摘 要
随着信息技术的迅猛发展，大数据和云计算已成为推动社会进步与产业升级的核心驱动力。在云计算环境下，如何高效处理海量数据并挖掘其潜在价值成为当前研究的重要课题。本研究旨在探索适用于云计算环境的大数据处理技术，以解决传统方法在扩展性、效率及成本控制方面的局限性。通过深入分析云计算架构特点及其对大数据处理的需求，本文提出了一种基于分布式计算框架的优化算法，并结合虚拟化技术和负载均衡策略，显著提升了系统资源利用率和任务执行效率。同时，研究设计了多层数据预处理机制，有效降低了噪声干扰和冗余信息的影响，为后续分析提供了高质量的数据支持。实验结果表明，所提方法在大规模数据集上的处理速度较现有方案提升约30%，且具备良好的可扩展性和稳定性。此外，本文还探讨了隐私保护技术在大数据处理中的应用，提出了数据加密与访问控制相结合的安全框架，确保敏感信息在云端存储与传输过程中的安全性。总体而言，本研究不仅为云计算环境下的大数据处理提供了新的技术路径，还为相关领域的实际应用奠定了理论基础，具有重要的学术价值和实践意义。
关键词：大数据处理 云计算 分布式计算框架
Abstract
With the rapid development of information technology, big data and cloud computing have become the core driving forces for social progress and industrial upgrading. In a cloud computing environment, efficiently processing massive amounts of data and uncovering their potential value has emerged as a critical research topic. This study focuses on exploring big data processing technologies tailored for cloud computing environments to address the limitations of traditional methods in scalability, efficiency, and cost control. By thoroughly analyzing the characteristics of cloud computing architectures and their requirements for big data processing, this paper proposes an optimized algorithm based on a distributed computing fr amework. Combined with virtualization techniques and load balancing strategies, the proposed approach significantly enhances system resource utilization and task execution efficiency. Additionally, a multi-layer data preprocessing mechanism is designed to effectively reduce the impact of noise interference and redundant information, providing high-quality data support for subsequent analyses. Experimental results demonstrate that the proposed method achieves approximately a 30% improvement in processing speed on large-scale datasets while maintaining excellent scalability and stability. Furthermore, this paper investigates the application of privacy protection technologies in big data processing and proposes a secure fr amework integrating data encryption and access control, ensuring the security of sensitive information during storage and transmission in the cloud. Overall, this research not only provides new technical pathways for big data processing in cloud computing environments but also lays a theoretical foundation for practical applications in related fields, showcasing significant academic and practical implications.
Keyword:Big Data Processing Cloud Computing Distributed Computing fr amework
目 录
引言 1
1云计算与大数据处理基础 1
1.1云计算技术概述 1
1.2大数据处理的基本概念 2
1.3云计算与大数据的关联分析 2
2云计算环境下的大数据存储技术 3
2.1分布式存储系统架构 3
2.2数据存储优化策略研究 3
2.3存储系统的可靠性与安全性 4
3云计算环境下的大数据计算框架 4
3.1并行计算模型分析 4
3.3流计算技术在云计算中的实现 5
4云计算环境下的大数据处理性能优化 5
4.1资源调度算法研究 6
4.2数据传输效率提升方法 6
4.3系统性能评估与优化策略 6
结论 7
参考文献 8
致谢 9
