design automation lab. / snu sensor network 1 2002. 4. 23 design automation lab. jung, jinyong

Design Automation Lab. / SNU

Sensor Network 1

2002. 4. 23

Design Automation Lab.

Jung, Jinyong

2Design Automation Lab. / SNU

Contents

m-Links Navigation model for very small internet devices

Exposure Formulation of coverage problem in sensor networks

Design Automation Lab. / SNU

m-Links: An Infrastructure for Very Small Internet Devices

MOBICOM 2001

Bill N. Schilit, Jonathan Trevor,

David M. Dilbert, Tzu Khiau Koh

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Introduction

Mobile Link (m-Links) infrastructure Utilizing existing WWW contents and services on very

small devices

Approaches to Device-independent Access Device-specific authoring Multiple-device authoring Client-side navigation Automatic re-authoring

• Digestor

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Introduction

Navigation model “browsing” = navigation + use

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Design Goals

Web navigation Culling the links from the content

Get a useful bits of information Data detector

Maximize program/data composibility Link’s MIME type

Open Extensibility Re-use existing web-based services

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A Small-device Navigation Model

Navigation model “dig and go” model

Issues Determining sensible labels for Web links Context of a link Dealing with “link overload” Data detect Open system design

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A Small-device Navigation Model

Context of a link

Link “overload”

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Data Flow

m-Links is like Search engine Caching or transducing proxy

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M-Links Architecture

Link Engine Service Manager UI Generator

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Link Engine

Processing flow1) The document is loaded from internet.

2) HTML parser creates a parse tree.

3) Text elements are scanned by data detectors and new links are created.

4) The links are categorized

5) Each link is added to the page’s link collection.

6) Link collection data structure is stored in a cache.

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Link Engine

Link extraction and naming Link extraction

• Explicit: <A>, <AREA>

• Data detected Link naming algorithm

• Concise and meaningful text label for the link

• Quality value• Title > anchor text, alt-text, .. > URL

• Check the uniqueness of the label

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Link Engine

Link categorization Off-site Navigation Based on MIME type Based on layout characteristics

Link cache Caching Web pages processed Similar manner to those used by search engines

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Service Manger

Returning the subset of services appropriate for a link and user

General service, Content provider service Check

• MIME type, characteristics of device, user’s indentity Submit HTTP request to the appropriate web server.

Defining and extending services Service specification document

• XML-based

• Rule section, execution section, presentation section

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User Interface Generator

Supporting a variety of different UI HDML and WML for web-phones HTML for palm-size PDA

Template markup files Generates the variable values

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Services

Reading Extracts content from a type of file and presents it in a

device-specific manner.

Sending Email, WAP-alert service

Printing Printing, fax service

Mapping Yahoo on-line mapping service

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Implementation and Experience

Implementation of the m-Links Java servlet engine Microsoft’s IIS web server

Problem Web pages contain client-side scripts Not severe

• Authors provide “hidden” or extra links for non-script browsers

• Many sites provide alternative pages

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Conclusions

Propose the navigation model for very small devices m-Links system addresses design goal:

Supporting web navigation Getting useful bits of information Maximizing program-data composibility through a

separation of service from link Providing open framework

Design Automation Lab. / SNU

Exposure In Wireless Ad-Hoc Sensor Networks

MOBICOM 2001

Seapahn Meguerdichian, Frinaz Koushanfar,

Gang Qu, Miodrag Potkonjak

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Introduction

Calculation of coverage is fundamental problems in sensor networks

Coverage problems Art Gallery Problem Sensor coverage for detecting ocean color Coverage studies to maintain connectivity formulation of coverage

• Maximal breach, maximal support path

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Introduction

Exposure A formulation of coverage in sensor network Expected average ability of observing a target in the

sensor field. An integral of a sensing function that generally depends

on distance from sensors on a path from a starting point path pS to destination point pD.

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Technical Preliminaries

Sensor models Sensing ability diminishes as distance increase. Sensing ability can improve as the exposure increase.

S : sensing model, s : sensor d(s,p) : Euclidean distance bet’n the sensor s and the

point p

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Technical Preliminaries

Sensor field intensity and exposure All-sensor field intensity IA(F,p)

Closest-sensor field intensity IC(F,p)

Exposure during [t1,t2] along the path p(t)

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Exposure

Simple case pS = p(1,0)

Lemma 1

q(0,1)

p(1,0)

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Exposure

Theorem 3

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Exposure

Corollary 4

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Exposure

Corollary 5

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Generic Approach for Calculating Minimal Exposure Path

Finding the exposure path under arbitrary sensor and intensity models is an extremely difficult.

Divide sensor network region n x n, m-th-order

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Generic Approach for Calculating Minimal Exposure Path

Finding minimal exposure path

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Experimental Results

Simulation platform Sensor field is defined as a square, 1000m wide. Assume constant speed

Uniformly distributed random sensor deployment n=32, m=8 1/d2 (K=2), 1/d4 (K=4) model IA, IC intensity models Data for 50 cases

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Experimental Results

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Experimental Results

Relative standard deviation

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Experimental Results

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Experimental Results

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Conclusion

Calculation of exposure is one of fundamental problem in wireless ad-hoc sensor networks

Introduced the exposure-based coverage model Presented efficient algorithm for minimal exposure

paths Performance and worst-case coverage analysis tool

in sensor networks