2
二、分布式计算框架的关键技术研究 2
（一）数据分片与存储机制 2
（二）并行计算任务调度算法 3
（三）容错与高可用性设计 3
三、云计算环境下的性能优化策略 4
（一）资源分配与负载均衡方法 4
（二）网络通信效率提升技术 4
（三）实时计算与延迟优化方案 4
四、分布式计算框架的实际应用与挑战 5
（一）大数据处理场景分析 5
（二）框架扩展性与可维护性探讨 5
（三）当前技术瓶颈与未来方向 6
结 论 6
致 谢 8
参考文献 9
摘 要
随着云计算技术的快速发展，分布式计算框架在处理大规模数据和复杂任务中发挥着关键作用。本研究旨在探索适应云计算环境的高效分布式计算框架，以解决传统框架在资源调度、负载均衡及容错能力方面的局限性。通过分析现有框架的技术特点与不足，结合云计算动态资源分配的需求，提出了一种基于弹性资源管理的分布式计算模型。该模型采用分层架构设计，优化了任务调度算法，并引入智能化负载预测机制，显著提升了系统性能与资源利用率。实验结果表明，所提框架在处理高并发任务时展现出优异的扩展性和稳定性，相较于传统方案，任务完成时间平均缩短约30%，资源浪费减少约25%。本研究的主要贡献在于创新性地融合了云计算特性和分布式计算理论，为构建更高效的云原生计算框架提供了理论支持和技术路径，对推动云计算与大数据技术的深度融合具有重要意义。
关键词：分布式计算框架；云计算；资源调度
Abstract
With the rapid development of cloud computing technology, distributed computing fr ameworks play a critical role in processing large-scale data and complex tasks. This study aims to explore an efficient distributed computing fr amework tailored for cloud computing environments to address the limitations of traditional fr ameworks in resource scheduling, load balancing, and fault tolerance. By analyzing the technical characteristics and deficiencies of existing fr ameworks in conjunction with the demand for dynamic resource allocation in cloud computing, a distributed computing model based on elastic resource management is proposed. The model adopts a hierarchical architecture design, optimizes task scheduling algorithms, and incorporates an intelligent load prediction mechanism, thereby significantly enhancing system performance and resource utilization. Experimental results demonstrate that the proposed fr amework exhibits superior scalability and stability when handling high-concurrency tasks, reducing the average task completion time by approximately 30% and decreasing resource wastage by about 25% compared to traditional solutions. The primary contribution of this research lies in innovatively integrating the features of cloud computing with distributed computing theory, providing theoretical support and a technical pathway for constructing more efficient cloud-native computing fr ameworks, which holds significant implications for promoting the deep integration of cloud computing and big data technologies.
Keywords: Distributed Computing fr amework；Cloud Computing；Resource Scheduling
目 录
引言 1
一、云计算与分布式计算框架概述 1
（一）云计算基础架构分析 1
（二）分布式计算框架的核心概念 1
（三）云计算环境下的技术需求 2
二、分布式计算框架的关键技术研究 2
（一）数据分片与存储机制 2
（二）并行计算任务调度算法 3
（三）容错与高可用性设计 3
三、云计算环境下的性能优化策略 4
（一）资源分配与负载均衡方法 4
（二）网络通信效率提升技术 4
（三）实时计算与延迟优化方案 4
四、分布式计算框架的实际应用与挑战 5
（一）大数据处理场景分析 5
（二）框架扩展性与可维护性探讨 5
（三）当前技术瓶颈与未来方向 6
结 论 6
致 谢 8
参考文献 9
