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Sogang University ICC Lab
Sensor Networks
- Introduction
Sogang University ICC Lab.2
목차
센서 네트워크 개요
센서 네트워크 플랫폼
센서 네트워크 MAC
센서 네트워크 라우팅
센서 네트워크 응용
센서 네트워크 표준화
Sogang University ICC Lab.3
센서 네트워크 개요 Definition
Network of sensor nodes with computation, sensing, wireless
communication capabilities
What we can do with Sensor Netowkrs?
Sensing (Actuation) : Motion -> Image -> Classification
Collaboration:
Mobile sensors: tracking
Sogang University ICC Lab.4
센서 네트워크 개요 Features
Embedded computer with sensors and radios
Sensing target in proximity
Large number of densely distributed nodes
Multi-hop, wireless, ad hoc network
Sensing, processing, communication, actuation
Sogang University ICC Lab.5
센서 네트워크 응용 서비스
Sogang University ICC Lab.6
Hardware Platforms Crossbow (Mica Series)
Intel Mote (iMote)
Moteiv (Telos, Tmote SKY)
Maxfor (TIP 시리즈 )
옥타컴 (Nano-24)
Sogang University ICC Lab.7
Crossbow (Mica Series) 미국 버클리대학에서 미국 국방성의 DARPA 프로젝트 스폰서를 받아 개발
현재 가장 범용적으로 사용되는 하드웨어 플랫폼
Rene, dot, Mica, Mica2, MicaZ
TinyOS, 각종 시뮬레이터 및 다양한 공개 응용이 제공됨
메인보드에 온도 , 조도 , 지자기 센서 등의 센서를 스택 형식으로 장착 가능
Sogang University ICC Lab.8
Intel Mote (iMote) UC Berkeley 와 Intel Research Berkeley Lab 에서 공동 연구로 개발
ARM 기반의 마이크로 프로세서 사용
32bit ARM7TDMI CPU 사용
센싱 정보의 복잡한 계산이나 상위 레벨의 복잡한 정보 처리 가능
Zeevo 社의 2.4GHz 대역의 Bluetooth 사용
최대 720kbps 전송률 지원
cf) ZigBee 의 경우 250kbps
TinyOS 를 ARM instruction set 에
맞게 포팅하여 사용
http://www.intel.com/research/
exploratory/motes.htm
Sogang University ICC Lab.9
Moteiv (Telos, Tmote SKY) MCU 로는 Texas Instruments 社의 MSP 430 사용
짧은 wake-up time (6μs), 낮은 소모 전력 (Active: 15mW,
Sleep: 15μW), 낮은 동작전원 ( 최소 1.8V)
cf) ATmega128 의 경우 180μs, 33mW, 75 μW, 2.7V
RF 모듈로 Chipcon 사의 CC2420 칩 사용
센서 노드용 OS 로 TinyOS 사용
http://www.moteiv.com/
Sogang University ICC Lab.10
Maxfor (TIP 시리즈 ) 한국전자부품연구원 (KETI) 에서 개발
TIP 3X 시리즈
MCU: ATMega 128L
900MHz 대의 RF 칩 사용 (Chipcon 社의 CC1000)
TIP 5X, 7XX 시리즈
MCU: MSP430
2.4GHz 대역의 RF 사용 (Chipcon 社의 CC2420)
센서 운영체제로 TinyOS 사용
http://www.maxfor.co.kr/
Sogang University ICC Lab.11
옥타컴 (Nano-24) ETRI 에서 개발한 센서 노드 운영체제인 Nano-Qplus 사용
Crossbow 社의 MicaZ 와 유사한 보드 구성
Atmega 128L CPU 사용
Chipcon 社의 CC2420 RF 칩 사용
조도 , 온도 , 습도 , 적외선 , 가스 , 초음파 , 가속도 센서등 다양한
종류의 센서를 스택형식으로 장착 가능
Sogang University ICC Lab.12
옥타컴 (Nano-24)
Nano-24 메인 모듈
Sogang University ICC Lab.13
옥타컴 (Nano-24)
Sogang University ICC Lab.14
센서 네트워크 운영체제 TinyOS
SOS
MANTIS
나노 Qplus
Sogang University ICC Lab.15
센서 운영체제 요구 사항 제한된 자원의 효율적 사용을 위해 저전력 통신을 지원해야 하고 ,
프로세서의 메모리 영역의 효율적인 관리를 수행해야 함
센서노드는 설치된 후 유지보수가 어려우므로 동적으로 환경에 적응 할
수 있는 능력 필요
센서 노드의 통신 거리 제약을 극복하기 위해 멀티 홉 라우팅 지원
응용 프로그래머들의 손쉬운 프로그래밍을 위한 API 제공
Sogang University ICC Lab.16
TinyOS UC 버클리의 Smart dust 프로젝트에서 개발
이벤트 발생 중심의 상태 변화 방식
효율적인 CPU 사용
슬립모드 지원
nesC
센서 네트워크용 프로그래밍 언어
동적 메모리 할당 사용 안함
안정성을 위해 전체 프로그램에 대한 분석을 통해 최적화 수행
컴포넌트 기반의 언어
멀티 홉 라우팅 제공
추가 모듈 지원 : TinyDB, TinySec
Sogang University ICC Lab.17
TinyOS
컴포넌터 기반의 TinyOS 예제
Sogang University ICC Lab.18
SOS Mote 계열 기반의 센서 네트워크 지원을 목적으로 UCLA 에서 개발
메시지 패싱 , 동적 메모리 할당
Common Kernel 지원
커널의 동적 재구성 지원
무선 네트워크를 통해 센서 노드의 소프트웨어 업데이트 수행
응용 애플리케이션은 하나 이상의 모듈로 구성
비동기 메시지 및 함수 호출을 통해 서로 동작함
Sogang University ICC Lab.19
MANTIS 콜로라도 대학에서 개발된 센서 네트워크용 임베디드 운영체제
초소형 스레드에 기반한 멀티 스레드 구조
일반 프로그래머들이 익숙한 구조
특징
레이어 기반 운영체제
멀티 스레딩 지원
Preemptive 스케줄링
Mutual exclusion 을
통한 I/O 동기화
하드웨어를 추상화
시키는 디바이스 드라이버
Sogang University ICC Lab.20
나노 -Qplus 한국전자통신연구원 (ETRI) 에서 개발된 센서 네트워크 운영체제
특징
에너지 소모를 최소화하기 위해 노드들간의 시간 동기화 기법을
제공
멀티 스레드간의 스택을 공유하여 메모리 사용을 줄일 수 있음
멀티 스레드 스케줄러 방식
실시간 운영체제 (RTOS) 지원
C 기반의 응용프로그램 개발환경 지원
Sogang University ICC Lab.21
나노 -Qplus 구조
Nano-HAL (Nano Hardware Abstract Layer)
• 하드웨어를 추상화하기 위해 개발된 디바이스 드라이버 영역
• LED, Clock. Power, RF 모듈 , UART, ADC
태스크 스케줄러 (Task scheduler)
• Linux 스타일의 스케줄러와 유사
• 저전력 및 효율적인 리소스 관리 제공
• POSIX 스레드 기반의 API 를 통해 멀티 스레드간 메시지 전달
Sogang University ICC Lab.22
나노 -Qplus 동적 전원관리
• 처리할 태스크가 없을 경우 전원 소비가 늦은 실행모드로 전환
RF 메시지 핸들링
• IEEE 802.15.4 기반의 멀티홉 라우팅 형성을 돕는다 .
시간 동기화
• 노드들 사이의 듀티 사이클을 조정하기 위한 모듈이다 .
• 트리기반의 시간 동기화 기법 제공
Sogang University ICC Lab.23
나노 -Qplus
Nano-Qplus 구조
Sogang University ICC Lab.24
센서 네트워크 MAC IEEE 802.15.4 MAC
S-MAC
B-MAC
Sogang University ICC Lab.25
센서 MAC 개요 Low-power capacities lead to limited coverage and
communication range for sensor nodes
The primary objective in wireless sensor networks design is
maximizing node/network lifetime.
The communication of sensor nodes will be more energy
consuming than computation
The medium-access decision within a dense network
composed of nodes with low duty-cycles is a challenging
problem that must be solved in an energy-efficient manner
Sogang University ICC Lab.26
MAC-Layer-Related Sensor Network Properties Reasons of Energy Waste
Collision
Overhearing
Control-packet overhead
Idle listening
Overemitting
Communication Patterns
Broadcast
Convergecast (opposite to broadcast or multicast)
Local gossip
multicast
Sogang University ICC Lab.27
Important Consideration in Wireless Sensor Network MAC Power Consumption
Channel Occupancy
Throughput, Latency & Fairness
Self-Organization and Self-Maintenance
Scalability
Quasi-Stationary Assumption
Unlicensed Frequency Bands
Sogang University ICC Lab.28
IEEE 802.15.4 MAC
Upper Layers
IEEE 802.2 LLC Other LLC
IEEE 802.15.4
2400 MHz
PHY
IEEE 802.15.4
868/915 MHz
PHY
IEEE 802.15.4 Architecture
Sogang University ICC Lab.29
IEEE 802.15.4 MAC Overview Star and peer-to-peer topologies
Employs 64-bit IEEE & 16-bit short address
Two devices specified
Full Function Device (FFD)
Reduced Function Device (RFD)
Sogang University ICC Lab.30
IEEE 802.15.4 MAC Overview Simple frame structure
Reliable delivery of data
Association/disassociation
AES-128 security
CSMA-CA channel access
Optional superframe structure with beacons
GTS (Guaranteed Time Slot) mechanism
Sogang University ICC Lab.31
IEEE 802.15.4 Devices Full function device (FFD)
Any topology
PAN coordinator capable
Talk to any other devices
Implements complete protocol set
Sogang University ICC Lab.32
IEEE 802.15.4 Devices Reduced function devices (RFD)
Limited to star topology or end-device in a peer-to-peer
network
Cannot become a PAN coordinator
Talks only to a network coordinator
Very simple implementation
Reduced protocol set
Sogang University ICC Lab.33
IEEE 802.15.4 Definitions Network devices: An RFD or FFD implementation containing an
IEEE 802.15.4 medium access control and physical interface to
the wireless medium.
Coordinator: An FFD with network device functionality that
provides coordination and other services to the network.
PAN Coordinator: A coordinator that is the principal controller
of the PAN. A network has exactly one PAN coordinator
Sogang University ICC Lab.34
Full function device
Reduced function device
Communications flow
Master/slave
PANCoordinator
IEEE 802.15.4 MAC- Star Topology -
Sogang University ICC Lab.35
Full function device Communications flow
Point to point Cluster tree
IEEE 802.15.4 MAC- Peer-to-Peer Topology -
Sogang University ICC Lab.36
Full function device
Reduced function device
Communications flow
Clustered stars - for example,cluster nodes exist between roomsof a hotel and each room has a star network for control.
IEEE 802.15.4 MAC- Combined Topology -
Sogang University ICC Lab.37
IEEE 802.15.4 MAC Addressing All devices have IEEE addresses (64 bits)
Short address (16 bits) can be allocated
Addressing modes
PAN identifier (16bits) + device identifier (16/64 bits)
• 0x0000 – 0xfffd
• 0xfffe, 0xffff
• Beacon frame: no destination address
Sogang University ICC Lab.38
Data Service Data transfer to neighboring devices
Acknowledged or unacknowledged
Direct or indirect
Using GTS service
Maximum data length (MSDU)
aMaxMACFrameSize (102 bytes)
Sogang University ICC Lab.39
S-MAC (Sensor-MAC)The main features of S-MAC are: Periodic listen and sleep
Each node goes into periodic sleep mode during which it switches the radio off and sets a timer to awake later
Collision and Overhearing avoidance Message passing
Sogang University ICC Lab.40
S-MAC
Choosing and Maintaining Schedules
Schedule table
• The schedules of all its known neighbors
Maintaining Synchronization
SYNC packet
• The address of the sender and the time of its next sleep
Adaptive Listening
To switch the nodes from the low-duty-cycle mode to a
more active mode
Sogang University ICC Lab.41
S-MAC
Sogang University ICC Lab.42
B-MAC (Berkeley MAC)
B-MAC’s Goals:
Low power operation
Effective collision avoidance
Simple implementation (small code)
Efficient at both low and high data rates
Reconfigurable by upper layers
Tolerant to changes on the network
Scalable to large number of nodes
Sogang University ICC Lab.43
B-MAC Features
Clear Channel Assessment (CCA)
Low Power Listening (LPL) using preamble sampling
Hidden terminal and multi-packet mechanisms not provided,
should be implemented, if needed, by higher layers
Sleept
ReceiveReceiver
Sleept
PreambleSender Message
Sleep
Sogang University ICC Lab.44
B-MAC Interface
CCA on/off
Acknowledgements on/off
Initial and congestion backoff in a per packet basis
Configurable check interval and preamble length
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Constraints No centralized coordinator
Dynamic network topology
Bandwidth constrained wireless links
Careful resource management
Transmission power
On-board energy
Processing capacity
Storage
Channel access availability
Hidden/Exposed terminal problem
Lack of symmetrical links
Sogang University ICC Lab.46
Sensor Network Architecture
Sensor Nodes
Sink
Internet 및 기존 유무선 망
Task Manager User
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System Architecture & Designing
Network Dynamics
Mobile or Stationary nodes
Static Events (Temperature)
Dynamic Events ( Target Detection)
Node Deployment
Deterministic – Placed manually
Self-organizing – Scattered randomly
Sogang University ICC Lab.48
System Architecture & Designing
Energy Considerations
Direct vs. Multi-hop communication
• Direct Preferred – Sensors close to sink
• Multi-hop – unavoidable in randomly scattered
networks
Data Delivery Models
Continuous
Event-driven
Query-driven
Hybrid
Sogang University ICC Lab.49
System Architecture & Designing Node Capabilities
Homogenous
Heterogeneous
Nodes dedicated to a particular task (relaying, sensing,
aggregation)
Data Aggregation/Fusion
Aggregation – Combination of data by eliminating redundancy
Data Fusion is Aggregation through signal
processing techniques
Aggregation achieves energy savings
Sogang University ICC Lab.50
센서 라우팅 분류
Routi ng Protocol s
Network Structure Protocol Operati on
Fl atNetworksRouti ng
Hi erarchi calNetworksRouti ng
Lacati onBased
Routi ng
Negoti at i onbased
Routi ng
Mul t i -pathbased
routi ng
Querybased
routi ng
QoSBased
Routi ng
Coherentbased
Routi ng
Sogang University ICC Lab.51
센서 라우팅 예시
Data Centric Protocols
SPIN , Directed Diffusion
Hierarchical Protocols
LEACH
Location Based Protocols
GAF , GEAR
Sogang University ICC Lab.52
Sink sends queries to certain regions and waits data from sensors
located in that region
Attribute-based naming is necessary to specify properties of data
Data Centric Routing
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Data Centric Routing Flooding
Gossiping
Sensor Protocols for Information via Negotiation (SPIN)
Directed Diffusion
Energy-aware Routing
Rumor Routing
Gradient-Based Routing (GBR)
Constrained Anisotropic Diffusion Routing (CADR)
COUGAR
ACtive QUery forwarding In sensoR nEtworks (ACQUIRE)
Sogang University ICC Lab.54
Data Centric Routing Flooding
Sensor broadcasts every packet it receives
Relay of packet till the destination or maximum number of
hops
Causes Implosion, Overlap & Resource Blindness
Gossiping
Enhanced version of flooding
Sends received packet to a randomly selected neighbor
Problems of Implosion, Overlap, Resource Blindness
Sogang University ICC Lab.55
SPIN
Network-wide Broadcast Limited by Negotiation and using
Local Communication
Flooding problems:
Implosion – same data from many neighbors
Detection of overlapping regions
Excessive resources consumption (Blindness)
Needs only Localized Information
Data Fusion
Two main protocols SPIN-PP & SPIN-BC
Sogang University ICC Lab.56
Data Aggregation
Methods of Aggregation
Duplicate suppression
Aggregate functions like Avg,Min,Max etc
Data Aggregation Trees
Center At Nearest Source
Shortest Path Tree
Greedy Incremental Tree
Sogang University ICC Lab.57
Data is described by meta-data ADV msg. Node has data sends ADV to neighbors If neighbor do not have data sends REQ Node responds by sending the DATA This process continues around the network Nodes may aggregate their data to ADV In a Lossy Network ADV may be repeated periodically and REQ if not
answered
SPIN-PP (Point-to-Point Communication)
Sogang University ICC Lab.58
ADV and DATA sending like PP (but in B.C.)
Since only one REQ answer is needed, any node waits a random
interval and B.C. REQ only if none was received yet.
The rest – like SPIN-PP
SPIN-BC (Local Broadcast Communication)
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ADVNode with data
Node with data advertises to all its neighbors
Example of SPIN-PP
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REQNode with data
Neighbor requests for data and it is sent
Example of SPIN-PP
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DATA Node with data
Node with data advertises to all its neighbors
Example of SPIN-PP
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Node with dataADV
Receiving node sends ADV to neighbors
Example of SPIN-PP
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Node with data
Receiving neighbors requests for data.
REQ
Already has data(or dead)
Example of SPIN-PP
Sogang University ICC Lab.64
Node with data
DATA
Receiving node sends ADV to neighbors
Example of SPIN-PP
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Directed Diffusion
Sensor node names data with one or more attributes that it
generates
Other nodes express interests based on these attributes
Sink nodes query sensor network for information from a
particular section of the terrain
Sogang University ICC Lab.66
Directed Diffusion
Network nodes propagate interests
Interests establish gradients that direct diffusion of data
Path of interest propagation sets up a reverse data path for
data that matches the interest
As it propagates, data may be locally transformed (e.g.
aggregated) at each node, or be cached
Rest is similar to conventional routing
Sogang University ICC Lab.67
Directed Diffusion - Rules for Interests and Gradients -
What are the local rules for propagating interests? E.g., just flood interest More sophisticated techniques possible: directional interest
propagation, based on cached aggregate information What are the local rules for establishing gradients?
In example, highest gradient towards neighbor who first sends interest
Others possible e.g., towards neighbor with highest remaining energy
Sogang University ICC Lab.68
Directed Diffusion - Data Transmission Choices -
Different local data forwarding rules can result in different
kinds of transmission
single path delivery
multi-path delivery, with traffic on each link proportional to
its gradient
• data probabilistically striped along different paths
• redundant delivery across different paths
• layered transmission along different paths
delivery from single source to multiple sinks
delivery from multiple sources to multiple sinks
Sogang University ICC Lab.69
Directed Diffusion - Reinforcement Variants -
Can define several criteria for selecting which path is reinforced
amount of data received from neighbor
loss rates
observed delay variance
Can define local message processing or state aging rules that
allow variants of reinforcement behavior
reinforce a small number of source-sink paths (instead of
one)
negatively reinforce a path, because, for example, some
node in the path is running low on resources
Sogang University ICC Lab.70
Example of Directed Diffusion - Interests and Gradients -
Sink
Source
Thickness of line proportional to gradient
Interest
Gradient
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Example of Directed Diffusion - Data Transmission -
Sink
Source
Sogang University ICC Lab.72
Example of Directed Diffusion - Data Transmission -
Sink
Source
Sogang University ICC Lab.73
Example of Directed Diffusion - Data Transmission -
Sink
Source
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Example of Directed Diffusion - Reinforcing Gradients -
Sink
Source
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Example of Directed Diffusion - Reinforcing Gradients -
Sink
Source
Sogang University ICC Lab.76
Example of Directed Diffusion - Reinforcing Gradients -
Sink
Source
Sogang University ICC Lab.77
Example of Directed Diffusion - Reinforcing Gradients -
Sink
Source
Sogang University ICC Lab.78
Hierarchical Protocols
When sensor density increases single tier networks cause
Gateway overloading
Increased latency
Large energy consumption
Clustered Network allow coverage of large area of interest and
additional load without degrading the performance
Sogang University ICC Lab.79
Hierarchical Protocols
Hierarchical routing Uses Multi - hop communication within a cluster Performs data aggregation and fusion on data to reduce number of
transmitted messages to the sink Maintain the energy reserves of nodes efficiently
Example - LEACH, PEGASIS
Sogang University ICC Lab.80
LEACH
Self-Organizing – Adaptive Clustering
Cluster-Heads elect themselves
“Random Round-Robin”
Stationary Sink
Localized Coordination
Data Fusion
Basic Algorithm assumes any node can communicate with sink
– limited scale
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LEACH Operation
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LEACH Operation
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Location Based Protocols
Location information can be used to Find shortest path to the sink Form a virtual grid and keep only few nodes active at a time
Example GAF GEAR
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Determining Location
Location of a node can be determined using
Global Positioning System
Ultrasonic Systems using trilateration
Beacons
Location based protocols assume that each node knows its
location in the network
Sogang University ICC Lab.85
TinyOS Routing Protocol
Tree-based Routing protocol
Constructed and maintained by periodic hello (called
‘RoutePacket’) message exchange
Network Topology is changed through link quality estimation
Support of Broadcast and Multi-hop Routing
Broadcast: sink node to all sensor nodes
• Ex. a command message from sink node to sensor nodes
Multi-hop: each sensor to sink
• All unicast messages of sensor node are sent to its parent
node (ex. sensing message forwarding)
Sogang University ICC Lab.86
TinyOS Routing Protocol
InternetInternet
sink
Tree topology construction
Sogang University ICC Lab.87
TinyOS Routing Protocol
(n+1, 20)
(Hop Count, link quality)
(n, 32)
(n, 17)
(n+1, 40)
(n+2, 23)
(n+1, 22)
(n, 21)
(n,27)
(n+1, 24)
(n+2, 26)
Before RoutePacket exchange, node states
After RoutePacket exchange, link quality estimation update
(n+1, 22)
(n+1, 17)
Forwarding path
Periodic RoutePacket Exchange
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센서 네트워크 응용 구조도
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센서 네트워크 응용 예제
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센서 네트워크 서비스 모델
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국내 센서 네트워크 구축 예
한국전산원
농산물 재배환경 모니터링 시스템
제주 해양환경 정보수집 시스템
한국전자통신연구원 (ETRI)
스마트 오피스
지하 시설물 관리
한국전자부품연구원 (KETI)
산불 모니터링 시스템
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농산물 재배환경 모니터링 시스템
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제주 해양환경 정보수집 시스템
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스마트 오피스 (ETRI)
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지하 시설물 관리 (ETRI)
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산불 모니터링 시스템 (KETI)
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산불 모니터링 시스템 (KETI)
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센서 네트워크 표준 기술
IEEE 802.15.4
IEEE 802.15.4b
ZigBee
IEEE 1451.5
IPv6 over LoWPAN (6LoWPAN) of IETF
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IEEE 802.15.4a Scope and Description:
Develop an alternate physical layer for data
communication with high precision ranging/location
capability/ (1m accuracy and better) , high aggregate
throughput, and ultra low power; as well as adding
scalability to data rates, longer range, and lower power
consumption and cost
The alternate PHY is an (optional) amendment to the
current IEEE 802.15.4-2003 LR-WPAN standard.
802.15.4a became an official Task Group in March 2004;
with its committee work tracing back to November 2002
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IEEE 802.15.4a Current Status
The baseline is two optional PHYs consisting of UWB
impulse Radio (operating in unlicensed UWB spectrum) and
a Chirp Spread Spectrum (operating in unlicensed 2.4 GHz
spectrum)
The UWB Impulse Radio will be able to deliver
communications and high precision ranging
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Overall Enhancements in IEEE 802.15.4b
Added support for distributing a shared time-base
Support for group addressing
Added extensions of the 2.4GHz derivative modulation
Yields higher data rates at the lower frequency bands
Added support of Beacon-Enabled Cluster Tree network
IEEE 802.15.4 does not support while 15.4b does
Protection of broadcast and multicast frame possible
Easier setup of protection parameters possible
Possibility to vary protection per frame, using a single key
Optimization of storage for keying material
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ZigBee Alliance
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ZigBee vs. WLAN vs Bluetooth
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IEEE 1451
The IEEE 1451, a family of Smart Transducer Interface
Standards, describes a set of open, common, network-
independent communication interfaces for connecting
transducers (sensors or actuators) to microprocessors,
instrumentation systems, and control/field networks.
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6LowPAN
IPv6 over Low power WPAN
Why IPv6
More suitable for higher density
Statelessness mandated
No NAT necessary
Possibility of adding innovative techniques as location
aware addressing
IEEE 64 bit address subsumed into IPv6 address
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Challenges of 6LoWPAN