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Ubiquitous Networks Introduction

Ubiquitous Networks Introduction. Lynn Choi Korea University. Class Information. Lecturer Prof. Lynn Choi, School of Electrical Eng. Phone: 3290-3249, Kong-Hak-Kwan 41 1, lchoi@korea.ac.kr , Time Fri 9:00am – 11:45am Office Hour: Tue 5:00pm – 5:30pm Place Chang-Yi-Kwan 127 Textbook

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Ubiquitous Networks Introduction

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  1. Ubiquitous NetworksIntroduction Lynn Choi Korea University

  2. Class Information • Lecturer • Prof. Lynn Choi, School of Electrical Eng. • Phone: 3290-3249, Kong-Hak-Kwan 411, lchoi@korea.ac.kr, • Time • Fri 9:00am – 11:45am • Office Hour: Tue 5:00pm – 5:30pm • Place • Chang-Yi-Kwan127 • Textbook • Collection of research papers: refer to “Reading List” • References • “Wireless Sensor Networks: An Information Processing Approach”, Feng Zhao and Leonidas Guibas, Morgan Kaufmann, 2004. • “Ad Hoc Networking", Charles E. Perkins, Addison-Wesley, December 2000. • “Wireless Ad Hoc and Sensor Networks: Theory and Application”, Li, Cambridge Press. • Class homepage: http://it.korea.ac.kr

  3. The Content of the Class • We will discuss wireless ad hoc networks. • What is ad hoc networks? • “Ad Hoc” means • “for this purpose only”, “temporary” • “Ad Hoc Network” means • Infrastructure-less network • No wired infrastructure such as base stations, access points, or routers • Self-organizing • Short-lived • Temporary network just for the communication needs of the moment • Dynamic topology • The topology can be changed dynamically due to node mobility, node autonomity, power, failure, etc. • Main topics: networking issues in sensor networks/MANET

  4. Wireless Ad Hoc Network Taxonomy Wireless Networks • Infrastructure-based versus ad-hoc network • Single-hop versus multi-hop wireless links • Hybrid wireless networks • Integration of infrastructure-based and ad hoc networks Infrastructure-based Infrastructure-less Cellular Networks Mobile Nodes Static Nodes Sensor Networks Wireless LANs Mobile Ad Hoc Networks Mobile Sensor Networks

  5. Class Schedule • Sensor Networks (9/6) • Introduction, Sensor Networks • MAC basics (9/13) • WLAN Basics • WPAN (Bluetooth, 802.15.3, 802.15.4/Zigbee) • MAC (9/20) • Introduction S-MAC, WiseMAC, A-MAC/A+MAC, Zero-MAC • Sensor network MAC protocols • Wakeup Scheduling (9/27) • DMAC, SpeedMAC • Clock Synchronization (10/4) • Clock synchronization • Introduction to NTP, TPSN, RBS, FTSP • Routing issues (10/11) • Introduction to Directed Diffusion, TTDD, VSR • Sensor network routing protocols

  6. Class Schedule • Midterm Exam (10/18) • MANET introduction (10/25) • Introduction to DSDV, DSR, AODV • Geographic routing (11/1) • Introduction to GPSR, M-Geocast • Recent MANET/MSN research issues (11/8, 11/15, 11/22) • Mobile sensor networks, ad hoc network community: TAR • Aggregation, reliability, efficient broadcast, clustering • Operating system and programming environment • Cognitive radio, network coding, cooperative networking • QoS, vehicular ad hoc networks • Project presentation (11/29) • Final exam (12/6)

  7. Grading • Midterm: 35% • Final: 35% • Presentation: 15% • 3 presentations per person • Project: 15% • Novel ideas • Experimentation: simulation • Class participation: +/-5%

  8. Ubiquitous NetworksIntroduction to Sensor Networks Lynn Choi Korea University

  9. New Generation of Computing Devices • Bell’s law • New computing class appears every 10 years • 1960’s mainframe • 1970’s minicomputer • 1980’s workstation/PC • 1990’s PC/mobile phones • 2000’s PDA/mobile phones • 2010’s smart phones • 2020’s wearable sensors • Moore’s law • # of transistors per chip doubles every 1~2 years

  10. Computing Generations and Industry IBM, Unisys, HP(Tandem), Fujitsu, Hitachi, NEC DEC, Data General, Apollo, HP IBM System/360 IBM zEnterprise SUN, HP, DEC, SGI, Intel DEC PDP-11 SUN SparcStation 10 MS, Intel, Dell, HP, Compaq, Apple, Motorolla Palm, Compaq, Apple DELL PC IBM PC AT Palm Pilot Apple, Google Apple iPhone Samsung Gallaxy II

  11. What is Wireless Sensor Networks? • Definition • A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. • Application • The development of wireless sensor networks was motivated by military applications such as battlefield surveillance and are now used in many industrial and civilian application areas • Design • Low-power microcontroller with limited memory & storage • Low-power low data-rate RF receiver • Sensors (temperature, GPS, camera, etc.) & Actuators (robots, speaker) • Battery

  12. Vision: Embed the World • Embed numerous sensing nodes to monitor and interact with physical world. • Network these devices so that they can execute more complex task.

  13. Embedded Networked Sensing Applications • Micro-sensors, on-board processing, wireless interfaces feasible at very small scale--can monitor phenomena “up close” • Enables spatially and temporally dense environmental monitoring Embedded Networked Sensing will reveal previously unobservable phenomena Seismic Structure response Contaminant Transport Ecosystems, Biocomplexity Marine Microorganisms

  14. Agricultural Applications Kyung-SanVineyardgreenhouse Growth, quality improvement, distribution history, purchase and delivery management USN-based remote chrysanthemum production system Pung-Ki Apples Kyung-San Vineyard

  15. Building Management System Energy Monitoring and Management

  16. USN Applications

  17. Applications of Sensor Networks • Military applications • Battlefield surveillance and monitoring • Detection of attack by weapons of mass production such as chemical, biological, nuclear weapons • Environmental applications • Forest fire detection, glacier/alpine/coastal erosion (ASTEC) monitoring • Flood detection, water/waste monitoring • Habitat monitoring of animals • Structural monitoring • Seismic observation • Healthcare applications • Patient diagnosis and monitoring • Commercial applications • Smart home, smart office, smart building, smart grid, intrusion detection, smart toys • Agricultural, fisheries, factories, supermarkets, schools, amusement parks • Internet data centers(IDC), Inventory control system, machine health monitoring

  18. Enabling Technologies Embednumerous distributed devices to monitor and interact with physical world Networkdevices tocoordinate and perform higher-level tasks Embedded Networked Exploitcollaborative Sensing, action Control system w/ Small form factor Untethered nodes Sensing Tightly coupled to physical world Exploit spatially and temporally dense, in situ, sensing and actuation

  19. MEMS • Micro-Electro-Mechanical Systems (MEMS) • The integration of mechanical elements, sensors, actuators, and electronics on a common silicon substrate through microfabrication technology. • While the electronics are fabricated using integrated circuit (IC) process sequences (e.g., CMOS, Bipolar, or BICMOS processes), • The micromechanical components are fabricated using compatible "micromachining" processes that selectively etch away parts of the silicon wafer or add new structural layers to form the mechanical and electromechanical devices.

  20. Sensor Network • Sensor networks • Sensors are usually scattered in a field. • Sensors collect and route data toward the sink • Sensors relay on each other for multi-hop communication • Sink communicates to a user through Internet

  21. Sensor Node • Consists of 3 subsystems • Sensor • Monitor a variety of environmental conditions such as • Temperature, humidity, pressure, sound, motion, .. • Different types of sensors • Passive elements • Seismic, thermal, acoustic, humidity, infrared sensors, 3D accelerators, light • Passive arrays • Image, biochemical • Active sensors • Radar, sonar, microphones • High energy, in contrast to passive elements • Processor • Performs local computations on the sensed data • Communication • Exchanges messages with neighboring sensor nodes

  22. Sensor Node Development LWIM III UCLA, 1996 Geophone, RFM radio, star network AWAIRS I UCLA/RSC 1998 Geophone, DS/SS Radio, strongARM, Multi-hop networks WINS NG 2.0 Sensoria, 2001 Node development platform; multi- sensor, dual radio, Linux on SH4, Preprocessor, GPS • UCB Mote, 2000 • 4 MHz, 4K RAM • 512K EEPROM, • 128K code, CSMA • half-duplex RFM radio Processor

  23. Sensor Node Development Sun SPOT Sun, 2008 Everything Java (Java drivers) IPv6/LoPAN, AODV Intel/Crossbow iMote2, 2007 Xscale processor 32MB Flash, 32MB SRAM 802.15.4 radio (CC2420) Linux kernel + JFFS2 flash file system Processor

  24. Physical Size WINS NG 2.0 Berkley Motes AWAIRS I LWIM III AWACS (Airborne Warning and Control System)

  25. Sensor Node HW-SW Platform In-node processing Wireless communication with neighboring nodes Event detection Acoustic, seismic, image, magnetic, etc. interface Electro-magnetic interface sensors radio CPU Limited battery supply battery Energy efficiency is the crucial h/w and s/w design criterion

  26. Sensor Node Platforms • Rockwell WINS & Hidra • Sensoria WINS • UCLA’s iBadge • UCLA’s Medusa MK-II • Berkeley’s Motes • Berkeley Piconodes • MIT’s AMPs • Intel’s iMote • Sun’s SPOT • And many more… • Different points in (cost, power, functionality, form factor) space

  27. Rockwell WINS and Hidra Nodes • Consists of 2”x2” boards in a 3.5”x3.5”x3” enclosure • StrongARM 1100 processor @ 133 MHz • 4MB Flash, 1MB SRAM • Various sensors • Seismic (geophone) • Acoustic • magnetometer, • accelerometer, temperature, pressure • RF communications • Connexant’s RDSSS9M Radio @ 100 kbps, 1-100 mW, 40 channels • eCos RTOS • Commercial version: Hidra • C/OS-II • TDMA MACwith multihop routing • http://wins.rsc.rockwell.com/

  28. UC Berkeley Motes • Processing • ATMEL 8b processor with 16b addresses running at 4MHz. 8KB FLASH as the program memory and 512B of SRAM as the data memory, timers • Three sleep modes: Idle, Power down, Power save • Communication • RF transceiver, laser module, or a corner cube reflector • 916.5MHz transceiver up to 19.2Kbps • Sensors • Temperature, light, humidity, pressure, 3 axis magnetometers, 3 axis accelerometers • TinyOS

  29. The Mote Family

  30. Crossbow MiCA Series • MICA2 • 868, 912MHz multi-channel transceiver • 38.4 kbps data rates • Embedded sensor networks • Light, temperature, barometer, acceleration, seismic, acoustic, magnetic sensors • >1 year battery life on AA batteries • Atmel ATMEGA128L 8 bit microcontroller • 128KB program and 512KB data (flash) memories • MICAZ • 2.4 GHz IEEE15.4 compliant • 250 kbps high data rates • Same processor and memory as MICA2 • IMote2 • 2.4 GHz IEEE15.4 compliant • Xscale processor up to 416MHz • DSP coprocessor • 256KB SRAM, 32MB Flash, 32MB SDRAM • TelosB • 2.4 GHz IEEE15.4 compliant • 8MHz TI MSP430 microcontroller • Open source platform

  31. Comparison with MANET • The number of nodes in a sensor network can be several orders of magnitude larger (more densely deployed) • Need more scalability • Limited resources • Limitations in processing, memory, and power • More prone to failure • More prone to energy drain • Battery sources are usually not replaceable or rechargeable • No unique global identifiers • Data-centric routing vs. address-centric routing • Queries are addressed to nodes which have data satisfying conditions • Query may be addressed to nodes “which have recorded a temperature higher than 30°C” • More massive data • Need aggregation/fusion before relaying to reduce bandwidth consumption, delay, and power consumption

  32. Issues and Challenges • Autonomous setup and maintenance • Sensor nodes are randomly deployed and need to be maintained without any human intervention • Infrastructure-less • All routing and maintenance algorithms need to be distributed • Energy conscious design • Energy at the nodes should be considered as a major constraint while designing protocols • The microcontroller, OS, communication protocols, and application software should be designed to conserve power • Global time synchronization • Sensor nodes need to synchronize with each other in a completely distributed manner for communication synchronization, temporal ordering of detected events, elimination of redundant events/messages • Dynamic topology due to failures or power-down/up • Real-time and secure communication

  33. Sensor Network Architecture Goals • Maximize the network life time (low energy) • Usually battery operated and they are not easy to recharge or replace • Coverage • Two types of coverage region • Sensing region: At least a node must exist in a sensing region • Communication region: A node must be within the communicating region of another node to be connected to the network • How to determine optimal spacing between the communicating node? • Too close means collision and increase the number of hops in communication while too far means disconnectivity • Performance: minimize latency and increase network bandwidth • Minimize collision among wireless transmission • Minimize unnecessary transmissions • Minimize redundant data collection by different nodes • Minimize redundant messages sent by a single node • Cost • Minimize the total number of nodes and the cost of each node • Others: scalable to a large number of nodes, fault tolerant • Conflicting goals • Cost vs. availability, Cost vs. performance?

  34. Sensor Network Protocol Stack User Queries, External Database In-network: Application processing, Data aggregation, Query processing Data dissemination, storage, caching Adaptive topology, Geo-Routing MAC, Time, Location Phy: comm, sensing, actuation Resource constraints call for more tightly integrated layers Open Question: Can we define anInternet-like architecture for such application-specific systems??

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