prof. younghee lee 한국정보통신대학교 1 미래 application 들을 위한 network solutions...

1Prof. Younghee Lee 한국정보통신대학교

미래 application 들을 위한 network solutions 에 대한 연구

March 23, 2004Younghee Lee


Content

Requirements for future applications– NGI– Ubiquitous computing

Problems of today’s Internet Possible solutions

– MPLS– Active & programmable network– Overlay network– Ad hoc network, Sensor network– (knowledge plane)

Research activities of cnlab ICU


Requirements for future the Internet applications

NGI– Increased Capability

» Advanced end-to-end networking technologies: Reliability, Robustness, Security, QoS/differentiation of service (incl

uding multicast and video), Network management (Including allocation and sharing of bandwidth)

– Increased Capacity» The “100x” testbed — at speeds 100 times faster end to end than toda

y’s Internet.

– Applications» Collaboration technologies, Digital libraries, Distributed computing, Priv

acy and security, Remote operation and simulation



Networking for Ubiquitous computing (IBM)– Plug-and-play networking– Requires “smarter” infrastructure

» Self configuration» Auto-discovery and Service access

– Proximity based connectivity– Hidden computing– Spontaneous networking– Security and Privacy– Access and connectivity rules


Architecture for pervasive computing system– Networked Apps, API

» Power conscious Apps» HW and middleware aware» Disconnected model when possible

– Middleware/Networking Stacks» Utilizing existing stacks if possible» Lightweight networking for peers» Complexity pushed to infrastructure for Internet access

– Radio/BB/MAC» Integrated RF design» Low power transmitter (1 mW)» Power conscious MAC» Encryption» Ubiquitous system interface



2-5 years later– Environment

» Smart Spaces, Internet Appliances, Things-that-think, Car, Home Networks, Body-on-the-Net

– Technology» Intergrated/embedded Networking (low cost, Low power), "Lightweight" IP and Networking Services, Spontaneous Networkin

g, Wireless, Universal connectivity The future of the Internet is not multimedia(only).

– The future of QoS networks is cloudy– Primary driver for advanced networking?

» The future multimedia applications? or » computer to computer data networking

Challenges in nomadicity: – Location independence, Device independence, Widespread access, Security, Adaptability to new technologies, Fri

endly interface, Partitioning functionality into co-operating software entities



Different applications needs different security services– Confidentiality, Integral, availability, non-repudiation, Access control, Authentication– lacking : authorization and quality of service

Four concrete application areas for further bandwidth usage:– Real-time synchronization: User will have data and media on various devices and in various central server and decentral

(think your P2P storage of movies) places, and user want to have access to this data and media all the time everywhere. – Media usage:If it can take only 10 seconds for movie download, people will use that bandwidth. Then they will sample movi

es and TV and download more. User will share with friends sending a full movie via email like mp3 files? – Life Storage: By far the biggest driver will be the recording, transmission and storage of whole life. (Data, Information, know

ledge, wisdom)– Gaming: When you get real-time 3D worlds inhabited by thousands of avatars interacting with each other, and your local g

aming environment always needs to be on top of all the developments in this world, then your bandwidth usage will skyrocket. NxN multicast



Questions

Network service 측면 :– 어떻게 저 많은 서비스 요구사항을 네트워크가 만족시킬 수 있는지 ?– 현재 망 차원에서는 불가능 ?

Network control 측면 :– 어떻게 저 다양한 응용서비스가 네트워크를 control 하면서 각자의 구미에 맞게끔

네트워크를 이용할 수 있을지 ?– No control plane for application in the Internet(best effort service case)


Problems of today’s Internet

Internet design principles– Internet Architecture : Cerf and Kahn’s internetworking princi

ples:» minimalism, autonomy - no internal changes required to interconnect

networks» best effort service model» stateless routers» decentralized control

Big differences with connection oriented telecommunication networks (PSTN, PSDN, ATM,…)


Problems of today’s Internet Internet design principles

– End-to-End Argument» If the application can implement a functionality correctly, implement it a lower layer only as a perfo

rmance enhancement Application has more information about the data and the semantic of the service it requires (e.

g., can check only at the end of each data unit) A lower layer has more information about constraints in data transmission (e.g., packet size, e

rror rate)» Rule of Thumb

Implementing a functionality at a lower level should have minimum performance impact on the application that do not use the functionality

» What About Other Services?: Multicast? Quality of Service (QoS)?


Why Is It Not Happening? Network QoS model is too primitive.

– Large gap between network and application QOS

– Too low level; hard to use Applications have insufficient informati

on about the network to make informed decisions.

– Am I using a modem or a gigabit Ethernet?

– Where can I get more bandwidth Service providers have little control ov

er how their traffic is handled.– No customization

Implication to active network, overlay network, ad hoc network?

Knowledge plane?

DistributedSimulation

DistanceLearning

VideoConferencing

GamesUser User

Too ComplexNo

InformationNo Control


Problems of the Global Internet

Problems and requirements– Various Internet attackers: spam e-mail,..

» Need protect users and network itself from attacker

– ISP Service differentiation: QoS– Third party’s involvement

» 정부 , ISP 등이 위해정보 차단 , 세금징수 등 ..

– Multiway communication– Firewall in the network, traffic filters, NAT for address space management– (Congestion control, incentive)

How can we solve all these problems or requirements of the Global Internet ?

– Location?– Labeling for packet discrimination?…– How to improve and evolve current Internet respecting e2e argument principle?


Network processor

Today’s gateways and backbone routers can never be fast enough– Cannot keep up with fiber capacity– Cheap, monolithic “superprocessor” : Intel IXP nnnn

» Replacing rack-mount routers» Also processing higher layer protocol» QoS, encryption


MPLS

QoS routing?– Bandwidth?, Delay? – Delay-constrained least cost (NP-complete)

DiffServ, IntServ Stateless or stateful ?

– Challenge: features of stateful solutions, but at the cost of stateless solutions

– Can MPLS be a candidate ? » Differentiate flows for optimum performance and services

Push complexity of control plane to data plane» Positive. But what about IP network design principle? : Stateless


Programmable Platforms

Stateful solutions need a complex control plane– Control plane: difficult to develop and debug– open flexible control plane

Open programmable interface (API) – user, network node, third party : resource manipulate or repro

gram– open signaling: IEEE 1520

Related standard– IETF General Switch Management Protocol(GSMP)– Forwarding and Control Element Separation (ForCES)– The Multiservice Switching Forum (MSF)


Various active network research(mostly funded by DARPA)– ANTS/PAN ( MIT), SwitchWare (Upenn), Liquid Software (Arizona), NetScr

ipt (Columbia), Janos (Utah), ANTS/Detour (Washington), OpenetLab (Nortel), CANES (Georgia Tech), Genesis (Columbia), Panda (UCLA), Smart Packets (BBN), DARWIN (CMU), Active Networks and Novel Network Management Technology (GE), ABLE (Bell Labs)

– Very active until 2000» About 6 projects are active now in US » Activeware (MIT) Liquid Software (U. Arizona) Scout Operating System (U. Arizona) Spin Oper

ating System (U. Washington) Switch Ware Project (Upenn NOW Network of Workstations (U. Berkeley)

FAIN(Future Active IP Networks)– R&D project under the Information Society Technologies (IST) program : 3

years from 2000 funded by Commission of the EU– Various European countries, Hitachi, Upenn– open, flexible, programmable and dependable (reliable, secure, and mana

geable) network architecture based on novel active node concepts.

Active Networks


– “programmability into the network”, – “new services are introduced fast”.– Problems

» What is the killer application? Incentive?» Need of processing power

– end to end argument point of view» contradict the end-to-end principle: a function or service should be

carried out within a network layer only if it is needed by all clients of that layer

» consonant with end-to-end arguments: programmability may allow a network client to implement precisely the service it needs, an outcome

Active Networks


Active networks for something

Execution at right place; – Something would prefer to be executed at intermediate node rather than e

nd node

Characteristics of functions – closely related with network control or node data manipulation

» Congestion, multicast, QoS, sensor node,…

– reactive on right time at right place» Adaptive to network changes or context changes» For pervasive computing

Context => event => service– How to describe service?: service description – How to discover optimum service?: service discovery– How to execute them on right time at right place?: agent

– application specific and temporal only to certain application» If it’s common to every application, we don’t need active networking


Active networks for something(1)

Active networking for the GRID– Active P2P Grid architecture– Self-adapting, self-configurable, self manageable grids

Active overlay network– Application Level Active Networks (ALAN)

Active sensor network– Adaptive to network situation, decided by application– Active routing for ad-hoc network: Seamless integration

Programmable network management– Applying Active networks to Network management

» Smart Packets(BBN)


Active networks for something(2)

Active Networking in Pervasive Computing– situation(context) aware, dynamic, adaptive,….

– Mobility discovery– Pan-network server service – Agent: execution on behalf of application at better place

Active Networking for OPES– OPES: Services deployed at application level intermediaries i in the network to tran

sform filter content » Caching, virus scanning, language translation, … , …

– Active node to execute the code for specific application» Message containing the code or rule set

video transcoding, virus filter and so on... Active networking for knowledge plane concept

– Knowledge based network control for effective network– Agent execution for various applications– Information gathering, knowledge discovery, …


Overlay Network

Motivations– Changes in the network happen very slowly– Why?: Network services are end-to-end– Proposed changes that haven’t happened yet:

» Congestion (RED ‘93); More Addresses (IPv6 ‘91), Security (IPSEC ‘93); Multi-point (IP multicast ‘90)

An isolated virtual network deployed over an existing network

– Composed of Hosts, Routers, Tunnels– IP service: e2e datagram service – Multicast, QoS services need stateful protocols only for control

state over IP networks => e2e edge/overlay service – Application level intermediaries


Overlay Network

New service deployment without network updates– Performance drawback compared to the case with network updates

Potential Benefits– Easier to deploy

» only requires adding software to end hosts

– Potentially simplifies support for higher level functionality» leverage computation and storage of end systems

e.g., packet buffering, transcoding of media streams, ACK aggregation

» leverage solutions for unicast congestion control and reliability


Overlay Network: applications Applications

– Multicast– Quality of Service– Mobility– Addressing: 6bone, IP-NL ; enhanced NAT– Security– Web caching, CDN, P2P

» Related IETF activities Web Replication and Caching (WREC)

– Taxonomy, requirements Content Delivery Internetworking (CDI)

– Settlements, SLAs, property rights Web Intermediaries (WEBI)

– Content Invalidation Protocol Open Pluggable Edge Services (OPES)

– Rules-based invocation of proxylet services


Overlay multicast: (Overcast)

Scalable, efficient, and reliable distribution of high quality video Large groups ~ millions of nodes

– Typical application: content distribution

Designed for throughput intensive content delivery– Streaming, file distribution– Not good for gaming application: latency problem

Server based infrastructure ICU :

– 1 to N, N to N multicast for streaming service– High performance forwarding engine in kernel level


Knowledge Plane

Concern over risks of increased reliance on networks– The role of the network is growing more quickly than our ability to manage – Network-centric warfare has promise and peril– The civilian economy is alternately helped and hurt by the Internet

Key Idea: The Internet Knowledge Plane as a basis for making progress in cognition while exploring a new vision for network architecture

– New “collective cognitive” mechanisms for supporting cooperation and learning

– A coherent management infrastructure for the Internet that does not compromise its strengths ;e2e

– Additional military benefits: quick deployment, more effective networks, and reduced reliance on human experts

초기개념 형성단계 다양한 응용서비스가 필요한 지식정보를 공유 : 응용별로 망 구성을 위한

별도의 정보 획득 및 조치 불 필요


Knowledge plane:

E

• Element failures

• Misconfiguration

• Attacks

•Departures from expectation

• Departures from design

K-Application “Why?”:Network fault detection, isolation, and repair

Models

Models ofInternet structure,

application behavior,

requirements

K-Base

Inferencerules,

diagnosticprocedures

ActionPerception

THE KNOWLEDGE PLANE

Sensors Actuators

E

E

E


Knowledge plane:Technology Foundations

Bayes belief nets, machinelearning, genetic algorithms,neural networks, expertsystems

Active Networks, Sensor Nets,CoABS, various overlaynetworks

DASADA, NMS

Domain-specificlanguages

Distributed Hash Tables (DHTs)

Algorithmic game theory

RKF, DAML,KnowledgeRepresentation,dimensionalityreduction

M P K


Knowledge plane:Technology Foundations


Knowledge plane: summary

An net that builds itself using high-level specification.

Very different net from the Internet.– We might experiment with knowledge overlays

What is different?– Edge-involvement.

» Visibility of “application-level” behavior.– Global perspective.– Compositional structure.– Unified approach.– Cognitive framework


Ad hoc network: application

Military environments: was motivation & strong candidate – soldiers, tanks, planes

» Need mobility, avoid SPF, rapidly deployable, Multi-hop to reach to person outside of LOS(line of sight), when existing infrastructure is unavailable

– Survivable Radio Network(SURAN), Global Mobile(GloMo) Information System Civilian environments

– taxi cab network, automobile communications(Cellular + ad hoc+..)– Meetings/conferences– sports stadiums, super market, Hotel…– boats, small aircraft

Emergency operations– search-and-rescue– policing and fire fighting

Personal area networking– cell phone, laptop, head phone, wrist watch, multimedia devices– Wearable computing


Ad hoc network MANET nodes

– End system and also Network nodes» Discussion: Aspect of “End to End Arguments” in MANET?

– With wireless mobile host– May need multiple hops to reach a destination


Sensor Network Applications of sensor network

– Home network for pervasive computing– Habitat monitoring – Environmental observation and forecasting systems: Columbia River Estuary– Smart Dust– Biomedical sensors– Military applications


Classifications of Sensor Nets Sensor position

– Static (Habitat, CORIE, Biomedical) – Mobile (Smart Dust, Biomedical)

Goal-driven– Monitoring: Real-time/Not-real-time (Habitat, Smart Dust)– Forecasting (CORIE)– Function substitution (Biomedical)– …

Communication medium– Radio Frequency (Habitat, CORIE, Biomedical)– Light (Smart Dust)


Common Challenging Issues Limited computation and data storage

– Sensor design (Multi-objective sensors), Cooperation among sensors– Data aggregation and interpretation

Low power consumption Wireless communication

– Medium, ad hoc vs. infrastructure, topology and routing Data-related issues

– Trade-off between latency and energy: reactive? proactive?– Data representation: Raw/Compressed data– Error calibration: No access to real values, Inferred from other sensors

Continuous operation: Long-term data collection– Renewable power source.: Solar energy, Mechanical vibrations, Radio-Frequ

ency inductance, Infrared inductance Inaccessibility – network adjustment and retasking Robustness and fault tolerance


Uncertain Conclusion

Need many thing between applications and very high speed networks

– Pay too much attention only to HSN?– Intermediaries: Middleware

Interim solution: overlay network? Ultimate solution?

– Knowledge plane?– Totally new global network?

Solutions for local environment?– Sensor network, ad-hoc network, WPAN,…


People– 7 Ph.d students, 4 Ms Students

Research– Network Supports for Pervasive Computing In Home

Networking environments: making home more comfortable, safe and convenient, controlling devices automatically without user’s knowledge

» Pervasive Network Access Zero-configuration performed over entire networks of nodes Mobility management: adaptive mobility

» Context aware semantic service discovery Automatic service discovery with minimized user’s intervention

Computer Network Lab.


Research– Active networking: making the network intelligent and progr

ammable for high quality Internet services » Congestion control, multicast, QoS, sensor network node,…» Reactive on right time at right place

– Overlay Network: making the end node computers working like network nodes immediate new network service

» Overlay multicast: Split -join» Programmable overlay

– Ad hoc network: making the computer nodes to construct the network by themselves

» Ad hoc routing: Proactive-reactive Hybrid type » Address auto-configuration



Research direction– Adaptive networks

» Self configuration: zero configuration Mobile devices, ad hoc devices,…

» Dynamically adapt to the requirements of applications and situation changes

– Service discovery» Semantic service discovery: Currently Home network environment

Inexact matching Interworking between existing middleware ;Jini, Havi, UPnP…

» Extend to Global network environment including mobile network OSGI



Semantic service discovery

Ontologies in home environment– Advantage of our ontology structure

Low complexityEasily define relation between device and serviceEnabling the composition of services and device attributes based quer

y message

AttributeP rimitiveService

Device ServiceState

VariableC ontrol

Interface

Entity

c lass

subc lass

property


Semantic service discovery

Ontology structure Device ontology

A smallest physical unit of providing a service

Service ontology Primitive service composition, and primitive service and device attribute

composition

Primitive service ontology A smallest logical unit of providing service A mediator between device and service

Attribute ontology Device attributes Represent device attribute efficiently

State Variable / Control Interface ontology models state of primitive services with state variables and control primitive

service through control interfaces


Implementation

System Model Jini-based client / service model

LookupServic e

C lient Servic e

Devic e- desc riptionRepository

Servic eProxy

Servic eProxy

4.Discovery&Lookup 1.Discovery & J oin

6.Use

2.Downloaddevice- description

file

5.Receive

O ntology

Evaluator

ReasoningEngine

MatchingManager

3. reasoning & evaluation


Implementation Architecture of Extended Lookup Service

Registry

Inferencing Engine

Evaluator

Matching Manager

Dynamic-valueExtractor

Device descriptionRepository

Device/ServiceDescriptionOntology

Location Server.

Device..

Lookup Service

Service register

Service

Service request message

Client

Service request message

Request dynamic value

Reply dynamic value

Request Reply

Result of evaluationRequest of evaluation

Control

Data

QueryInterpreter


NGIS middleware

NGIS Applications: Internet TV, Multimedia Comm.

IXP 기반의 고성능 인터넷 정합장치IXP 기반의 고성능 인터넷 정합장치

NGIS Middleware Architecture

NGIS 네트워킹 미들웨어NGIS 네트워킹 미들웨어

N to N Multicast- Topology Management

N to N Multicast- Topology Management

1 to N Multicast- Bandwidth Acquisition

1 to N Multicast- Bandwidth Acquisition

Fast Packet Forwarding EngineFast Packet Forwarding Engine

메타데이타 변환 엔진메타데이타 변환 엔진

MPEG-7 Ontology- Ontology Management

MPEG-7 Ontology- Ontology Management

Transformation EngineTransformation Engine

NGIS 미들웨어 구조


Networking Middleware

1-to-N Multicast– Target: High-quality multimedia streaming– Requirement: Bandwidth Stability– Approach: Split & Combine

Level-2

Level-0 : Sender

Level-1



Fast Packet Forwarding Engine– Overlay Multicast 패킷을 적은 Latency 로 Forwarding– Forwarding Engine: Kernel 영역에 위치– buffering 의 최소화



Fast Packet Forwarding Engine– Protocol Update Engine: 현재 등록된 Protocol 의 정보 수정– Protocol Interface: Enhanced Socket Interface for Overlay Multicast

prof. younghee lee 한국정보통신대학교 1 미래 application 들을 위한 network solutions...

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