WoTSF: A Framework

for Searching in the Web of

Things

M. Younan, S. Khattab, and R. Bahgat

May 11th 2016

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

F: A

Fra

mew

ork

fo

r Se

arch

ing

in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

tern

atio

nal

Co

nfe

ren

ce o

n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

1 • Introduction

2 • Related Work

3 • The Architecture of the WoTSF

4 • The Implementation of the WoTSF

5 • Experimental Evaluation

6 • Conclusion and Future Work

Agenda M

. Yo

un

an, S

. Kh

atta

b, a

nd

R. B

ahga

t, "

Wo

TSF:

A F

ram

ewo

rk f

or

Sear

chin

g in

th

e W

eb

of

Thin

gs,"

in IN

FOS

20

16

: Th

e 1

0th

Inte

rnat

ion

al C

on

fere

nce

on

Info

rmat

ics

and

Sys

tem

s,

AC

M, C

airo

, Eg

ypt,

May

, 20

16

.

INTRODUCTION

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

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Fra

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ork

fo

r Se

arch

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f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

tern

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nal

Co

nfe

ren

ce o

n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

Introduction (WSN -> WoT)

• Wireless Sensor Network (WSN)

• Daily life integration of embedded devices – Convert things to Smart Things (SThs)

– No.of devices reaches order of billions in 2020.

– No.of users < no.of devices.

• The Internet of Things (IoT). – Huge Sensory Data (data stream).

• The Web of Things (WoT). – Current web tools and services.

• Contribution Idea: – Searching in the WoT increases its popularity

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

F: A

Fra

mew

ork

fo

r Se

arch

ing

in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

tern

atio

nal

Co

nfe

ren

ce o

n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

Introduction

• Features of the WoT (Searching)

– Different formats.

– Non-standardized naming

– Huge and dynamic Sensory Data.

– Daily life integration (normal user)

• Simple query language

• Real time queries

• Interested in high level knowledge (summary)

• Main Points:

– Crawling

• LWoTSEs’ Data –> following features of the WoT dataset presented in [1][2].

– Indexing

• WoTSF: a Framework for searching in the WoT (High level indices)

Crawling

Indexing and Searching

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

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Fra

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in t

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f Th

ings

," in

INFO

S 2

01

6 :

The

10

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form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

RELATED WORK

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

F: A

Fra

mew

ork

fo

r Se

arch

ing

in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

tern

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Co

nfe

ren

ce o

n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

Related Work (Selection)

Traditional Search engines

o Google Optimizations [3]

o AJAX Crawler [4]

DiscoWoT (Mayer and Dominque. 2011)[5].

Shodan SE (www. Shodanqh.com,2015)[6] .

Dyser SE (Ostermaier et al.- 2010)[7].

Zhang et al. (2015) present a framework for a

distributed range-query search[8]

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

F: A

Fra

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ork

fo

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arch

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in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

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Co

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ren

ce o

n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

Dyser

• Dyser uses periodic patterns for each sensor (L,O,W,P), where L: period length O: offset W: sensor output P: probability value

E.g., (7-Days, 2, empty, 0.5)

• Expansion of such periodic pattern is (K*L +O)

Su Mo Tu We Th Fr Sa

17 18 19 20 21 22 23

24 25 26 27 28 29 30

For Example: If crawling process starts in 20-4, then Index record: (Occ., ID_01, 25-4-2016, empty, 0.5)

# recorded patterns in Dyser index will be >= # SThs

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

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Fra

mew

ork

fo

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arch

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in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

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Co

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ren

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n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

Dyser Index-> WoTSF Index

S01: (7-Days, 1, empty, 0.8)

S02: (7-Days, 1, empty, 0.8)

S03: (7-Days, 2, empty, 0.5)

S04: (7-Days, 2, empty, 0.9)

S05: (7-Days, 2, empty, 0.6)

S06: (7-Days, 3, empty, 0.7)

S07: (7-Days, 3, empty, 0.2)

S08: (7-Days, 3, empty, 0.4)

S09: (7-Days, 3, empty, 0.9)

S10: (7-Days, 4, empty, 0.3)

S11: (7-Days, 5, empty, 0.8)

S12: (7-Days, 6, empty, 0.6)

S13: (7-Days, 7, empty, 0.5)

S14: (7-Days, 7, empty, 0.7)

WoT01: (7-Days, 1, empty, 0.8, S01)

WoT01: (7-Days, 1, empty, 0.8, S02)

WoT01: (7-Days, 2, empty, 0.9, S04)

WoT01: (7-Days, 3, empty, 0.9, S09)

WoT01: (7-Days, 4, empty, 0.3, S10)

WoT01: (7-Days, 5, empty, 0.8, S11)

WoT01: (7-Days, 6, empty, 0.6, S12)

WoT01: (7-Days, 7, empty, 0.7, S14)

Using aggregation function: ‘Max.’

1

2

3

4

5

6

7

WoTSF: High Level Index

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

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Fra

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S 2

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s an

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A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

THE PROPOSED WOTSF ARCHITECTURE

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

ro ,

Egyp

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ay, 2

01

6.

The WoTSF Architecture

Query life cycle of the WoTSF

Crawling (WoT)

Google Opt. (server-root file)

Save time:

crawl less no.of pages

parse less no. of pages

(Union format)

(High Level)

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

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CM

, Cai

ro ,

Egyp

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ay, 2

01

6.

The WoTSF Architecture (Query Processing)

Query

q2 WoT_1

WoT_1 M.Ds

WoT_2 M.Ds

WoT_3 M.Ds

DS_1

Ind.

DS_2

Ind.

DS_3

Ind.

•Select WoTSEs APIs

•Send sub-queries

Key: sensor type

b

c

d

… …

a

q2

Master Indices

•Generate sub-queries

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

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Egyp

t, M

ay, 2

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6.

The WoTSF Architecture (Index Structure)

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

The WoTSF Architecture (Index Structure)

mi mi MI

SI SI SI

D D D D D

S

WWW WWW

WWW

A R S A

R

SThs-Level (individual WoTSEs)

WoT-Level (WoTSF)

Master Indices

Secondary Indices

Storage

Dynamic Pages

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

The WoTSF Implementation (Ranking)

• Sensor State probability

𝑆𝑆 𝑖 = 𝐾 ∗ 𝐶𝑆 𝑖 + 1 − 𝐾 𝑃𝑖

K-> constant (0:1), CS-> current state, P->Probability

• Entity State probability

𝐸𝑆 𝑖 = 1

𝑛 𝑆𝑆 𝑗𝑛𝑗=1

N-> number of sensors

𝐸𝑆(𝑖) = 𝐷(𝑗) ∗ 𝑆𝑆(𝑗)𝑛𝑗=1

D(j) -> impact factor of sensor j on ES(i)

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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s an

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A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

THE WOTSF IMPLEMENTATION

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

The WoTSF Implementation (Crawling)

(b) Gateway

Start

Receive new_value

Update prediction model (Sr)

no.of. consecutivechanges >

M

Calculate Entity State

SrVal_Stability (Sr,new_value) = (cur_rec_time - last_rec_time(Sr))/interval

no.of records

> N Replace (oldest_value,

new_value Add

new_value

Update (EoI, State)

newChange (EoI, State)

Listen to Sensors

(a) Sensor

Start

Read Cur_Value

Compare Cur_value with previous value

(range)

Send Cur_Value

Change

Wait Period (T)

Yes

Crawling Levels:

– WoTSE

– WoTSF

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

The WoTSF Implementation (Indexing)

• The WoTSF is evaluated using Real dataset:

We use Kth percentile (historical data) -> single record per time unit.

e.g.

Suppose, a temperature

sensor reads a set of

values {5, 20, 21, 20,

20, 21, 23, 20, 21, 23}

then,

average=19.4

50th = 20

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

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A

CM

, Cai

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Egyp

t, M

ay, 2

01

6.

The WoTSF Implementation (Indexing)

• The WoTSF is evaluated using random values:

– prediction model (‘7-Days’)

– SThs of type ‘occupancy’ in 10 WoT networks, -> 10,000 SThs

– aggregation function ‘Max’ (empty room).

– expanding the quadruple predictions

The prediction model type -> periodical crawling processes.

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

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F: A

Fra

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," in

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CM

, Cai

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Egyp

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6.

EXPERIMENTAL EVALUATION

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

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Egyp

t, M

ay, 2

01

6.

The WoTSF Implementation (Indexing)

(a) (b)

In case of distinct SThs values

• Dyser Index (a) – Count -> Max reading (STh level)

• WoTSF index (b) – Count -> Max reading (WoT level)

Local search engine WoTSF

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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d S

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ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

The WoTSF Implementation (Searching)

• The WoTSF prototype:

– implements autosuggestions like dyser.

– filters buildings (static part) -> WoTSEs’ APIs

– Evaluation is done on the dynamic part of the query (WoTSEs) using:

• Building - Level (Master Indices)

• SThs – Level (Secondary Indices)

(a) (b) (c)

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

The WoTSF Evaluation (Index size)

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

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ay, 2

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6.

Experimental Evaluation (WoTSF & Dyser)

• Index Size

M. Y

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nan

, S. K

hat

tab

, an

d R

. Bah

gat,

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CM

, Cai

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Egyp

t, M

ay, 2

01

6.

Experimental Evaluation (WoTSF & Dyser)

• Processing Time - WoTSF indices (High Level) - Dyser Indices

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

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F: A

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CM

, Cai

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Egyp

t, M

ay, 2

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6.

Experimental Evaluation (WoTSF & Dyser)

• Result Accuracy

Accuracy = 𝐶𝑜𝑟𝑟𝑒𝑐𝑡 𝑉𝑎𝑙𝑢𝑒𝑠 (𝑡𝑟𝑢𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒𝑠)

𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑡𝑟𝑖𝑒𝑣𝑒𝑑 (𝑓𝑎𝑙𝑠𝑒 𝑎𝑛𝑑 𝑡𝑟𝑢𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒𝑠)

Consistency = 𝐼𝑛𝑡𝑒𝑛𝑑𝑒𝑑 𝑅𝑒𝑡𝑟𝑖𝑒𝑣𝑒𝑑 (𝑡𝑟𝑢𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒𝑠)

𝑇𝑜𝑡𝑎𝑙 𝐼𝑛𝑡𝑒𝑛𝑑𝑒𝑑 (𝑡𝑟𝑢𝑒 𝑝𝑜𝑠𝑖𝑡𝑖𝑣𝑒𝑠+𝑓𝑎𝑙𝑠𝑒 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒𝑠)

Building ID Room ID State Prediction Value

100

101

Empty

0.8

102 0.4

103 0.7

200

201 0.3

202 0.5

203 0.4

Each building represents a single WoT network and hosts an occupancy sensor in each room

Search

Engine

Index

Size

WoTSF 2

Dyser 6

M. Y

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6.

The WoTSF Evaluation (Index size)

Search Engine Number of Results

all First K-Result = 4 Probability >= 50%

WoTSF 2 2 2

DSE 6 4 3

WoTSF and DSE search results according to different query types.

Search

Engine Results

Number of Results

all First K-Result = 4 Probability >=

50%

WoTSF Room 101 0.8

Room 202 0.5

DSE

Room 101 0.8

Room 103 0.7

Room 202 0.5

Room 102 0.4

Room 203 0.4

Room 201 0.3

WoTSF and DSE searching results (list of rooms) according to different query types.

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

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CM

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t, M

ay, 2

01

6.

The WoTSF Evaluation (Summary)

Criteria DSE WoTSF

Granularity of

master index Device (STh) level Network (e.g., building) level

Case:

Speed Search

All available results

More time for ranking.

top values per WoT network.

Faster search

Indices more up-to-date

Case:

Accurate

Results

Indices and accuracy: based on

prediction models.

Consumes more time

Indices: up-to-date.

Accuracy: high

Pros Less network overheads.

More consistent results

Small and semi-dynamic indices.

Less time for (crawling, parsing,

indexing).

Cons

Larger indices.

Harder to keep indices up-to-

date.

More time for crawling,

parsing, and indexing

Tradeoff between search speed

and result accuracy

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

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6.

CONCLUSION AND FUTURE WORK

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

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6.

• The WoTSF:

works on the top of Dyser

supports simple query language

saves time consumed for crawling, parsing and indexing

builds High level indices

Supports two types of search: • Search in high level indices (speed search).

• Search in secondary indices using LWoTSEs’ APIs (Accurate search)

increasing accuracy <-> indices are up-to-date

keeping individual LWoTSEs handle their network.

Conclusion

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

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6.

Future Work

• WoTSF has limitations such as:

– It consumes more time in accurate search type.

• Network overhead

• Merging and Ranking results.

– Scheduling the crawling processes

• to balance network overhead and result accuracy

– Using semantic technology: will be helpful for interoperability.

– Considering other aggregation functions

• LWoTSE has limitations such as:

– Extracting prediction models from SThs historical data

– Dynamic discovery.

– Solving problem of using multiple formats partially (crawling)

but not by meaning -> (ontologies)

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

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CM

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ay, 2

01

6.

References (Selected) [1]

M. Younan, S. Khattab, and R. Bahgat, "An Integrated Testbed Environment for the Web of

Things," in ICNS 2015 : The Eleventh International Conference on Networking and Services,

ISBN: 978-1-61208-404-6, Rome, Italy, May, 2015, pp. 69-78.

[2] M. Younan, S. Khattab, and R. Bahgat, "Evaluation of An Integrated Testbed Environment for

the Web of Things ", in IntSys15v8n34 : International Journal On Advances in Intelligent

Systems, v 8 n 3&4, December, 2015.

[3] Google. (2010, Jan.) Search Engine Optimization (SEO) - Starter Guide.

[4] P. Suganthan G C, "AJAX Crawler," in Data Science & Engineering (ICDSE), International

Conference on. IEEE, Cochin, Kerala, July 2012, pp. 27-30.

[5] S. Mayer, D. Guinard, "An Extensible Discovery Service for Smart Things," in in Proceedings of

the 2nd International Workshop on the Web of Things (WoT 2011), ACM, San Francisco, CA,

USA, June, 2011, pp. 7-12.

[6] (2015, Jan.) shodan search engine. [Online]. www.shodanhq.com

[7] B. Ostermaier, K. Romery, F. Mattern, M. Fahrmairz, and W. Kellererz, "A Real-Time Search

Engine for the Web of Things," in The 2nd IEEE International Conference on the Internet of

Things (IoT), Tokyo,Japan, November. 2010, pp. 1-8.

[8] C. Zhang, T. Zhang, and M.Wang, "A Distributed Range Query Framework for the Internet of

Things," in 18th International Conference on Intelligence in Next Generation Networks (ICIN

2015), IEEE 2015, ISBN 978-1-4799-1866-9, Paris, France, February, 2015, pp. 83-88.

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

F: A

Fra

mew

ork

fo

r Se

arch

ing

in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

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tern

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Co

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ren

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n In

form

atic

s an

d S

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ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.

QUESTIONS ?

THANKS

M. Y

ou

nan

, S. K

hat

tab

, an

d R

. Bah

gat,

"W

oTS

F: A

Fra

mew

ork

fo

r Se

arch

ing

in t

he

We

b o

f Th

ings

," in

INFO

S 2

01

6 :

The

10

th In

tern

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nal

Co

nfe

ren

ce o

n In

form

atic

s an

d S

yste

ms,

A

CM

, Cai

ro ,

Egyp

t, M

ay, 2

01

6.