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An Open Proximity Model for Service Discovery in Pervasive Computing
Victor Ramiro Cid
Profesor Guía: Éric Tanter
Miembros de la Comisión: Johan Fabry
Patricio InostrozaLuciano Ahumada
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Contents
1. Motivation and Context
2. Open Proximity Model
3. Open Proximity Model in AmbientTalk
4. Conclusions and Perspectives
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Motivation and Context
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Pervasive Computing
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Pervasive Computing
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Service Discovery
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Service Discovery
Advertising
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Service Discovery
Advertising
Querying
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Service Discovery
Advertising
Querying
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Service Discovery
Advertising
Querying
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Service Discovery - Client
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Service Discovery - Client
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What about the User?
Service Discovery - Client
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We want calm!
Service Discovery - Client
User Overwhelmed
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Service Discovery - Service
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Service Discovery - Service
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Service Discovery - Service
What about the Service?
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Service Discovery - Service
We want calm!
Service Overwhelmed
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Motivation
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Motivation
“Scalability is a critical problem in pervasive computing.” [Satyanarayanan 2001]
The density of interactions with any particular entity falls off as one moves away from it. [Satyanarayanan 2001]
Designers should divide the work into physical environment with boundaries that demarcate their content. [Kindberg 2001]
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Motivation
“Scalability is a critical problem in pervasive computing.” [Satyanarayanan 2001]
The density of interactions with any particular entity falls off as one moves away from it. [Satyanarayanan 2001]
Designers should divide the work into physical environment with boundaries that demarcate their content. [Kindberg 2001]
An Open Proximity Model for Scoping Service Discovery in
Pervasive Computing
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Contribution
SoftwareEngineering
DistributedSystems
Networking
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Contribution
SoftwareEngineering
DistributedSystems
Networking
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Open Proximity Model
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Proximity is defined as the state, quality, sense, or fact of being near or next
Proximity as a Concept
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Proximity is defined as the state, quality, sense, or fact of being near or next
• Taxonomy
• Physical and Abstract
• Objective and Subjective
Proximity as a Concept
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Proximity is defined as the state, quality, sense, or fact of being near or next
• Taxonomy
• Physical and Abstract
• Objective and Subjective
Proximity as a Concept
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Proximity is defined as the state, quality, sense, or fact of being near or next
• Taxonomy
• Physical and Abstract
• Objective and Subjective
Proximity as a Concept
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Proximity is defined as the state, quality, sense, or fact of being near or next
• Taxonomy
• Physical and Abstract
• Objective and Subjective
Proximity as a Concept
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Proximity relationships (PR)
• Open and Idiosyncratic
• Composable
• Distributed Evaluation
• Dynamic
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Proximity relationships (PR)
• Open and Idiosyncratic
• Composable
• Distributed Evaluation
• Dynamic
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Proximity relationships (PR)
• Open and Idiosyncratic
• Composable
• Distributed Evaluation
• Dynamic
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Proximity relationships (PR)
• Open and Idiosyncratic
• Composable
• Distributed Evaluation
• Dynamic
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Proximity relationships (PR)
• Open and Idiosyncratic
• Composable
• Distributed Evaluation
• Dynamic
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Open Proximity Model in a nutshell
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Open Proximity Model in a nutshell
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Open Proximity Model in a nutshell
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Open Proximity Model in a nutshellProximity: Accept all incoming jobs from DCC in the 3rd floor
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Open Proximity Model in a nutshellProximity: Accept all incoming jobs from DCC in the 3rd floor
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Open Proximity Model in a nutshellProximity: Accept all incoming jobs from DCC in the 3rd floor
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Open Proximity Model in a nutshell
DCC PDA
Proximity: Accept all incoming jobs from DCC in the 3rd floor
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Open Proximity Model in a nutshell
DCC PDA
Proximity: Accept all incoming jobs from DCC in the 3rd floor
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Open Proximity Model in a nutshell
Print Job
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Model Components
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Model Components
Object
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Model Components
PropertiesObject
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Model Components
ƒ
Proximity FunctionPropertiesObject
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Model Components
+ + ƒ
Proximity FunctionPropertiesObject
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Model Components
+ + ƒ
Proximity FunctionPropertiesObject
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Basic evaluation strategy
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Multicast
Selective evaluation strategy
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Multicast
Selective evaluation strategy
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Multicast
Selective evaluation strategy
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Multicast
Selective evaluation strategy
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Multicast
Selective evaluation strategy
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Multicast
Selective evaluation strategy
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Multicast
Selective evaluation strategy
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Staged evaluation strategy
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Staged evaluation strategy
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Staged evaluation strategy
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Staged evaluation strategy
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Staged evaluation strategy
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Staged evaluation strategy
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• Compose functions as boolean formulas
• Tree composite
• Internar nodes: Operations
• Leaves: simpler functions
• Short-circuit evaluation
• Distributed evaluation
• Must be done by the programmer
Composite Proximity
OR
AND
f1 f2
AND
OR
f5f4
f3
(f1 && f2) || (f3 && (f4 || f5))
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Open Proximity Model in AmbientTalk
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AmbientTalk
• Distributed object-oriented language (Prototype-based)
• Event-driven concurrency based on actors [Agha86]
• Asynchronous message sends, with non-blocking futures
• Built-in engine for service discovery of remote objects
• Extensible language
• Powerful reflective and meta-programming layer
• Block closures, keyworded messages, interface with JVM
AmbientTalk: the project
• Started in 2005
• Small team: 3-6 people
• Interpreter
• Pure Java implementation
• Runs on J2ME/CDC phones
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Service Discovery in AmbientTalk
AdvertisingQuerying
def hp := Printer.new(...);export: hp as: PrinterServer;
when: PrinterServer discovered: {|printer|printer<-addJob(job);
}
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Extended Service Discovery in AmbientTalk
def hp := Printer.new(...);export: hp with: s_props in: euclidean(s_props,radius);
when: PrinterServer discovered: {|printer|printer<-addJob(job);
}with: c_props in: euclidean(c_props,radius);
QueryingAdvertising
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Properties Syntax
• AT objects with new semantics (extended Mirror)
• They can capture variables from their lexical scope
• Changed normal object behaviour through MOP
• invokeField
• pass (serialization)
def props := properties:{
deftype PeerNode;
def name := “Smith”;
def x() {gps.getX()};
def y() {gps.getY()};
};
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Properties Syntax
• AT objects with new semantics (extended Mirror)
• They can capture variables from their lexical scope
• Changed normal object behaviour through MOP
• invokeField
• pass (serialization)
def props := properties:{
deftype PeerNode;
def name := “Smith”;
def x() {gps.getX()};
def y() {gps.getY()};
};
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Properties Syntax
• AT objects with new semantics (extended Mirror)
• They can capture variables from their lexical scope
• Changed normal object behaviour through MOP
• invokeField
• pass (serialization)
def props := properties:{
deftype PeerNode;
def name := “Smith”;
def x() {gps.getX()};
def y() {gps.getY()};
};
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Properties Syntax
• AT objects with new semantics (extended Mirror)
• They can capture variables from their lexical scope
• Changed normal object behaviour through MOP
• invokeField
• pass (serialization)
def props := properties:{
deftype PeerNode;
def name := “Smith”;
def x() {gps.getX()};
def y() {gps.getY()};
};
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Proximity Function Syntax• They are not sent through the network
• They can capture variables from their lexical scope
• Special mapping of formal parameters based on name convention
• The formal parameters are looked up in the target properties set
def euclidean(props, radius){ { |x,y,name| def d := ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt(); (d < radius).and: { (props.name <=> name) != 0 }; };};
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Proximity Function Syntax• They are not sent through the network
• They can capture variables from their lexical scope
• Special mapping of formal parameters based on name convention
• The formal parameters are looked up in the target properties set
def euclidean(props, radius){ { |x,y,name| def d := ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt(); (d < radius).and: { (props.name <=> name) != 0 }; };};
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def euclidean(props, radius){ def f := Functor.new( {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}); def g := Functor.new({|name|
(props.name <=> name) != 0 }); def composite := And.new(f,g); composite;};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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def euclidean(props, radius){ def f := Functor.new( {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}); def g := Functor.new({|name|
(props.name <=> name) != 0 }); def composite := And.new(f,g); composite;};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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def euclidean(props, radius){ def f := Functor.new( {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}); def g := Functor.new({|name|
(props.name <=> name) != 0 }); def composite := And.new(f,g); composite;};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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def euclidean(props, radius){ def f := Functor.new( {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}); def g := Functor.new({|name|
(props.name <=> name) != 0 }); def composite := And.new(f,g); composite;};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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def euclidean(props, radius){ composite: {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}and: {|name| (props.name <=> name) != 0 };
};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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def euclidean(props, radius){ composite: {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}and: {|name| (props.name <=> name) != 0 };
};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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Syntactic Sugar
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def euclidean(props, radius){ composite: {|x,y| ((props.x - x).expt(2) +
(props.y - y).expt(2)).sqrt() < radius)}and: {|name| (props.name <=> name) != 0 };
};
Proximity Function Syntax• Composite to represent composition of functions
• Basic functions is a Functor
• Composite nodes are Boolean operations And/Or
• Evaluation is bottom-up, optimizing boolean cases (Order matters!)
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Syntactic Sugar
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Experiment Setup
5 nodes20 connections
5 nodes20 connections
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Experiment Setup
5 nodes20 connections
8 nodes56 connections
5 nodes20 connections
5 nodes20 connections
15 nodes210 connections
Connections ≈ O(n2)28
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Major Results
• Network layer used for service discovery in AmbientTalk:
• Does not meet all requirements needed to extend the service discovery
• Problems with:
• Measure data collision
• Define transmission velocity and retransmission rates
• Use of Java scheduler to measure time and not real scale time
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Major Results
0
100.000
200.000
300.000
400.000
2 5 10 15 20 25 30 35 40 45 50
Dat
a se
nt (K
B)
Number of Nodes
AT2 OPM
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Major Results
0
1.000
2.000
3.000
4.000
0 10 100 1000 10000
Sen
t D
ata
(KB
)
Properties array size
BES SES StES
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Conclusions and Perspectives
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Conclusions
1. Proximity Taxonomy and Proximity Relationships
2. Open Proximity Model
2.1.Three evaluation strategies proposed
2.2.trade-off between simplicity and efficiency
3. Open Proximity Model in AmbientTalk
3.1.Use of reflection and meta-programming facilities is very helpful
3.2.AmbientTalk’s network layer fails to meet several networks requirements
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Perspectives
1. Improvements on OPM in AmbientTalk
2. A new communication layer for AmbientTalk
3. Publish-Suscribe Service Discovery
4. Context awareness
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GRACIAS!!!
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