摘要
作为未来通信网络技术发展趋势之一,物联网是复杂、综合的跨学科研究领域,在设计、研究和实现等各个方面均面临着诸多难题和挑战,存在大量的基础科学问题亟待解决,如大规模网络的复杂性、网络环境的动态性、多元异构性、资源的有限性等问题。在生命科学的快速发展和推动下,以自然界中生命调控方法和作用规律为基础的生物智能理论得到了进一步的发展和应用。其中,很多生物智能方法具有异构性、自组织、动态性和可扩展等特征,为设计高效、具有鲁棒性的网络系统架构、算法和机制提供了借鉴和参考。本论文针对物联网的特性和需求,利用生物启发的网络智能理论与相关机制来研究物联网大规模异构网元的互连、分布式动态自组织方式和动态环境中网元间协同合作与服务等问题,为建立物联网协同自治理论奠定基础。本论文主要工作如下：
(1)对物联网的基本特性、研究目标、相关研究背景和面临的挑战等内容进行了概括,并对生物智能算法的发展、研究现状和应用领域进行了综述,分析了生物智能应用于解决物联网等通信网络技术在发展中面临问题的可行性,为本文研究物联网中网元互连与交互、动态自组织、服务响应方式等相关问题提供了基本思路。
(2)基于生物体内分泌系统中的激素传递和调节机理,设计了生物启发的物联网网元间分布式信息交互机制,并在此基础上提出了分布式协同跟踪算法(EIDCA)用于解决无线传感器网络中的目标跟踪问题。仿真结果证明在EIDCA算法作用下,网元能够在分布式的网络结构中进行高效的信息交换与相互作用,在维持网络稳定的同时能够完成目标跟踪任务,与其它分布式跟踪算法相比具有更好的跟踪效果和保持跟踪能力。
(3)基于人体内分泌血糖调节模型,提出了一种适用于物联网的动态自组织算法(ISOS),使网元能够在其动态局部自治区内根据其自身状态和周围环境情况进行自我调节；另外,该算法以多种激素作为不同信息载体,通过对自治网元激素释放过程的调控来实现网元之间的自组织与协同合作功能。仿真结果证明了在该动态自组织算法的作用下,自治网元能够在分布式网络结构中相互协作、高效组织起来,以维持物联网的全局稳定状态并完成网络目标,具有较好的调节能力和稳定性；另外,当网络期望唤醒网元概率较小时ISOS算法能够取得更大的性能优势,尤其适合在网络资源有限的条件下使用。
(4)为满足物联网动态环境中“常响应”服务模式需要,本论文建立了物联网智能服务模型；同时基于人体神经-内分泌系统的相互调节机制及其对内稳态的综合调控机理,设计了“常响应”模式的动态服务请求的监测算法(HITS)。实验结果证明了在HITS作用下,物联网在维持稳定的同时能够对随机产生的服务请求具有较好的监测和快速响应能力,并通过预测用户的运动范围来实现对移动中用户服务状态的持续监控,为建立物联网面向服务的体系结构、实现动态环境中物联网的智能服务与应用提供了参考方案。
论文的最后总结全文的研究工作,并对下一步的目标和研究方向进行了讨论和展望。
As a future development trend of the communication network technologies, the Internet of Things (IoT) is an integrated interdisciplinary research area which faces many difficulties and challenges on designing, researching and realization. There are a lot of basic scientific problems to be solved, e.g. complexity of the large-scale network, dynamic characteristics of network environments, efficient control of massive heterogeneous network elements, resource and energy limitations, etc.. With the rapid development of biology science, the biological intelligent theory, which is inspired by the life regulation and control mechanisms in nature, has become more developed, and the application and popularization have already come into a new stage. Many bio-inspired methods endow systems or networks with the heterogeneity, autonomy, autonomous, dynamics and scalability, which can be references and inspirations for designing new efficient network architectures and mechanisms. Taking the features and requirements of the IoT into account, this work focuses on the issues of data exchange and interaction among heterogeneous network elements, distributed self-organization schemes and intelligent service provision in the dynamic system environment, and tries to solve these problems by applying biological intelligence methods and theories, which can lay the foundation for the cooperative autonomous theory of the IoT. The main contribution of the thesis lies in:
(1) A summarization of the features, challenges and relevant research work of the IoT is provided. The feasibility of the biological intelligence is analyzed in solving the problems in the communication networks like the IoT, especially the regulation principles and mechanism in maintaining the homeostasis of internal environment by the endocrine system and neural system. This thesis also provides the methods of the researches on the interactions among network elements, self-organization, maintenance of network's stability and scalability, and service request response methods.
(2) An information interaction mechanism among the IoT elements is designed inspired by the hormone transmission and regulation principles in the endocrine system. Based on this, an endocrine-based intelligent distributed cooperative algorithm (EIDCA) is also given for object tracking in the wireless sensor networks, and a numerical evaluating method is designed to provide an explicit measurement for comparison of different algorithms. Experiment results show that with the proposed EIDCA, the network elements can exchange information and interactive efficiently in a distributed way and the EIDCA accomplishes the tracking mission for the invading object more efficiently and persistently compared with other algorithms.
(3) An intelligent self-organizing scheme (ISOS) for the IoT inspired by the endocrine regulating mechanisms of blood glucose regulation is proposed. For each node in the network, an autonomous area is established, where the node can effectively interact with its peers and perform self-control according to its own status and dynamic circumstance in a decentralized infrastructure. To act as the media for the information transmission and data sharing among the nodes, the concept of the hormone with different purposes is introduced and implemented numerically, and the nodes can therefore collaborate with each other and worked in a cooperative way. By adjusting the releasing procedure of the hormones, the ability of effectively detecting service requests randomly generated can also be guaranteed in the probabilistic partially-working IoT. A series of scenario-based simulations with results verifies the performance of the proposed mechanism entitles the IoT with the ability of maintaining its status in a globally stable status and effectively discovering the random service requests in a resource-critical configuration, which would be of great significance for the practical implementation of the IoT.
(4) Inspired by the neuroendocrine comprehensive regulation mechanism of maintaining the homeostasis in human body, an IoT intelligent service model and dynamic service request detection algorithm (HITS) for realizing "always response service" in the dynamic environment are proposed. A dynamic information exchange scheme plays a critical part in the HITS to guarantee the rapidness of the network on responding the randomly generated service requests. Simulation results show that the proposed HITS algorithm can be regarded as a qualified instance of the distributed IoT infrastructure. The application of the HITS algorithm entitles the network with intelligent decision-making and cooperative working abilities, by which the autonomy of the nodes, the stability of the network and the effectiveness for providing service to the potential service-in-need targets can be guaranteed simultaneously.
Finally a conclusion is made for the whole contents of this dissertation, together with the perspectives of this field for the next step.
引文
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