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Energy conservation techniques in mobile delay-tolerant sensor networks.

机译:移动延迟容限传感器网络中的节能技术。

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Mobile delay-tolerant sensor networks are becoming increasingly important because of their ability to deliver long periods of fine-grained sensing over a wide area with a small number of nodes. A key challenge in these systems, however, is that nodes are extremely energy constrained since they must be small, lightweight, and function autonomously for months at a time. This problem is compounded by the fact that mobile nodes demand radios with relatively long ranges to maximize the effectiveness of short, infrequent communication periods.; This dissertation explores energy conservation techniques for these networks from a variety of system viewpoints. From the application's viewpoint, it introduces a family of lossless compression algorithms tailored to sensor networks. These algorithms include a novel LZW variant that exploits characteristic patterns of sensor data to reduce energy consumption by more than 40% as well as further data transforms that can take advantage of the structure of the data to decrease energy consumption by nearly a factor of three.; Then, this dissertation explores a data abstraction layer for mobile sensor networks that lies between the file system and the application to reorganize data from the network's viewpoint. This organization facilitates the development of services for data identification, search, and reduction, which combine to save energy by making communications more efficient.; Finally, it looks at system-specific energy trade-offs throughout the system, from the hardware-software interface to the application. For reference, this dissertation explores two detailed case studies from the ZebraNet project, in which we designed, developed, and deployed an energy-aware mobile sensor network that employed peer-to-peer protocols and mobile ad-hoc networking technologies to help track zebra migrations in ways not possible with current animal tracking technology.; As energy is the fundamental constraint in mobile delay-tolerant sensor networks, interest in novel energy conservation techniques for these systems continues to grow. This dissertation explores the energy issues inherent to mobile sensor nodes and proposes numerous energy-saving methods that have the potential to greatly increase system lifetime and usability.
机译:容忍移动时延的传感器网络变得越来越重要,因为它们具有使用少量节点在宽广的区域上提供长时间的细粒度传感的能力。但是,这些系统中的一个关键挑战是,节点必须严格限制能源,因为它们必须小巧,轻巧,并且一次只能运行数月。移动节点需要具有相对较长范围的无线电以使短的,不频繁的通信周期的有效性最大化的事实使这个问题更加复杂。本文从多种系统角度探讨了这些网络的节能技术。从应用程序的角度来看,它引入了一系列针对传感器网络量身定制的无损压缩算法。这些算法包括一个新颖的LZW变体,该变体利用传感器数据的特征模式将能耗降低了40%以上,并进行了进一步的数据转换,可以利用数据结构将能耗降低近三倍。 ;然后,本文探索了移动传感器网络的数据抽象层,该层位于文件系统和应用程序之间,以从网络的角度重新组织数据。该组织促进了数据识别,搜索和还原服务的开发,这些服务结合起来可以通过提高通信效率来节省能源。最后,它研究了整个系统中从硬件-软件接口到应用程序的特定于系统的能源平衡。作为参考,本文探讨了ZebraNet项目的两个详细案例研究,在其中我们设计,开发和部署了一个能源感知型移动传感器网络,该网络使用对等协议和移动自组网技术来帮助跟踪斑马线。以目前的动物追踪技术无法实现的迁移。由于能量是移动延迟容忍传感器网络中的基本约束,因此对于这些系统的新型节能技术的兴趣持续增长。本文探讨了移动传感器节点固有的能源问题,并提出了许多节能方法,这些方法有可能极大地延长系统寿命和可用性。

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