open service network analysis

Jorge Cardoso (1,2), John A. Miller (3), Casey Bowman (3), Christian Haas (2), Amit P. Sheth (4), Tom W. Miller (5)

(1) CISUC/Dept. Informatics Engineering, University of Coimbra, Portugal(2) Karlsruhe Service Research Institute, Karlsruhe Institute of Technology, Germany

(3) Dept. of Computer Science, University of Georgia, USA(4) Kno.e.sis Center, Wright State University, USA

(5) Dept. of Economics, Finance and Quantitative Analysis, Kennesaw State University, USA

// 01 May 2013 //First Int. IFIP Working Conf. on Value-Driven Social Semantics & Collective Intelligence (VaSCo)

Paris, France

Open Service Network Analysis

Departamento de Engenharia InformáticaFCTUC FACULDADE DE CIÊNCIAS E TECNOLOGIA da UNIVERSIDADE DE COIMBRA

The importance of services

Manual Semi-automatic Fully Automated

2013 Genessiz: Center for Large-Scale Service System Research 2

Service economies

Self-services

Consulting IT Services Cloud services

Software

The importance of networks


World Wide Web Social NetworksLinked Data

…energy grids, water systems, wireless mobile networks...

Financial/Political Networks Food chain NetworksRailway Network

Presenter

Presentation Notes

The Internet, the World Wide Web, social networks, and Linked Open Data (LOD) are examples of some of the myriad types of networks that are a part of everyday life for many people. The recently established network science [1] field of research confirms also the importance of networks in more tangible areas such as energy distribution grids, water systems, and wireless mobile networks. Small-world networks are sparse networks with high cluster coefficient, relatively short average path length, and scalable entropy. In nonmathematical terms, a scale-free network is one with a small number of high-degreed nodes and a large number of low-degreed nodes. The rare nodes with high degree are called hubs; therefore, scale-free networks are networks with hubs, which results in a skewed degree sequence distribution.

Networks and Vulnerability• Protecting just 4 nodes

made a system less vulnerable

• Left – all communications

servers are coupled to the power grid

• Right – Four are decoupled – Lower vulnerability

• Circles represent a power grid• Diamonds a communications

network• Colors show the probability that a

node fails after 14 servers fail

2012 Genessiz: Center for Large-Scale Service System Research 4Source: C.M. Schneider et al/arxiv.org 2011; Map: Geoatlas/graphi-ogre, adapted by T. Dubéhttp://www.sciencenews.org/view/feature/id/343939/description/When_Networks_Network

…definitions…“A service network is defined as a graph structure

composed of service systems which are nodes connected by one or more specific types of

service relationship, the edges.”


”A service system is a functional unit with a boundary through which interactions occur with the environment, and, especially, with other service systems.”!

Service Network Modeling

_Business services__Business services_


_Business services_ _Business services_

_Business services_

_Business services_

_Business services_

_Business services_

_Business services_ _Business services_

_Business services_

_Business services_

_Business services_

_Business services_

_Business services_

_Business services_

_Business services_

_Business services_


_Business services_

_Business services_

_Business services_

_Business services_

_Business services_


Basic Building BlocksService Description

• Service description• Follows Linked Data principles • Simplicity for computation and

modeling• Reuse existing vocabularies• Means for publishing and

interlinking distributed data• [CPL+13][CM12][CPL+12][CB

M+10]

Service Relationship

Open Semantic Service Relationship (OSSR)

• Relationship description• Interconnects services• Multi-layer• Follows Linked Data principles • Reuse existing vocabularies• Means for interlinking service

descriptions/systems



www.internet-of-services.com

http://www.linked-usdl.org/

Linked USDL:CoreLinked USDL:PricingLinked USDL:SECLinked USDL:SLA

Service Description Modeling


http://aws.amazon.com/ec2/

:pricing_EC2_Small_EU_Windows_ReservedInstance_Light_1yr a price:PricePlan ;dcterms:description "Price plan for a 'Small' EC2 Reserved Instance in Europe with Windows, light

utilization and a one year contract duration."@en ;price:hasContractDuration

[ a gr:QuantitativeValue ; gr:hasValueInteger "1" ;gr:hasUnitOfMeasurement "ANN" ] ;

price:hasBillingCycle[ a gr:QuantitativeValue ;

gr:hasValueInteger "1" ;gr:hasUnitOfMeasurement "MON" ] ;

price:hasPriceComponent:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Upfront ,:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Hourly ,

:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Upfront a price:PriceComponent;

dcterms:title "General costs upfront"@en ;dcterms:description "One-time fee for general usage of the instance."@en ;price:isLinkedTo

…price:hasPrice

[ a gr:UnitPriceSpecification ;gr:hasCurrency "USD" ;gr:hasCurrencyValue "69" ;gr:hasUnitOfMeasurement "C62" ] .

@prefix price: <http://www.linked-usdl.org/ns/usdl-pricing#>


The relationship problem…• Relations provided by RDFS,

FOAF, SIOC, SKOS,…– rdfs:subClassOf,

owl:EquivalentClass– owl:sameAs, rdfs:seeAlso,

foaf:knows, …

• Limited and not suitable to connect all the world’s services.

• One approach – Connect services via multiple

types of connection layers– Capture the inherent richness and

characteristics of services

• This goes well beyond the connection of services treated simply as unidimensional nodes


Cardoso, J. Modeling Service Relationships for Service Networks. In 4th International Conference on Exploring Service Science (IESS 1.3), pages 114-128, Springer, LNBIP, Porto, Portugal, 2013.

Genessiz: Center for Large-Scale Service System Research2013 12


Service Network Analysis

Centrality: 23

ACME Customer Relationship

Management

ACME Business Intelligence

Heroku

Amazon Elastic Block

Store

BIME

Service ProvidersService Creators

Service ConsumersService ProvidersService Aggregators

Service Marketplace

Motivation Scenario

Service Value Networks (SVN)

Cooperative Models (t)

Evolution Models (t)

Open Semantic Service Relationship(OSSR)

Unified ServiceDescription Language(*- USDL)

Open Semantic Service Networks (OSSN)

Service networks

models

models

models

Service system

Optimization (?)

Service Network Analysis Approaches

1

2

3

4

Service Network Optimization


1


• Optimal construction has two phases– Maximal color-compliant construction (1) and cost minimization (2)

• Phase 1:– Build a service network from three sets of nodes, atomic services (sources),

composite services (intermediate nodes), and consumers (sinks). – Starting with the sources, all intermediate and consumer nodes are connected

by edges that are color compliant, e.g., if an intermediate node needs a blue input and green input and there exist sources producing/outputting these colors, then this intermediate node is added to the graph.

– This process continues through k stages, the maximum number of stages (i.e., distance from source to sink) desired.



• Optimal construction has two phases– Maximal color-compliant construction (1) and cost minimization (2)

• Phase 2:– Once the graph has been created, it can be reduced to an optimal form– Objective function: the cost of the network, and decision variables represent

the flow of material through the network. – The flow is constrained by the supply, production, or demand capacity of the

nodes in the network. – A Linear Programming algorithm such as the Simplex algorithm, can be used

to find the optimal values for the decision variables. – These values determine the optimal amount of flow through the network and

the value of the objective function estimates the minimum cost.


Evolutionary Analysis

• Hypothesis– Highly connected services increase their

connectivity faster than less connected ones– Preferential attachment (PA) phenomenon– Only local information

• Preferential attribute– e.g. price, quality, or availability


2

OSSN Formal Modeling


OSSN and Preferential Attachment

• Use USDL value proposition as a preferential attachment. – usdl:valueproposition– Service value is judged from the perspective

of consumers as they compare services among the alternatives.

• Let us assume – price is the value proposition (local rule)


OSSN and Preferential Attachment

• Objective – Forecast the evolution of a service network – The market share of each service is:


OSSN and Preferential Attachment• The service market

share is represented in the figure at t = 3.

• What will happen to the market if the conditions are not changed*?

• According to Bass model, the leading service will reaches a fixedpoint market share according to:

2012 Genessiz: Center for Large-Scale Service System Research 23*the value propositions of remain the same

Presenter

Presentation Notes

Figure 2 illustrates that from the four services provided, three also rise in market share during the early stages, reach a peak, and then decline as the service leader accelerates because of the increasing returns effect of preferential attachment.

OSSN and Preferential Attachment• The service market

share is represented in the figure at t = 3.

• What will happen to the market if the conditions are not changed*?

• According to Bass model, the leading service will reaches a fixedpoint market share according to:

2012 Genessiz: Center for Large-Scale Service System Research 24*the value propositions of remain the same

Presenter

Presentation Notes

Figure 2 illustrates that from the four services provided, three also rise in market share during the early stages, reach a peak, and then decline as the service leader accelerates because of the increasing returns effect of preferential attachment.

Cooperative AnalysisSelf-organizing system

• Explore the applicability of system dynamics – Using mathematical expressions to model the

relationships of SN– Instead of looking at causes and their effects in

isolation (e.g. PA)

• The next figure – Service systems Si, Sj, Sk, – Links illustrating internal and external

relationships


3

Total ServicesKPI Gain perIndividualService

-

+

+

Sk KPI = Resource Limit

+

Si KPI =# services

Sj KPI = # services

Sj KPI = Net gains

+

+

+

+

Si KPI = Net gains

+

+

+

-

-

+

Service system Si

Service system Sk

Service system Sj

a)

SN and System Dynamics

OSSR

OSSR OSSR

OSSR Causal links connect KPIs from different services’ and within services. (’Tragedy of the Commons’ archetype )

USDLUSDL

USDL

• Positive Feedback (+)Reinforcement and amplification• Negative Feedback (-)Counteracts perturbations and stabilizes

Presenter

Presentation Notes

The ‘Tragedy of the Commons’ archetype identifies the causal connections between individual actions and the collective results (in a closed system). It hypothesizes that if the individual use a common resource becomes too great for the system to, the commons will become overloaded or depleted and everyone will experience diminishing benefits.

OSSN and System Dynamics• If the two services Si and Sj overuse the shared service Sk,

– It will become depleted and all the providers will experience diminishing benefits

• Services Si and Sj– To increase net gains, both providers increase the availability of

service instances – As the number of instances increases, the margin decreases and

there is the need to increase even more the number of instances available

– As the number of instances increases, the stress on the availability of service Sk is so strong that the service collapses or cannot respond anymore as needed

– At that point, service Si and Sj can no longer fully operate and the net gain is dramatically reduced for all the parties involved as shown in the following figure

2012 Genessiz: Center for Large-Scale Service System Research 27Time

Si

Presenter

Presentation Notes

Causal links connect KPIs from different services’ and within services. The pattern represented by this OSSN is commonly known as the ’Tragedy of the Commons’ archetype. It hypothesizes1 that if the two services Si and Sj overuse the common/shared service Sk, it will become overloaded or depleted and all the providers will experience diminishing benefits. Service Si and Sj provide services to costumers. To increase net gains, both providers increase the availability of service instances. As the number of instances increases, the margin decreases and there is the need to increase even more the number of instances available. As the number of instances increases, the stress on the availability of service Sk is so strong that the service collapses or cannot respond anymore as needed. At that point, service Si and Sj can no longer fully operate and the net gain is dramatically reduced for all the parties involved as shown in Figure 3.b). This scenario shows that the modeling of causal relationships using the extensions proposed for the OSSR model provides the required mechanism to execute an analytical analysis of open semantic service networks.

Service Value Networks• Previous three approaches considered structural aspects, SVN take consider

participants’ behavior– For example, depending on the market mechanism of a service marketplace, providers

might report their service characteristics (such as price) untruthfully to increase sales

• Consumers request services – Certain functionalities– Have preferences (e.g. an acceptable price range, availability thresholds, etc.)


SVNs components

Attributes: availability, throughput, latency, and price.

4

Service Value Networks

• Mechanism Design perspective– How we can select a combination of services

that best satisfies the consumer requirements?

• Complex service auction– Maximize the welfare of the SVN– Sum of consumer and provider utilities.

• Provider utility = revenue - costs of service• Consumer utility = valuation - price• Valuation = distance between request and offer


Service Value Networks• Two step mechanism

– Calculation of the allocation (1)– Calculation of the payments (2)

• (1) Calculation of the allocation– Computes the various combinations of atomic services to the desired aggregated

service.– Select the aggregated service with the highest (positive) difference between

consumer valuation minus the costs of the atomic services.

• (2) Calculation of the payments:– Implement a Vickrey-Clarke-Groves (VCG) payment scheme to determine the

actual payments to the providers– VCG motivate providers to report the attributes of their services truthfully– Rewards providers according to their relative importance (added value) to the SVN,

which means they can receive an additional discount on their service provisioning price.


Presenter

Presentation Notes

In auction theory, a Vickrey–Clarke–Groves (VCG) auction of multiple goods is a sealed-bid auction wherein bidders report their valuations for the items. The auction system assigns the items in a socially optimal manner. This system charges each individual the harm they cause to other bidders,[1] and ensures that the optimal strategy for a bidder is to bid the true valuations of the objects. It is a generalization of a Vickrey auction for multiple items.

Service Value Networks

• Properties of the mechanism– Allocative efficient: it selects the best

combination of atomic services given the consumer preferences.

– Strategy-proof: the dominant strategy for service providers is to submit their service attributes truthfully to the marketplace


Conclusions• Service Networks

– Large scale, open, dynamic, and highly distributed

• Service Network Modeling– Use Linked USDL for open service modeling– Use the Open Semantic Service Relationship (OSSR) model– Results in Open Semantic Service Networks (OSSN)

• Service Network Analysis– Allocation optimization– Evolutionary analysis– Cooperative analysis– Value analysis



Thank you.Questions?

References3. Von Bertalanffy, L.: General System Theory: Foundations, Development, Applications. The International Library of Systems Theory and Philosophy. Braziller (2003)8. Yule, U.: A mathematical theory of evolution based on the conclusions of dr. j. c. willis. Phil. Trans. Roy. Soc. Lond. 213(2), 21–87 (1925)12. J. Gordijn, E. Yu, and B. van der Raadt, e-service design using i* and e3value modeling, IEEE Software, vol. 23, pp. 26-33, 2006.13. H. Akkermans, Z. Baida, J. Gordijn, N. Pena, A. Altuna, and I. Laresgoiti, Value webs: Using ontologies to bundle real-world services," IEEE Intelligent Systems, vol. 19, no. 4, pp. 57--66, Jul. 2004.14. O. Danylevych, D. Karastoyanova, and F. Leymann, Service networks modelling: An soa & bpmstandpoint, Journal of Universal Computer Science, vol. 16, no. 13, pp. 1668--1693, jul 2010.15. V. Allee, Reconfiguring the value network," Journal of Business Strategy, vol. 21, no. 4, pp. 1-6, 2000.16. N. Weiner and A. Weisbecker, A business model framework for the design and evaluation of business models in the internet of services, in Proceedings of the Annual SRII Global Conference, Washington, DC, USA, 2011, pp. 21-33.17. R. C. Basole and W. B. Rouse, Complexity of service value networks: Conceptualization and empirical investigation, IBM Systems Journal, vol. 47, no. 1, pp. 53-70, 2008.


References• [CPL+13] Cardoso, J.; Pedrinaci, C. and Leenheer, P. D Open Semantic Service Networks:

Modeling and Analysis. In 4th International Conference on Exploring Service Science (IESS 1.3), pages 141-154, Springer, LNBIP, Porto, Portugal, 2013.

• [Car13] Cardoso, J. Modeling Service Relationships for Service Networks. In 4th International Conference on Exploring Service Science (IESS 1.3), pages 114-128, Springer, LNBIP, Porto, Portugal, 2013.

• [CM12] Cardoso, J. and Miller, J. A Internet-Based Self-Services: from Analysis and Design to Deployment. In The 2012 IEEE International Conference on Services Economics (SE 2012), IEEE Computer Society, Hawaii, USA, 2012.

• [CPL+12] Cardoso, J.; Pedrinaci, C.; Leidig, T.; Rupino, P. and Leenheer, P. D Open semantic service networks. In The International Symposium on Services Science (ISSS 2012), pages 1-15, Leipzig, Germany, 2012.

• [CBM+10] Cardoso, J.; Barros, A.; May, N. and Kylau, U. Towards a Unified Service Description Language for the Internet of Services: Requirements and First Developments. In IEEE International Conference on Services Computing, IEEE Computer Society Press, Florida, USA, 2010.
