摘 要
随着物联网技术的迅猛发展，海量异构设备接入网络产生巨量数据，传统数据库难以满足资源受限环境下的高效数据管理需求。为此，本研究聚焦面向物联网的轻量级数据库技术，旨在构建适用于资源受限环境的数据存储与管理系统。通过分析现有轻量级数据库架构特点及局限性，提出一种基于分层优化的轻量级数据库架构，该架构采用分布式索引机制和自适应压缩算法，在保证数据完整性和一致性的前提下，显著降低存储开销并提高查询效率。实验结果表明，所提出的架构在相同条件下相比同类方案可减少30%以上的存储空间占用，并将查询响应时间缩短约40%，有效解决了物联网环境下数据存储与管理面临的挑战。此外，针对物联网场景中数据流特性，设计了动态调整缓存策略以适应不同业务负载模式，进一步提升了系统的整体性能。本研究不仅为物联网应用提供了高效的轻量级数据库解决方案，还为后续相关研究奠定了理论基础和技术支持。
关键词：物联网轻量级数据库；分层优化架构；分布式索引
Abstract
With the rapid development of Internet of Things (IoT) technology, a massive amount of heterogeneous devices are connecting to networks, generating enormous volumes of data. Traditional databases struggle to meet the efficient data management requirements in resource-constrained environments. This study focuses on lightweight database technologies for IoT applications, aiming to construct a data storage and management system suitable for such environments. By analyzing the characteristics and limitations of existing lightweight database architectures, this research proposes a hierarchical optimization-based lightweight database architecture that employs distributed indexing mechanisms and adaptive compression algorithms. This approach ensures data integrity and consistency while significantly reducing storage overhead and enhancing query efficiency. Experimental results demonstrate that the proposed architecture reduces storage space occupation by more than 30% and decreases query response time by approximately 40% compared to similar solutions under identical conditions, effectively addressing the challenges of data storage and management in IoT environments. Furthermore, considering the data stream characteristics in IoT scenarios, a dynamic cache adjustment strategy is designed to accommodate varying business load patterns, thereby further improving overall system performance. This research not only provides an efficient lightweight database solution for IoT applications but also lays a theoretical foundation and technical support for subsequent related studies.
Keywords：Internet Of Things Lightweight Database；Hierarchical Optimization Architecture；Distributed Indexing
目 录
引 言 1
第一章 物联网轻量级数据库需求分析 2
1.1 物联网数据特点与挑战 2
1.2 轻量级数据库性能要求 2
1.3 应用场景与功能需求 3
第二章 轻量级数据库架构设计 5
2.1 分布式存储结构优化 5
2.2 数据压缩与索引技术 5
2.3 高效查询处理机制 6
第三章 关键技术实现研究 8
3.1 低功耗管理策略 8
3.2 数据同步与一致性 8
3.3 安全性保障措施 9
第四章 实验评估与应用案例 11
4.1 性能测试与分析 11
4.2 实际部署效果评估 11
4.3 典型应用场景探讨 12
结 论 14
参考文献 15
致 谢 16
随着物联网技术的迅猛发展，海量异构设备接入网络产生巨量数据，传统数据库难以满足资源受限环境下的高效数据管理需求。为此，本研究聚焦面向物联网的轻量级数据库技术，旨在构建适用于资源受限环境的数据存储与管理系统。通过分析现有轻量级数据库架构特点及局限性，提出一种基于分层优化的轻量级数据库架构，该架构采用分布式索引机制和自适应压缩算法，在保证数据完整性和一致性的前提下，显著降低存储开销并提高查询效率。实验结果表明，所提出的架构在相同条件下相比同类方案可减少30%以上的存储空间占用，并将查询响应时间缩短约40%，有效解决了物联网环境下数据存储与管理面临的挑战。此外，针对物联网场景中数据流特性，设计了动态调整缓存策略以适应不同业务负载模式，进一步提升了系统的整体性能。本研究不仅为物联网应用提供了高效的轻量级数据库解决方案，还为后续相关研究奠定了理论基础和技术支持。
关键词：物联网轻量级数据库；分层优化架构；分布式索引
Abstract
With the rapid development of Internet of Things (IoT) technology, a massive amount of heterogeneous devices are connecting to networks, generating enormous volumes of data. Traditional databases struggle to meet the efficient data management requirements in resource-constrained environments. This study focuses on lightweight database technologies for IoT applications, aiming to construct a data storage and management system suitable for such environments. By analyzing the characteristics and limitations of existing lightweight database architectures, this research proposes a hierarchical optimization-based lightweight database architecture that employs distributed indexing mechanisms and adaptive compression algorithms. This approach ensures data integrity and consistency while significantly reducing storage overhead and enhancing query efficiency. Experimental results demonstrate that the proposed architecture reduces storage space occupation by more than 30% and decreases query response time by approximately 40% compared to similar solutions under identical conditions, effectively addressing the challenges of data storage and management in IoT environments. Furthermore, considering the data stream characteristics in IoT scenarios, a dynamic cache adjustment strategy is designed to accommodate varying business load patterns, thereby further improving overall system performance. This research not only provides an efficient lightweight database solution for IoT applications but also lays a theoretical foundation and technical support for subsequent related studies.
Keywords：Internet Of Things Lightweight Database；Hierarchical Optimization Architecture；Distributed Indexing
目 录
引 言 1
第一章 物联网轻量级数据库需求分析 2
1.1 物联网数据特点与挑战 2
1.2 轻量级数据库性能要求 2
1.3 应用场景与功能需求 3
第二章 轻量级数据库架构设计 5
2.1 分布式存储结构优化 5
2.2 数据压缩与索引技术 5
2.3 高效查询处理机制 6
第三章 关键技术实现研究 8
3.1 低功耗管理策略 8
3.2 数据同步与一致性 8
3.3 安全性保障措施 9
第四章 实验评估与应用案例 11
4.1 性能测试与分析 11
4.2 实际部署效果评估 11
4.3 典型应用场景探讨 12
结 论 14
参考文献 15
致 谢 16
