自动化英文翻译

该技术将是只适合于可持

续发展应用中，所关注的现象变化非常缓慢。< /p>

(2)

密集到稀疏部署

一些传感器网络应用需要一个密集映射的环境。

一旦传感器密集部署和细节的 现

象揭示，

我们可以看到它可以捕获足够的资料较少的传感器，

从而释放传感器部署在

其他地方。这里，我们描述适用的工作是 正在进行中的传感器网络社区。

(3)

部署周期短

< br>有些应用程序只需要短时间部署，

因而对传感器的共享是种理想选择。

加拉的部署是一个带有部署周期短的应用例子。

< br>我们要收集数据，

以验证有关昼夜变

化的假设，所以我们 希望数天时间来对数据进行分析。

4

．挑战

许 多挑战性技术的出现，

是为了能够快速部署和移动传感器，

主要 因为迄今为止

的工作主要集中在静态的，长期运行的部署中。

我们已经有了趋于密集化的目标，

降低高密度部署使之稀疏，< /p>

使周期短的部署趋

于平衡，

我们发现以下 三个挑战是最恰当的。

算法必须是具有人机通信功能的，

对于< /p>

人为错误是可以解决的。

对于系统故障必须迅速查明，

进行接收。最后，系统必须迅速做出部署。< /p>

5

．结论

5

毕业设计（论文）英文翻译

无线传感 器网络可视为一种工具，

其对于可持续发展来说具有很好的潜力。

如果

我们视这种发展的无线传感网络技术为共享资源的话，它就可以得到技术社区的帮

助。

为了使无线传感器网络作为一种共享资源得到落实，

我们确定了三个有希望的技

术方法：

精确仿真 ，

从密集部署到稀疏部署，

实施短周期部署。

< br>我们讨论了我们的工

作部署，

这些部署已证明了这些技术 ，

描述了我们的过去和现在需要做哪些工作去面

对即将出现的重 大挑战。

6

毕业设计（论文）英文翻译

Designing Wireless Sensor Networks as a

Shared Resource

for Sustainable Development

Abstract

：

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 ?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 processing

1 Introduction

Wireless 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

7

毕业设计（论文）英文翻译

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

8