rusmart 2013 presentation

A Sub-graph Isomorphism

Based Approach to Enable

Discovery and Composition of

Smart Space Elements

Oscar Rodriguez Rocha

Cristhian Figueroa

Boris Moltchanov

Politecnico di Torino, Telecom Italia

ruSMART 2013

Motivation

• Mobile technologies are on the rise: – Growing number of customers

– Heterogeneity and number of mobile devices and services

• Mobile environments are dynamic and heterogeneous– Increase in complexity and costs to manage and monitor mobile

services.

• Challenge– To manage and monitor the behavior of mobile users in order to

provide them with more tailored mobile services

– Increase mobile operator’s revenues

Smart Space Governing (SSG)

• Allows to monitor and manage a mobile network by

representing it as a Smart Space (SS).

• Smart Space Elements (SSE):

– Mobile Operator

– Mobile Users

– Mobile Devices

– Mobile Services

– Monitoring Services


• A Monitoring Service contains a set of

inputs/outputs and a label with the description of

its functionality.

Monitoring Service 1

Monthly number of SMSs by user

Number of SMSs

Starting Date

User ID

IMEI

Inputs

Outputs

Label


• SS can be managed by creating Composed

Monitoring Services (CMS) or rules driven by the

outputs of the SS elements.

– CMS are represented as graphs whose nodes can be:

• Monitoring Services

• Connectors: XOR-Split, AND-Split, AND-Join, OR-Join

• Events: alarms, messages, notifications.

S4S1 XOR-S

S2

S3

S5AND-J


SSG over a Mobile Network

Mobile ServicesE.g. SMS, Voice call, Video Call, MMS, Internet, etc

Monitoring ServicesE.g. Internet data uploaded/downloaded by user, Monthly number of SMS’s by user,

get user name by IMEI, voice call duration by user, number of calls by cell ID

Composed Monitoring ServicesE.g. Send an email when more than 100.000 users sending more than 50 SMSs in a day

A SSG-based Platform for Telco

• Discovery mechanisms

• Visual Editor

• Storage layer

4CaaSt EU Project

• Goal: Create a PaaS Cloud platform which supports

the optimized and elastic hosting of Internet-scale

multi-tier applications

• Embeds features that ease programming of rich

applications

• Enables the creation of a business ecosystem where

applications from different providers can be tailored to

different users, mashed up and traded together

Automatic Compositions Discovery

System• Allows to create compositions of monitoring

services

• Discovers through a visual interface:

– Monitoring Services to be included in the

compositions.

• By label, by inputs/outputs

– Compositions that already exist in the repository

containing the user query in order to be reused.

• As result the services and compositions are

ranked according their similarity degree with the

user query.

Storage

Discovery

Visual Visual Editor Canvas

Monitoring Services Similarity Analyzer

Compositions Similarity Analyzer

Monitoring Services

Repository

Compositions Repository

Labels SimI/OSim

Structural Sim

Comp. RankingService Ranking

Automatic Compositions Discovery System

Visual Editor

• Allows to create Composed Monitoring

Services by dragging and dropping

components to the provided canvas

– Monitoring Services

– Connectors

• Automatic Composition Discovery

System

Monitoring Services Similarity

• Labels Comparator: Ngram (common q-grams) (m1),

check synonym (Wordnet) (m2), and check abbreviation

(m3).

• Interfaces Comparator: determine a service St from

inputs and outputs of a query service Sq, such that St

shares the larger possible number of outputs with Sq

and without exceeding its inputs.

Monitoring Services Similarity

Labels Comparator

XORsplit

XORjoin

MS4MS3

XORsplit

XORjoin

MS2MS1

Label: TextLabel: DialLabel: MessageLabel: Call Nc1

Nc2 Nc3

Nc4

Np1

Np2 Np3

Np4

Nc2 - Np2

LS (Call, Dial) = 1.0

1.0

Nc3 – Np3

LS (Message, Text) = 0.93

0.93

Nc2 - Np3

LS (Call, Text) = 0.1Nc3 – Np2

LS (Message, Dial) = 0.33

Compositions Similarity

• Problem: Search for similar compositions containing

the fragment of composition being designed in the

visual editor canvas.

– This is also known as sub-graph isomorphism problem

– NP- Problem

• Solution: Smart Space Elements Discovery

Algorithm (SSED)

SSED Algorithm: isomorphism

similarity

A B

C B

C D

G

D

A

I

B

C D

E

A

F

E F

H

J

B

C D

E

A

G

H I

J

K

F

E

F G

H

D

B

A

i

Query Composition

Compositions Repository

SSED Algorithm: sub-graph

Isomorphism• Adjacence matrix and backtracking

• Reduces the size of the search space.

Ullmann

[Ullman et. al.,1976]

• Distance matrix representation of a graph to establish an initial partition graph nodes.

Schmidt and Druffel[Schmidt et. al.,1976]

• Transformations that lead to reduced graphs adjusted to a canonical form.

McKay's Nauty

[Miyazaki, et. al.,1981]

• Based on the depth-first search strategy -> rules to prune the search tree.

VF

[Cordella, et. al.,2001]

• A more effective data structure to optimize the execution time.

VF2

[Cordella, et. al.,2004]

The compositions are similar to the combination of regular and irregular graphs. In this case VF2 is the most efficient algorithm

SSED Algorithm: sub-graph

Isomorphism

Source: Foggia et al

SSED Algorithm

• It is based on VF2 algorithm: – The VF2 create mappings between the nodes of two graphs in

order to find a mapping which represents a sub-graph

isomorphism

• The SSED Algorithm compares the structure and also:– Nodes similarity

• Textual Similarity: compare labels of the nodes

• Inputs/outputs Similarity: intersection

– It takes into account the type of nodes in order to reduce the

search space

• Monitoring Services

• Events

• Connectors

Storage Layer

• Reduced version of the original one (4Caast

marketplace)

• Divided into 2 repositories:

– 1 for monitoring services (inside the Service Similarity

Analyzer)

– 1 for composed monitoring services (in the Composition

Similarity Analyzer)

• Achieves faster speeds when responding to the

component suggestion queries made by Visual

Editor.

Performance Analysis

0

1000

2000

3000

4000

5000

0 20 40 60 80 100

Tim

e (

ms)

Nodes

Conclusions

• Experimental platform developed by a major mobile

network operator in Italy.

• Approach to monitor a mobile network through the

creation of rules, based on:

– work provided by an European project

– analogy of Smart Spaces

• Creation of an algorithm fast enough to be executed

each time the user creates a composition

Future work

• Platform

– Conduct field test together with the operator (MNO)

– Benchmark the results obtained with current existing

instruments / platforms

• Discovering algorithm

– Evaluate the effectiveness by conducting a measurement

of customer satisfaction.

– Create an indexing mechanism to improve the

performance in order to considerably reduce the total

execution time.

Questions?

спасибоOscar Rodriguez Rocha

Cristhian Figueroa

Boris MoltchanovPolitecnico di Torino, Telecom Italia

ruSMART 2013

VF2 based AlgorithmPROCEDURE Match (s)

INPUT: an intermediate state s; the initial state s0 has M (s0)=0

OUTPUT: the mappings between two graphs

IF M(s) covers all the nodes of G2 THEN

OUTPUT M(s)

ELSE

Compute the set P(s) of the pairs candidate for inclusion in M(s)

FOREACH p in p(s)

IF the feasibility rules succeed for the inclusion of p in M(s) THEN

Compute the state S obtained by adding p to M (s)

CALL Match (s’)

END IF

END FOREACH

Restore data structures

END IF

END PROCURE Match

rusmart 2013 presentation

Technology