无线传感器网络中英文对照外文翻译文献Word下载.docx

1、Distributed localization in wireless sensor networks: a quantitative comparisonABSTRACTThis paper studies the problem of determining the node locations in ad-hoc sensor networks. We compare three distributed localization algorithms （Ad-hoc positioning, Robust positioning, and N-hop multi late ration

2、） on a single simulation platform. The algorithms share a common, three-phase structure: （1）1determine nodeanchor distances, （2） compute node positions, and （3） optionally refine the positions through an iterative procedure. We present a detailed analysis comparing the various alternatives for each

3、phase, as well as a head-to-head comparison of the complete algorithms. The main conclusion is that no single algorithm performs best; which algorithm is to be preferred depends on the conditions （range errors, connectivity, anchor fraction, etc.）. In each case, however, there is significant room fo

4、r improving accuracy and/or increasingcoverageINTRODUCTIONWireless sensor networks hold the promise of many new applications in thearea of monitoring and control. Examples include target tracking, intrusion detection, wildlife habitat monitoring, climate control, and disaster management. The underly

5、ing technology that drives the emergence of sensor applications is the rapid development in the integration of digital circuitry, which will bring us small, cheap, autonomous sensor nodes in the near future.New technology offers new opportunities, but it also introduces new problems. This is particu

6、larly true for sensor networks where the capabilities of individual nodes are very limited. Hence, collaboration between nodes is required, but energy conservation is a major concern, which implies that communication should be minimized. These conflicting objectives requireunorthodox solutions for m

7、any situations.A recent survey by Akyildiz et al. discusses a longissues that must be addressed before sensor networks deployed. The problems range from the physical layerlist of open researchcan become widely （low-power sensing,processing, and communication hardware） all the way up to the applicati

8、on layer （query and data dissemination protocols）. In this paper we address the issue of localization in ad-hoc sensor networks. That is, we want to determine the location of individual sensor nodes without relying on external infrastructure（base stations, satellites, etc.）.2The localization problem

9、 has received considerable attention in the past, as many applications need to know where objects or persons are, and hence various location services have been created. Undoubtedly, the Global Positioning System （GPS） is the most well-known location service in use today. The approach taken by GPS, h

10、owever, is unsuitable for low-cost, ad-hoc sensor networks since GPS isbasedonextensiveinfrastructure（i.e.,satellites）.Likewisesolutions developed in the area of robotic and ubiquitous computing are generally not applicable for sensor networks as they require too much processing power and energy.Rec

11、ently a number of localization systems have been proposed specifically for sensor networks. We are interested in truly distributed algorithms that can be employed on large-scale ad-hoc sensor networks （100+ nodes）. Such algorithms should be:self-organizing （i.e., do not depend on global infrastructu

12、re）,robust （i.e., be tolerant to node failures and range errors）,energy efficient （i.e., require little computation and, especially, communication）.These requirements immediately rule out some of the proposed localization algorithms for sensor networks. We carried out a thorough sensitivity analysis

13、 on three algorithms that do meet the above requirements to determine how well they perform under various conditions. In particular, we studied the impact of the following parameters: range errors, connectivity（density）, and anchor fraction. These algorithms differ in their position accuracy, networ

14、k coverage, induced network traffic, and processor load. Given the （slightly） different design objectives for the three algorithms, it is no surprise that each algorithm outperforms the others under a specific set of conditions. Under each condition, however, even the best algorithm leaves much room

15、 for improving accuracy and/or increasing coverage.The main contributions of our work described in this paper are:we identify a common, three-phase, structure in the distributed localization3algorithms.we identify a generic optimization applicable to all algorithms.we provide a detailed comparison o

16、n a single （simulation） platform.we show that there is no algorithm that performs best, and that there exists room for improvement in most cases.Section 2 discusses the selection, generic structure, and operation of three distributed localization algorithms for large-scale ad-hoc sensor networks. These algorithms are compared on a simulation platform, which is