Bridging Socially-Enhanced Virtual Communities

15
1 Bridging Socially-Enhanced Virtual Communities SAC 2011, March 21-24, 2011, Taichung, Taiwan Daniel Schall Florian Skopik, Harald Psaier Schahram Dustdar Distributed Systems Group Vienna University of Technology, Austria [email protected]

description

Interactions spanning multiple organizations have become an important aspect in today’s collaboration landscape. Organizations create alliances to fulfill strategic objectives. The dynamic nature of collaborations increasingly demands for automated techniques and algorithms to support the creation of such alliances. Our approach bases on the recommendation of potential alliances by discovery of currently relevant competence sources and the support of semi-automatic formation. The environment is service-oriented comprising humans and software services with distinct capabilities. To mediate between previously separated groups and organizations, we introduce the broker concept that bridges disconnected networks. Here we present a dynamic broker discovery approach based on interaction mining techniques and trust metrics.

Transcript of Bridging Socially-Enhanced Virtual Communities

Page 1: Bridging Socially-Enhanced Virtual Communities

1

Bridging Socially-Enhanced Virtual Communities

SAC 2011, March 21-24, 2011, Taichung, Taiwan

Daniel SchallFlorian Skopik, Harald Psaier

Schahram Dustdar

Distributed Systems GroupVienna University of Technology, Austria

[email protected]

Page 2: Bridging Socially-Enhanced Virtual Communities

Open dynamic ecosystems People and software services

integrated into evolving “solutions“

Communications and coordination „Anytime-anywhere“ pervasive

infrastructures and mobility

Mass collaboration Knowledge sharing and

social interaction

MotivationParadigm: human and service interactions

… software service

… user

… human/service interaction

Page 3: Bridging Socially-Enhanced Virtual Communities

Human-Provided Services (HPS)

User contributions modeled as services Users define their own services (!= WS-HT) Reflect willingness to contribute

Technical realization Service description with

WSDL (capabilities) Communication via SOAP messages

Example: Document Translation Service Input: original document, deadline, constraints Output: translated text

D. Schall, H.-L. Truong, S. Dustdar. The Human-Provided Services Framework. IEEE 2008 Conference on Enterprise Computing, E-Commerce and E-Services (EEE),Crystal City, Washington, D.C., USA, 2008. IEEE.

HPS

v

w

u

serviceprovider

Page 4: Bridging Socially-Enhanced Virtual Communities

Collaborative Environment

Collaborations and activities A concept to structure information in flexible

collaboration including the goal of ongoing tasks Involved actors, and utilized resources such as

documents or services

Monitoring of interactions Activity-based events (assignment, delegation, …) SOAP-based interactions (HPS)

Relations emerge from interactions Bound to particular scopes (expertise areas) Context in which interactions take place

tags applied to various artifacts4

Page 5: Bridging Socially-Enhanced Virtual Communities

Professional Virtual Communities

Various member groups collaborate in the context of different activities

These groups intersect since members may participate in different activities

Expert groups: the creation of new specifications or the discussion of future technology standards

Problem: missing expertise or know-how Idea: brokers bridge gaps (i.e. structural holes)

5

Page 6: Bridging Socially-Enhanced Virtual Communities

Dynamic Brokers

Social relations (FOAF) between members

Clusters Actors u, v, w Actors j, k, l, m

Broker Actor u knows b and b knows j Broker bridges two separated clusters

Finding brokers Social network analysis Network metrics: shortest path and betweenness

6

Page 7: Bridging Socially-Enhanced Virtual Communities

Broker Discovery

How to specify discoverypolicies? A broker (e.g., b) should

be connected to j but not to ‘some other actor’

The broker should betrusted by the community j, k, l, m

Should be trusted by at least one of them, all of them, …

How to discover new brokers Metrics and monitoring Weighted collaboration (social network) links

7

Page 8: Bridging Socially-Enhanced Virtual Communities

Querying Social Networks

The social network graph Sets of nodes and edges Node attributes (-> user profiles) Edge attributes (-> relationship metrics)

Querying graph data SPARQL (Query Language for RDF)

But … Runtime logs must be mapped into “semantic layer”

(service infrastructure) How to define complex queries filtering edges, nodes

based on metrics?

8

Page 9: Bridging Socially-Enhanced Virtual Communities

BQDL - Broker Query and Discovery Language (1/2)

Domain specific language To query social network data To find brokers that connect independent communities Metrics (link weights) Filters (nodes, edges)

SQL-like syntax Select … From … Where Add graph specific features Select node From G Where [Filter]

9

Page 10: Bridging Socially-Enhanced Virtual Communities

BQDL - Broker Query and Discovery Language (2/2)

Example query: find broker to connect two predefined communities

10

Select nodes connected to source community (potential brokers)

Select nodes connected to source community (potential brokers)

Broker must be directly connected to targetBroker must be directly connected to target

Page 11: Bridging Socially-Enhanced Virtual Communities

Prototype and Evaluation

Simulation environment Testbed to simulate dynamic interactions Distributed service-oriented environment SOAP-based logs + context identifiers (tags, …)

Performance study To test scalability of BQDL query stack implementation Concurrent processing of complex queries (see paper for detailed results)

Broker discovery tool Analyze properties of discovered brokers Visual frontend to test effectiveness of queries

11

Page 12: Bridging Socially-Enhanced Virtual Communities

G2 (Genesis) Simulation Environment

Testbed for simulating behavior of services (HPSs and SBSs) To obtain interaction logs

12

A WS Framework with: 3L: Services (Clients,

Registries, Brokers) 2L: Control Layer (Models,

Configuration) 1L: Plug-ins (Extensions,

e.g., logging, routing, adaptation language)

0L: Front-End and Back-End

Juszczyk L., Dustdar S. (2010). Script-based Generation of Dynamic Testbeds for SOA. 8th IEEE International Conference on Web Services (ICWS'10),5.-10. July 2010, Miami, USA.

Page 13: Bridging Socially-Enhanced Virtual Communities

Broker Discovery Tool

Search by tags Expertise areas Metrics (e.g., trust

threshold)

Broker View Brokers (blue nodes)

centered around query term (‘robustness’)

Communities attached to broker

Adapt visualization by adjusting thresholds

13

Page 14: Bridging Socially-Enhanced Virtual Communities

14

Conclusion

Human participation in SOA Flexible interactions between HPSs and SBSs Monitoring of interactions

Broker patterns Shared and exclusive brokers Reputation management

Broker Query and Discovery Language SQL-based syntax Domain specific query language to indentify brokers Discovery policies Support of rich set of metrics

Page 15: Bridging Socially-Enhanced Virtual Communities

15

Thank you!Questions?

[email protected]