Souleiman Hasan, Edward Curry• WATERNOMICS will develop and introduce ICT as an enabling...

Water Management, Web of Things, and Enabling Technologies

Souleiman Hasan, Edward Curry

W3C WoT Interest Group MeetingMunich, Germany, 2015

W3C WoT IG

Insight Centre for Data Analytics

https://www.insight-centre.org/

Insight Centre @ National University of Ireland, Galway

Formerly DERI

~ 150 researchers

April 2015, Munich, Germany2

https://www.insight-centre.org/

W3C WoT IG

• WATERNOMICS will develop and introduce ICT as an enabling technology to manage water as a resource, increase end-user conservation awareness and affect behavioural changes, and to avoid waste through leak detection.


W3C WoT IG

Overview

• Use Case• Event Processing Paradigm• Semantics• Approximate Matching• Thematic Event Processing• Building the IoT


W3C WoT IG

Use Case- Home Water Awareness and

Conservation -


W3C WoT IG

Motivation and Purpose for John

• Motivation• Lower personal water footprint• Water is a scare resource• Save money on water bill

• Purpose• Set monthly water consumption target• Keep aware of consumption• Get recommendations from things or Web


W3C WoT IG

Actors


Things

John

Sensors

Home Water Management Provider HWMP

ServiceLaptop, phone,…

W3C WoT IG

Step 1- Configuration


Things

John

Sensors


Service

HTML

Laptop, phone,…

HTTPHTTP

HTTPSet URL of

HWMP Service

W3C WoT IG

Step 2- Registration


Things

John

Sensors


ServiceLaptop, phone,… Catalog

Things IDs (URIs)

HTTP-‐

JSON L

D

HTML

HTTP-‐ JSON LD

HTTP...

W3C WoT IG

Step 3- Set Target


Things

John

Sensors



Things IDs (URIs)

HTTP

HTML

Set Monthly target 200L

W3C WoT IG

Step 4- Data Transfer


Things

John

Sensors



Consume water

HTML

Push EventsCatalogThings

IDs (URIs)HTTP-‐

JSON L

D

HTTP-‐ JSON LD

HTTP...

W3C WoT IG

Step 5- Aggregation/Analytics


Things

John

Sensors



Consume water

HTML

HTTP

HTTP

HTTPPush Events

Aggregation

CatalogThings

IDs (URIs)

W3C WoT IG

Step 6- Keep Aware


Things

John

Sensors



Things IDs (URIs)

HTML

60% of target, 10 days remaining

HTTP

W3C WoT IG

Step 7- Thing Thinks!


Things

John

Sensors



Things IDs (URIs)

HTML

2L per dayMy share 40%

Could miss target!!

HTTP-‐JSON LD

W3C WoT IG

Step 8- Thing Recommends


Things

John

Sensors



Things IDs (URIs)

HTML

Use program B instead of A

Direct Interaction-‐ LCD and Control Panel

W3C WoT IG

Going Large Scale

Event Processing and Semantics


W3C WoT IG

Complex Event Processing Systems

Adapted from CUGOLA, G. AND MARGARA, A., 2011. Processing flows of information: From data stream to

complex event processing. ACM Computing Surveys Journal.

SOULEIMAN HASAN AND EDWARD CURRY. 2014. APPROXIMATE SEMANTIC MATCHING OF EVENTS FOR THE INTERNET OF THINGS. ACM TRANS. INTERNET TECHNOL. 14, 1, ARTICLE 2 (AUGUST 2014), 23 PAGES.

(ADAPTED FROM CUGOLA AND MARGARA)


W3C WoT IG

The Principle of Decoupling

Patrick Th. Eugster, Pascal A. Felber, Rachid Guerraoui, and Anne-Marie Kermarrec. 2003. The

many faces of publish/subscribe. ACM Comput. Surv. 35, 2 (June 2003), 114-131.

Event ProcessingSpace

Time

SynchronizationEvent source

Event consumer


W3C WoT IG

Problem

• Event producers and consumers are semantically coupled▪ Consumers need prior knowledge of event types, attributes and

values.▪ Limits scalability in heterogeneous and dynamic environments

due to explicit dependencies▪ Difficult development of event processing subscriptions/rules in

heterogeneous an dynamic environments.

Space

Time

SynchProducer Consumer

Semantic


W3C WoT IG

Statistical Vector Space Semantics and Approximate

Event Processing


www.insight-‐centre.org

Distributional Semantics• Distributional hypothesis: the context surrounding a given word in a

text provides relevant information about its meaning.• Simplified semantic model.• Associational and quantitative.

• Explicit Semantic Analysis (ESA) is the primary distributional model used in this work.

A wife is a female partner in a marriage. The term "wife" seems to be a close term to bride, the latter is a female participant in a wedding ceremony, while a wife is a married woman during her marriage. ...

Slide Credits: Andre Freitas (http://andrefreitas.org/), [Freitas et al., 2013]

http://andrefreitas.org/


W3C WoT IG

Semantic Relatedness

θ

c1

child

husbandspouse

cn

c2

Works as a semantic ranking function

E.g. esa(room, building)= 0.099 E.g. esa(room, car)= 0.009 Slide Credits: Andre Freitas (http://andrefreitas.org/) [Freitas et al., 2013]


http://andrefreitas.org/


W3C WoT IG

Matching Model

• Top-‐1 and Top-‐k most probable mappings{type: increased energy consumption event, measurement unit: kilowatt per hour, device: computer, desk: desk 112c, office: room 112, floor: ground floor, zone: building, city: Galway, country: Ireland, continent: Europe}

{type = increased energy consumption event,

device = laptop~, room~esa = room 112}


W3C WoT IG

Thingsonomies and Thematic Event Processing



Tagging

• Inspired by works in social tagging, i.e. folksonomies

• Folksonomies are bottom up approach to semantics

• Free words


EarthBiAs2014

Approach 5: Thematic Event Processing

7-‐11 July 2014, Rhodes, Greece

Producer Consumer

event

Loose Semantic Coupling via Large Text Corpora

Happened

Publish: (A+T1)

Happened

Interested in

Subscribe: Interested in (B

+T2)

Symbolize

As (A+T1)Symbolize

As (B+T2)

A d1 d2 d3 d4 d5 d6 d7 d8 ….

B d1 d3 d4 d17

d25

d26

d77

d78

….

Theme T1

Theme T2

~

Souleiman Hasan and Edward Curry. 2014. Thematic event processing. In Proceedings of the 15th International Middleware Conference (Middleware '14).

Souleiman Hasan and Edward Curry. 2014. Approximate Semantic Matching of Events for the Internet of Things. ACM Trans. Internet Technol. 14, 1, Article 2 (August 2014), 23 pages


W3C WoT IG

The Thematic Approach

• Exchange approximations of meanings

Publisher Alice

Consumer Bob

Theme the

Subscription

Theme ths

ExpressionApproximate matcher

Event

Payload

Parameterization

Loose semantic coupling: lightweight free tagging

Hasan, S. and Curry, E., 2014. Thematic Event Processing. Middleware 2014.



W3C WoT IG

• Thematic tags added to events

Event Representation

Event

energy, appliances, building

type: increased energy consumption event, measurement unit: kilowatt per hour,

device: computer, office: room 112



W3C WoT IG

• Thematic tags added to subscriptions

Subscription Representation

Subscription

power, computers

type= increased energy usage event~, device~= laptop~, office= room 112



Parameterized Similarity

• Thematic tags used to parameterize the semantic measure


Interpreting Terms

• Project vectors in a distributional semantic vector space

• Thematic projection

W3C WoT IG

Building the IoT


W3C WoT IG

Challenges for Building IoT Systems

• Vastly heterogeneous, decoupled, and distributed nodes

• Lack of central coordination, reference requirements, or data model

• High overhead associated with software design associated with establishing agreements between parties


W3C WoT IG

Building IoT Event System

Indexing

Collector

Semantic relatedness web service

Textual corpus

Vector space index

Consumer Bob(user)

Publisher Alice

Publish + thematic tags

Thematic event processing engine(s)Approximate single event

matching

Subscribe + thematic

tags

IoT sensors

Terms +themes pairs

Relatedness score

CollectorPublisher Carol


CollectorPublisher Dave


Consumer Dan(application developer)

Consumer Erin(application developer)

Heterogeneous IoT Events

Relevant events

normalized for Bob


tags

Relevant events

normalized for Dan


tags

Relevant events

normalized for Erin

5

31

2

4 6

Souleiman Hasan and Edward Curry. 2015. Thingsonomy: Tackling Variety in Internet of Things Events, IEEE Internet Computing


W3C WoT IG

For WoT IG

• To have minimal description on format/semantics

• To enable free tags in things/events description

• To externalize the semantics model outside of the WoT framework to allow more possible semantics model: domain specific, ontologies, statistical semantics, non-symbolic semantics


W3C WoT IG

Conclusions

• Coupling necessary for crossing boundaries

• Decoupling necessary for scalable software

• Event-based systems need extension to address the coupling/decoupling tradeoff for semantics

• Approximate and thematic event processing exchange approximations of meaning with loose semantic coupling


W3C WoT IG

References

• CUGOLA, G. AND MARGARA, A., 2011. Processing flows of information: From data stream to complex event processing. ACM Computing Surveys Journal.

• EUGSTER, P.T., FELBER, P.A., GUERRAOUI, R. AND KERMARREC, A.M., 2003. The many faces of publish/subscribe. ACM Computing Surveys (CSUR), 35(2), pp.114–131.

• Carlile, Paul R. "Transferring, translating, and transforming: An integrative framework for managing knowledge across boundaries." Organization science15.5 (2004): 555-568.

• SOULEIMAN HASAN AND EDWARD CURRY. 2015. TACKLING VARIETY IN INTERNET OF THINGS EVENTS, IEEE Internet Computing (In Press)

• SOULEIMAN HASAN AND EDWARD CURRY. 2014. APPROXIMATE SEMANTIC MATCHING OF EVENTS FOR THE INTERNET OF THINGS. ACM TRANS. INTERNET TECHNOL. 14, 1, ARTICLE 2 (AUGUST 2014), 23 PAGES. DOI=10.1145/2633684 HTTP://DOI.ACM.ORG/10.1145/2633684

• HASAN, S., O’RIAIN, S. AND CURRY, E., 2013. TOWARDS UNIFIED AND NATIVE ENRICHMENT IN EVENT PROCESSING SYSTEMS. IN THE 7TH ACM INTERNATIONAL CONFERENCE ON DISTRIBUTED EVENT-BASED SYSTEMS (DEBS 2013). ARLINGTON, TEXAS, USA: ACM.

• HASAN, S., O’RIAIN, S. AND CURRY, E., 2012. Approximate Semantic Matching of Heterogeneous Events. In 6th ACM International Conference on Distributed Event-Based Systems (DEBS 2012). Berlin, Germany: ACM, pp. 252–263.

• SOULEIMAN HASAN AND EDWARD CURRY. 2014. THEMATIC EVENT PROCESSING. IN PROCEEDINGS OF THE 15TH INTERNATIONAL MIDDLEWARE CONFERENCE (MIDDLEWARE '14). ACM, BORDEAUX, FRANCE, 109-120. DOI=10.1145/2663165.2663335 HTTP://DOI.ACM.ORG/10.1145/2663165.2663335

• HASAN, S., CURRY, E., BANDUK, M., AND O’RIAIN, S. TOWARD SITUATION AWARENESS FOR THE SEMANTIC SENSOR WEB: COMPLEX EVENT PROCESSING WITH DYNAMIC LINKED DATA ENRICHMENT. THE 4TH INTERNATIONAL WORKSHOP ON SEMANTIC SENSOR NETWORKS 2011 (SSN11), (2011), 60–72.


W3C WoT IG

Dataset and Software

• Dataset▪ Souleiman Hasan, Edward Curry, Thematic event

processing dataset, DOI: 10.13140/2.1.3342.9123▪ Available at http://www.researchgate.net/publication/

263673956_Thematic_event_processing_dataset

• Collider ▪ Souleiman Hasan, Kalpa Gunaratna, Yongrui Qin, and Edward Curry. 2013.

Demo: approximate semantic matching in the collider event processing engine. In Proceedings of the 7th ACM international conference on Distributed event-based systems (DEBS '13). ACM, New York, NY, USA, 337-338. DOI=10.1145/2488222.2489277 http://doi.acm.org/10.1145/2488222.2489277


http://www.researchgate.net/publication/263673956_Thematic_event_processing_dataset




W3C WoT IG

Evaluation Metrics

• Alternative cost: number of exact rules needed to compensate heterogeneity

• Precision, Recall, F1Score: reflects ratios of true/

false negatives and positives

• Throughput: # of matched events per time unit

• Standard error: in performance of sample of thematic tags associated with subs and events



W3C WoT IG

Results

Hasan, S. and Curry, E., 2014. Thematic Event Processing. Middleware 2014. Under review.

The use of less terms to describe events, around 2-‐7, and more to describe subscriptions, around 2 -‐15, can achieve a good matching quality and throughput together with less error rates. Lightweight amount of tags.


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Souleiman Hasan, Edward Curry• WATERNOMICS will develop and introduce ICT as an enabling...

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