自動化英文翻譯.doc

畢業(yè)設(shè)計（論文）英文翻譯 成績： 西安建筑科技大學(xué)華清學(xué)院畢業(yè)設(shè)計 (論文)英文翻譯院 （系）： 機械電子工程系 專業(yè)班級： 自動化0702 畢 業(yè) 設(shè) 計論 文 方 向 ： 單片機 翻 譯 文 章 題 目 ：基于網(wǎng)絡(luò)共享的無線傳感網(wǎng)絡(luò)設(shè)計學(xué)生姓名： 程龍娜 學(xué) 號： 0706010237 指導(dǎo)教師： 趙敏華 2011年 4月 11日基于網(wǎng)絡(luò)共享的無線傳感網(wǎng)絡(luò)設(shè)計摘要：無線傳感器網(wǎng)絡(luò)是近年來的一種新興發(fā)展技術(shù)，它在環(huán)境監(jiān)測、農(nóng)業(yè)和公眾健康等方面有著廣泛的應(yīng)用。在發(fā)展中國家，無線傳感器網(wǎng)絡(luò)技術(shù)是一種常用的技術(shù)模型。由于無線傳感網(wǎng)絡(luò)的在線監(jiān)測和高效率的網(wǎng)絡(luò)傳送，使其具有很大的發(fā)展前景，然而無線傳感網(wǎng)絡(luò)的發(fā)展仍然面臨著很大的挑戰(zhàn)。其主要挑戰(zhàn)包括傳感器的可攜性、快速性。我們首先討論了傳感器網(wǎng)絡(luò)的可行性然后描述在解決各種技術(shù)性挑戰(zhàn)時傳感器應(yīng)產(chǎn)生的便攜性。我們還討論了關(guān)于孟加拉國和加利尼亞州基于無線傳感網(wǎng)絡(luò)的水質(zhì)的開發(fā)和監(jiān)測。關(guān)鍵詞：無線傳感網(wǎng)絡(luò)、在線監(jiān)測1.簡介無線傳感器網(wǎng)絡(luò)，是計算機設(shè)備和傳感器之間的橋梁，在公共衛(wèi)生、環(huán)境和農(nóng)業(yè)等領(lǐng)域發(fā)揮著巨大的作用。一個單一的設(shè)備應(yīng)該有一個處理器，一個無線電和多個傳感器。當這些設(shè)備在一個領(lǐng)域部署時，傳感裝置測量這一領(lǐng)域的特殊環(huán)境。然后將監(jiān)測到的數(shù)據(jù)通過無線電進行傳輸，再由計算機進行數(shù)據(jù)分析。這樣，無線傳感器網(wǎng)絡(luò)可以對環(huán)境中各種變化進行詳細的觀察。無線傳感器網(wǎng)絡(luò)是能夠測量各種現(xiàn)象如在水中的污染物含量，水灌溉流量。比如，最近發(fā)生的污染涌流進中國松花江，而松花江又是飲用水的主要來源。通過測定水流量和速度，通過傳感器對江水進行實時監(jiān)測，就能夠確定污染桶的數(shù)量和流動方向。不幸的是，人們只是在資源相對豐富這個條件下做文章，無線傳感器網(wǎng)絡(luò)的潛力在很大程度上仍未開發(fā)，費用對無線傳感器網(wǎng)絡(luò)是幾個主要障礙之一，阻止了其更廣闊的發(fā)展前景。許多無線傳感器網(wǎng)絡(luò)組件正在趨于便宜化（例如有關(guān)計算能力的組件），而傳感器本身仍是最昂貴的。正如在在文獻5中所指出的，成功的技術(shù)依賴于共享技術(shù)的原因是個人設(shè)備的大量花費。然而，大多數(shù)傳感器網(wǎng)絡(luò)研究是基于一個單一的擁有長期部署的用戶，模式不利于分享。該技術(shù)管理的復(fù)雜性是另一個障礙。 大多數(shù)傳感器的應(yīng)用，有利于這樣的共享模型。我們立足本聲明認為傳感器可能不需要在一個長時間單一位置的原因包括：（1）一些現(xiàn)象可能出現(xiàn)變化速度緩慢，因此小批量傳感器可進行可移動部署，通過測量信號，充分捕捉物理現(xiàn)象（2）可能是過于密集，因此多余的傳感器可被刪除。（3）部署時間短。我們將會在第三節(jié)更詳細的討論。上述所有假定的有關(guān)傳感器都可以進行部署和再部署。然而有很多的無線傳感器網(wǎng)絡(luò)由于其實時監(jiān)測和快速的網(wǎng)絡(luò)功能可能被利用作為共享資源。其作為共同部署資源要求，需要一些高效的技術(shù)，包括對傳感器的一些挑戰(zhàn)，如便攜性，流動頻繁的傳感器內(nèi)的部署，這使我們在第四節(jié)將會有大的挑戰(zhàn)。在本文中，我們專注于作為共享的可行性設(shè)計的傳感器網(wǎng)絡(luò)。下面我們開始闡述傳感網(wǎng)絡(luò)在孟加拉國和加利福尼亞州的水質(zhì)檢測中的應(yīng)用。2無線傳感網(wǎng)絡(luò)在水質(zhì)監(jiān)測中的應(yīng)用無線傳感器網(wǎng)絡(luò)是通過把小型計算機設(shè)備連接到各式傳感器和無線電而組成的。這些設(shè)備自適應(yīng)的形成特殊網(wǎng)絡(luò)（暫時的點對點網(wǎng)絡(luò)），通過無線方式對所處環(huán)境進行監(jiān)測、處理。其硬件和軟件的設(shè)計非常低功耗以此達到長期在現(xiàn)場部署的目的，即此種部署在所處環(huán)境中人為干預(yù)性小。設(shè)備大小通常從四分之一個個人數(shù)據(jù)處理機到類似一個個人數(shù)據(jù)處理機的裝置那么大。在一般情況下，資源可用性和功耗與設(shè)備大小是相一致的。例如，雖然資源可用性在很大程度上取決于傳感器的功耗，但是低功率節(jié)點（通常稱為微塵）用兩節(jié)AA電池可以運行大約一二個月。傳感器網(wǎng)絡(luò)提供密集的空間和時間上的采樣。此種取樣即使是在偏遠和難以到達的地方均可采樣。因此，它是對于在時間上和空間上要求精確采集最適用的網(wǎng)絡(luò)技術(shù)。例如無線傳感網(wǎng)絡(luò)在土壤中的應(yīng)用就是個很好的例子。因為土壤環(huán)境在空間上是多樣性的，需要精確的時間上的采樣。對于突然發(fā)生的變化都會被精確的采樣及時記錄下來。事實上，無線傳感器網(wǎng)絡(luò)是一種低功耗的網(wǎng)絡(luò)技術(shù)，對于一些發(fā)達地區(qū)其作為一種新興技術(shù)適用性更為廣泛。此外，對于公共健康方面的應(yīng)用極為重要。例如，參考文獻（17）闡述了人們對于水質(zhì)的極高的關(guān)注度，“對水質(zhì)的分析起初仍然是通過實驗采樣的辦法將采集到的樣本帶回實驗室進行研究。”這種類型的數(shù)據(jù)收集和分析通常是非常耗時的且大多是不準確的，并在許多情況下，錯過了人們對于及時關(guān)注的焦點的分析。我們參與了兩項正在進行的關(guān)于地下水質(zhì)監(jiān)測的無線傳感網(wǎng)絡(luò)部署：一項系統(tǒng)是以了解孟加拉國地下水中砷的含量為主。另一項系統(tǒng)是通過研究孟加拉國地下水和土壤來監(jiān)測硝酸鹽的傳播。以上我們的部署都具有類似的設(shè)置。一個塔架，是由外圍箱體式的無線設(shè)備組成，這些設(shè)備在土壤中通過長導(dǎo)線連接到嵌入式傳感器。每個設(shè)備可以支持7個傳感器，每個塔架都有多個設(shè)備。多路塔架被部署在目的地周圍，以達到空間上垂直和水平的密集部署。這些設(shè)備將采集到的樣本以無線方式傳送給基站以供分析。該部署的基站是一個個人數(shù)據(jù)處理機類的設(shè)備，也可以是一種輕便電腦。它是通過由太陽能提供再充電的汽車電池來進行供電。為了能夠獲得外部數(shù)據(jù)，我們的基站使用Zigbee技術(shù)，或在Zigbee不可用時，使用GPRS網(wǎng)絡(luò)。在孟加拉國，在恒河三角洲的幾千萬人飲用了已被砷嚴重污染的地下水，如果被污染的水量一直持續(xù)，由砷引起的患病率和皮膚癌將大約每年分別增加兩百萬和一萬例，由砷引起的癌癥的死亡率每年將會大約增加三千例。我們對于控制砷在地下水中的動態(tài)變化是難以完全了解的。在與孟加拉國的工程技術(shù)大學(xué)和麻省理工學(xué)院進行合作中，我們于2006年1月在靠近達卡的一個水稻地里部署了一個傳感網(wǎng)絡(luò)，目的是為了幫助確認這個假說成立。一個完整的塔架應(yīng)該包含3部分完整的傳感器（土壤濕度，溫度，碳酸鹽，鈣，硝酸，氯，氧化還原電位，氨氮，pH值），每個部署都具有不同的深度（在地面以下1，1.5，2米），在此基礎(chǔ)上的壓力傳感器用來監(jiān)測水的深度。在干旱地區(qū)和半干旱地區(qū)水的短缺和不斷增加的對于水資源的消耗已經(jīng)促進人們重新再利用被處理過的廢水。盡管對于水資源的再利用人類收獲了很多益處，但是已被處理的廢水對于人類的健康和環(huán)境質(zhì)量仍然存在著顯而易見的危害。解決這些危害需要進行自動的分布式的觀測和控制灌溉水量，查出它所傳輸?shù)奈廴疚?，包括暫停處理的或是還未處理的污染物，膠狀污染物，藥物，有機碳，揮發(fā)性有機化合物，治病微生物，營養(yǎng)素例如氮或磷。在加利福尼亞的帕姆代爾，一個水質(zhì)再利用現(xiàn)場是為測試土壤濕度，溫度和硝酸鹽的傳感器網(wǎng)絡(luò)而被用作的試車臺。此網(wǎng)絡(luò)集合了兩個方面：第一，確保此環(huán)境正在被監(jiān)測，第二，提供對水質(zhì)控制的反饋，從而達到優(yōu)化水流量和減少化學(xué)物質(zhì)滲透到地下。這種現(xiàn)場也可以被用來在對孟加拉國進行部署前對軟件，傳感器和硬件的測試。3傳感器共享技術(shù)對于傳感器網(wǎng)絡(luò)數(shù)據(jù)收集，即使是最小的傳感器資源，其共享也將讓許多人受益。我們相信以下三種技術(shù)方法特別適用于傳感器共享：（1）從一系列小型傳感器大范圍部署到精確仿真。（2）從密集部署到稀疏部署逐漸移動冗余傳感器（3）在一些可能的地區(qū)縮短部署周期。在這里，我們更詳細地描述這些場景，包括我們自己和別人在執(zhí)行有關(guān)的或支持的算法時的工作的調(diào)查。(1)精確仿真人類功能的移動性就是通過手動來模擬一個使用較少傳感器的密集部署區(qū)。人們可以移動一個領(lǐng)域的一小套傳感器，對密集空間收集數(shù)據(jù)。該技術(shù)將是只適合于可持續(xù)發(fā)展應(yīng)用中，所關(guān)注的現(xiàn)象變化非常緩慢。(2)密集到稀疏部署一些傳感器網(wǎng)絡(luò)應(yīng)用需要一個密集映射的環(huán)境。一旦傳感器密集部署和細節(jié)的現(xiàn)象揭示，我們可以看到它可以捕獲足夠的資料較少的傳感器，從而釋放傳感器部署在其他地方。這里，我們描述適用的工作是正在進行中的傳感器網(wǎng)絡(luò)社區(qū)。(3)部署周期短有些應(yīng)用程序只需要短時間部署，因而對傳感器的共享是種理想選擇。我們在孟加拉的部署是一個帶有部署周期短的應(yīng)用例子。我們要收集數(shù)據(jù)，以驗證有關(guān)晝夜變化的假設(shè)，所以我們希望數(shù)天時間來對數(shù)據(jù)進行分析。4挑戰(zhàn)許多挑戰(zhàn)性技術(shù)的出現(xiàn)，是為了能夠快速部署和移動傳感器，主要因為迄今為止的工作主要集中在靜態(tài)的，長期運行的部署中。我們已經(jīng)有了趨于密集化的目標，降低高密度部署使之稀疏，使周期短的部署趨于平衡，我們發(fā)現(xiàn)以下三個挑戰(zhàn)是最恰當?shù)?。算法必須是具有人機通信功能的，對于人為錯誤是可以解決的。對于系統(tǒng)故障必須迅速查明，并最大限度地通過正確的數(shù)據(jù)進行接收。最后，系統(tǒng)必須迅速做出部署。5結(jié)論 無線傳感器網(wǎng)絡(luò)可視為一種工具，其對于可持續(xù)發(fā)展來說具有很好的潛力。如果我們視這種發(fā)展的無線傳感網(wǎng)絡(luò)技術(shù)為共享資源的話，它就可以得到技術(shù)社區(qū)的幫助。為了使無線傳感器網(wǎng)絡(luò)作為一種共享資源得到落實，我們確定了三個有希望的技術(shù)方法：精確仿真，從密集部署到稀疏部署，實施短周期部署。我們討論了我們的工作部署，這些部署已證明了這些技術(shù)，描述了我們的過去和現(xiàn)在需要做哪些工作去面對即將出現(xiàn)的重大挑戰(zhàn)。Designing Wireless Sensor Networks as a Shared Resourcefor Sustainable DevelopmentAbstract ：Wireless sensor networks (WSNs) are a relatively new and rapidly developing technology; they have a wide range of applications including environmental monitoring, agriculture, and public health. Shared technology is a common usa ge model for technology adoption in developing countries. WSNs have great potential to be utilized as a shared resource due to their on-board processing and ad-hoc networking capabilities, however their deployment as a shared resource requires that the technical community rst address several challenges. The main challenges include enabling sensor portability the frequent movement of sensors within and between deployments, and rapidly deployable systems systems that are quick and simple to deploy.We rst discuss the feasibility of using sensor net-works as a shared resource, and then describe our research in addressing the various technical challenges that arise in enabling such senso rportability and rapid deployment. We also outline our experiences in developing and deploying water quality monitoring wireless sensor networks in Bangladesh and California.Key words: WSNs、on-board processing1 IntroductionWireless Sensor Networks (WSNs), networks of wirelessly connected sensing and computational devices, hold tremendous promise for many areas of development including public health,the environment, and agriculture. A single device has a processor, a radio, and several sensors. When a network of these devices is deployed in a eld, the sensing devices measure particular aspects of the environment. The devices then communicate those measurements by radio to one another and to more powerful computers for data analysis. In this way, WSNs can provide detailed observations of various phenomena that occur in the environment.WSNs are capable of measuring diverse phenomena such as contaminant levels in water, pollutants in the air, and the ow of water for irrigation. As an example of a potential application, consider the recent incident of contamination spilling into the Songhua river in China, the main source of drinking water for many people1. Determining rate of ow and sometimes direction of the river requires coordination of multiple sampling points. Sensors periodically taking samples at multiple locations along the river could determine the rate, quantity, and direction of contaminant ow using the distributed sensing and processing of a wireless sensor network.Unfortunately, the potential of wireless sensor net-works for sustainable development2 remains largely untapped while they are designed primarily for relatively resource-rich application contexts. The cost of WSNs is one of several major barriers that prevents them from being leveraged for sustainable development applications. Many components of WSNs are becoming cheaper (e.g. computing power), but the sensors themselves remain the most expensive component3. As stated in 5, successful technology-based international development projects rely on shared technology due to excessive cost of personal devices. However, most research on sensor networks is based on long-term deployments owned by a single user, a paradigm not conducive for sharing. The complexity of technology management is another barrier. We use Grameen telecom as a successful model 4 in which the management and maintenance of shared hardware is centralized. We envision a sensor network much in the same light.Many sensor network applications are conducive to such a shared model. We base this statement on the observation that sensors may not be required in a single location for extended periods of time for reasons including: (1) a phenomenon of interest may have a slow rate of change, thus a small number of sensors can be moved within a deployment, emulating the density required to suciently capture the physical phenomena, (2) the initial deployment may have been too dense, thus redundant sensors can be removed, and (3) the duration of the deployment may be short. We discuss these scenarios in more detail in Section 3.All of the deployment scenarios mentioned above rest on the assumption that sensors can be easily deployed and re-deployed. While WSNs have great potential to be utilized as a shared resource due to their on-board processing and ad-hoc networking capabilities, their deployment as a shared resource requires that the technical community rst address several challenges, including enabling sensor portability the frequent movement of sensors within and between deployments, and rapidly deployable systems systems that are quick and simple to deploy. This leads us to our major challenges in Section 4.Clearly, the primary issues related to successful technology adoption are the social, policy, and logistical questions to be answered in order to enable equitable access and the design of culturally appropriate technology. Our experience, though relevant, is limited to our technical expertise. These challenges and others should be formulated more explicitly with the necessary diverse input from communities, activists, governments and NGOs. In this paper we focus on justifying the technical feasibility of designing sensor networks as a shared technology (Section 3) and describing the technical challenges that must be addressed to enable WSNs as a shared technology (Section 4). We begin by describing our applications in water quality monitoring in Bangladesh and California (Section 2).2 WSNs For Water QualityWireless sensor networks are made up of small computational devices connected to various sensors and wireless radios. The devices automatically and adaptively form ad-hoc networks (temporary point-to-point networks) over wireless radios to make decisions based on measurements of their environment. The hardware and software are designed to be extremely low power in order to enable long-term in-situ deployments, i.e. undisturbed deployments that are left in the environment with minimal human intervention. Device sizes commonly range from that of a quarter to a PDA-like device. In general, resource availability and power consumption are commensurate with size. For example, while it largely depends on the power consumption of the sensors, the lower-power nodes (often called motes) can run for approximately one month on 2 AA batteries.Sensor networks provide dense spatial and temporal sampling even in remote and hard to reach locations. Thus, they are best applied to applications that need dense sampling in space and/or time. Soi applications are a good example, because the soi environment is heterogeneous across space, requiring dense spatial sampling. Abrupt changes can then be captured with a high temporal sampling rate.The fact that WSNs are low power and wireless makes them appealing as a technology for developing regions, but in addition the dense sampling is crucial for public health applications. For example, 17 states that while water quality concerns can be extremely critical, “analysis is still primarily conducted in a laborious manner by physical collection of a sample that is analyzed back in a laboratory.” This kind of data collection and analysis is time consuming and mostly undirected, and in many instances misses the toxin events of interest.We are involved with two ongoing WSN deployments related to groundwater quality: a system to understand the prevalence of arsenic in Bangladesh groundwater, and a system to monitor nitrate propagation through soils and ground water in California.Both of our deployments have a similar setup. A pylon 10 (Figure 2) consists of an enclosure housing the small wireless devices which connect to groups of sensors embedded at multiple depths in the soil through long wires. Each device can support 7 sensors and there are multiple devices per pylon. Multiple pylons are deployed around the eld to attain vertical and horizontal spatial density. The devices wirelessly transmit samples back to a base-station for analysis (Figure 1). The base-station in these deployments was a PDA-class device. It could also be a laptop. It is powered by a car-battery recharged using solar panels. To make data externally accessible, our base-station is connected using Zigbee or where Zigbee is unavailable, using a GPRS (i.e. cellular) network.In Bangladesh, tens of millions of people in the Ganges Delta drink ground water that is dangerously contaminated with arsenic. If consumption of contaminated water continues, the prevalence of arsenicosis and skin cancer will be approximately 2,000,000 and 100,000 cases per year, respectively, and the incidence of death from cancer induced by arsenic will be approximately 3,000 cases per year 18.A full understanding of the factors controlling arsenic mobilization to ground water is lacking. In a joint collaboration with scientists at the Bangladesh University of Engineering and Technology and MIT, we deployed a sensor network in January of 2006 in a rice eld near Dhaka,Bangladesh in order to aid in validating this hypothesis. A full pylon contains 3 complete suites of sensors (soil moisture, temperature, carbonate, calcium, nitrate, chloride, oxidation-reduction potential, ammonium, and pH), each deployed at a dierent depth (1, 1.5, and 2 meters below ground), and a pressure transducer at the base to monitor water depth. Water scarcity in arid and semi-arid regions and increasing demand on water supplies has stimulated interest in the reuse of treated wastewater. Despite the many benets to irrigating with reclaimed water, there remain both real and perceived risks to human health and environmental quality stemming from residuals in the treated wastewater. Proactively addressing these risks requires automating the distributed observation and control of the irrigation water and the trace pollutants that it conveys, including suspended or dissolved solids (TDS), colloidal solids, pharmaceuticals, organic carbon, volatile organic compounds, pathogenic microorganisms, and nutrients such as nitrogen or phosphorus. A water reuse site in Palmdale, California is being used as a testbed for a sensor network with soil moisture, temperature, and nitrate sensors. The network focuses on two things: rst, ensuring that environmental regulations are being met, and second, providing feedback to a water control system in order to optimize water ow and minimize chemical penetration into the subsurface. This site is also used to test the software, sensors, and hardware before deploying in Bangladesh.3 Sensor Sharing TechniquesSensor sharing will allow many people to benet from sensor network data collection, even with minimal sensor resources. We believe the following three technical approaches are particularly suited for enabling sensor sharing for sustainable development:(1) moving a smaller number of sensors around in a deployment to emulate density, (2) gradually removing redundant sensors from a deployment to go from dense to sparse deployments, and (3) leveraging shorter deployment cycles where possible. Here we describe each of these scenarios in greater detail, including a survey of our own and others work in implementing related or supporting algorithms.（1）Emulating DensityHuman-enabled mobility can be used to manually emulate the eect of a dense deployment using fewer sensors. People can move a small set of sensors around in a eld in order to collect data for a dense spatial map of the eld. This technique will be appropriate only for sustainable development applications in which the phenomenon of interest changes very slowly, on the order of days or longer.（2） Dense to Sparse DeploymentsSome sensor network applications require a dense mapping of the environment. Once sensors are densely deployed and details of the phenomenon are revealed, we may see it is possible to capture sucient information with fewer sensors, freeing sensors for deployment elsewhere. Here we describe applicable work which is ongoing in the sensor network community.（3） Short Deployment CyclesSome applications only require short-duration deployments and therefore are ideal for sensor sharing. Our deployment in Bangladesh is an example of an application with a short deployment cycle. We wanted to collect data to validate a hypothesis about diurnal variations, and so we wanted several days of data for analysis.4 ChallengesNumerous technical challenges arise in order to be able to quickly deploy and move sensors, primarily because the work to date has largely focused on static, long-running deployments.Given that we have the goals to emulate density, reduce dense deployments to sparse ones, and leverage short deployments cycles, we nd the following three challenges to be the most pertinent. Algorithms must be interactive and robust to human error. Faults in the system must be quickly identied to maximize the amount of good data received.Finally, systems must be made to be rapidly deployable. 5 ConclusionWireless sensor networks have the potential to be a useful tool for sustainable development. This can be facilitated by the technical community if we focus on issues with developing wireless sensor net-works as a shared technology. In order to implement WSNs as a shared resource, we identied three promising technical approaches: emulating density, moving from dense to sparse deployments, and implementing short deployment cycles. We discussed our work on deployments that have demonstrated these techniques and described our past and ongoing work to address the major challenges which arise.17References1 The General Assembly. 2005 World Outcome Document ref: Resolution adopted by the General Assembly 60/1. 2005 World Summit Outcome. United Nations, October 2005.2 M. Batalin, W. Kaiser, R. Pon, G. S. Sukhatme, G. Pottie, Y. Yu, J. Gord