Heterogeneous Sensor System on Chip

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1 Introduction of M2M Networks Heterogeneous Sensor System on Chip Chih Ting Lin Yi Chang Lu Graduate Institute of Electronics Engineering National Taiwan University

2

3 Billions of Connected Devices

4 Applications of M2M Systems

5 Infrastructures of M2M System

6 OSI 7 Layer Network Model Open System Interconnection model A reference model developed by ISO at 1984 Layer 7: Application layer Defines interface to user processes for communication and data transfer in network Layer 6: Presentation layer Masks the differences of data formats between dissimilar systems Layer 5: Session Layer Manages user sessions and dialogues Layer 4: Transport Layer Manages end to end message delivery in network Layer 3: Network Layer Determines how data are transferred between network devices Layer 2: Data Link Layer Defines procedures for operating the communication links Layer 1: Physical Layer Defines physical means of sending data over network devices

7 M2M Network Layers

8 Sensor Networks Sensor network systems A system consisting of a collective of networked sensor nodes designed to communicate to each other Integrate sensor, micro processor, and communication capabilities Sense environment, acquire information, and handle message Limited resources Sensor 範 圍 網 路 衛 星 或 其 他 傳 輸 媒 介

9 Previous Sensor Network Applications UC Berkeley Habitant Monitoring 2002 Develop a habitat monitoring kit Monitor sensitive wildlife and habitats Engage in the non intrusive i and non disruptive method

10 Previous Sensor Network Applications UC Berkeley Firebug 2003 Install GPS system with sensor network Enable temperature monitoring with coordination Monitor wildfire in forest

11 Previous Sensor Network Applications UC Berkeley Structural Health Monitoring of the Golden Gate Bridge 2005 Measure ambient structural vibration Install 64 nodes on GGB Collect vibrations synchronously at 1kHz rate

12 Previous Sensor Network Applications Duke Univ. Observation of Ecosystem Processes Deploy dense spatial temporal sensing of environments Buildawareness of the benefits of the technology

13 Previous Sensor Network Applications NTU (Prof. 李 世 光 ) Structural Monitoring 2002 Founded by 勞 委 會 勞 工 安 全 衛 生 研 究 所 Monitor the safety of 建 築 鷹 架 Up and low limit of admission strain strain

14 Previous Sensor Network Applications NTUT (Prof. 李 仁 貴 ) Semiconductor Fab Monitoring Monitor the equipment vibration

15 Previous Sensor Network Applications NTU (Prof. 黃 寶 儀 ) BL Live: The Elevator Report know the status t of the elevators in the building Establish mid/large scale sensor network testbed for everyday use Sensor Network

16 Previous Sensor Network Applications CGU (Prof. 林 仲 志 ) 無 線 感 測 網 路 居 家 型 退 化 偵 測 設 備 之 研 發 Measure reaction force and motion balance of elders

17 Previous Sensor Network Applications NTU (Prof. 江 昭 皚 ) 東 方 果 實 蠅 生 態 監 測 與 預 警 系 統 Measure the population of flies

18 Basic Infrastructure of Sensor Node A sensor node in WSN Microprocessor Data storage Sensor RF transceiver Energy source i Microprocessor Transceiver unit unit Power Supply unit Sensor light and temperature

19 Sensor Network Design Consideration Consideration of sensor network developments Application Environment Transmission Media Scalability Sensor Network Topology Hardware Constraints t Power Consumption Fault Tolerance Sensor Costs

20 Sensor Node Design Consideration The requirement of sensor networks Robustness, effectiveness, low cost, and small size Sensing unit Passive/active sensors Power consumption Microprocessor unit Power saving Cost/performance Communication unit IEEE (low data rate wireless PAN) Power saving

21 M2M Physical Device: Smart Sensor Node Sensors bridge physical events to systems Networking concept is rarely considered in traditional sensor designs Emphasize single sensor characterization Concentrate at different kind of sensing performance Stress thenetworklatency as the complexity sensing scope increases

22 Measure the sound Microphone

23 Accelerometer Measure e the eacceleratione at

24 Gyroscope Measure the orientation

25 Pressure Sensor Measure the pressure

26 Change the light path Optical Switch

27 Turbine Engine Generate the air thrust

28 Biomolecular Detector Measure the biomarker

29 M2M Physical Device: Smart Sensor Node Smart sensor node is necessary in M2M network Promote scopes of sensors and systems Improve system performance Lower sensor manufacturing cost Increase value of sensor nodes This project aims at heterogeneous Sensor System on ChipSystem on CMOS compatible stacking technology Pseudo 3D architecture Efficient andcompact designofsmart smart sensornodenode

30 3D ICs in the 80 s A parallel image processor from Mitsubishi T. Nishimura et al., Three dimensional IC for high performanceimage signal processor processor, IEEE International Electron Device Meeting Technical Digest, pp , Dec YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

31 3D ICs in the 80 s A gate array and memory chip from NEC Kunio et al., Three dimensional ICs, having four stacked active device layers, IEEE International Electron Device Meeting Technical Digest, pp , Dec YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

32 Possible Applications Sensor systems Heterogeneous integration Memory-processor systems Signaling/timing Network-on-chip Topology Field-programmable-gate-arrays Redundancy YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

33 3D Technology Package stacking Die/Wafer stacking Device stacking Lu, 3D technology based circuit and architecture design, Proceedingsof of International Conferenceon Communications, Circuits, and Systems, pp , July YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

34 Face to back stacking Die/Wafer Stacking Koyanagi et al., Three dimensional integration technology based on wafer bonding with vertical buries interconnections, IEEE Trans. Electron Devices, Vol. 53, No. 11, November YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

35 Device Stacking 6T SRAM cells Jung et al., Highly cost effective and high performance 65nm S3 (stacked single crystal Si) SRAM technology with 25 F 2, 0.16um 2 cell anddoubly doubly stacked SSTFT cell transistors for ultra high density and high speed applications, Symposium on VLSI Technology Digest of Technical Papers, pp , June, (also see IEDM 2004) YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

36 Design Considerations Through-silicon-vias(TSVs) & micro-bumps (MBs) Density Operating frequency Parasitic Styles Yield Davis et al., Demystifying 3D ICs: the pros and cons of going vertical, IEEE Design & Test of Computers, vol. 22, no. 6, pp , Nov. Dec YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

37 Capacitive Coupling Gu et al., Two 10Gb/s/pin low-power interconnect methods for 3D ICs, IEEE International Solid-State State Circuit Conference, pp , February, YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

38 Inductive Coupling Davis et al., Demystifying 3D ICs: the pros and cons of going vertical, IEEE Design & Test of Computers, vol. 22, no. 6, pp , Nov.-Dec YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

39 Design Considerations Device characteristics Thermal Flatness Stress Device options Silicon at the same node Silicon at different nodes Silicon and other materials Active and passive YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

40 Design Considerations Thermal issues Timing NBTI Leakage Thermal modeling and simulation FE/FD solvers RC network Chen et al.,, Thermal modeling and device noise properties p of three dimensional SOI technology," IEEE Trans. Electron Devices,, Vol. 54, No. 4, pp , Apr YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

41 Thermal Network Analogy Parameters Voltage Current Charge Resistance Capacitance Electrical Thermal Parameters V [V ] Temperature T[K] i [A] Heat Transfer Rate q[w ] Q[C] Heat Q T [J ] Thermal Resistance R E [ V / A] [ T / W ] Thermal Capacitance C E [ C / V ] R T C T [JJ / K ] C T Equations Equations Transient Steady State 2 V R C E E V ir E V t Transient 2 T Steady State R T C T t T T qr T YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

42 Design Considerations Cooling techniques Better heat sink Thermal vias Microfluidic channels Micro TE coolers Mizunuma et al.,, Thermal modeling for 3D ICs with integrated microchannel cooling, IEEE/ACM Proceedings of International Conference on Computer Aided Design, Nov YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

43 Design Considerations Power integrity IR drops Supply domains Timing strategies Synchronization Self-timed Signaling g strategies I/Os Level shifters YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

44 Arithmetic Units Wafer stacked kdtechnology Davis et al., An 8192 point Fast Fourier Transform 3D IC case study study, IEEE Proceedings of MWCAS, pp , 441 Aug YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

45 Nonvolatile SRAM Cell Device stacked kdtechnology Wang et al., Nonvolatile SRAM cell, IEEE International Electron Devices Meeting Technical Digest, Dec YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

46 Flexible Electronics Sensors Someya et al., Conformable, flexible, large area areanetworks of pressure andthermalsensors with organic transistor active matrixes, PNAS, pp , Aug YC Lu 2011 Graduate Institute of Electronics Engineering, National Taiwan University

47 Heterogeneous Sensor System on Chip System on (S 2 oc) Instead of fully integration sensing device into CMOS fb fabrication at the same layer with circuits Low temperature processes stack sensing device on the CMOS circuit The advantages by harnessing synergies of different materials and processes The capability of low cost, large area fabrication, multifunctions, and local data fusion Low power consumption CMOS circuits promote functionalities of each sensor node The improvement of network communication by local DSP capabilities The self intelligent network achieved by local fusion and computation

48 Sensor on Chip on based on Inkjet printing Gas Sensor: Quasi 3D architecture Configurable sensing elements Non contact patterning for CMOS chip stacking Stacking sensing layer on the top of CMOS chip

49 Expected Advantages of Heterogeneous S 2 oc Configurable sensing functions on a chip Printing different material for different scope Lowering manufacturing cost Promoting applied value of smart sensor nodes Low power consumption design of smart sensor node Low power organic sensing material Energy efficient i architecture t Reduced manufacturing cost of sensor nodes Stacking architecture t Low cost post process for sensing elements

50 Challenges Un stability of organic materials Employing long chain polymer to enhancestability in both thermal and electrical interference Utilizing parallel process elements design to minimize the interference from circuit closed to sensing material Low selectivity of polymer sensing elements Improving by the cross calibration of multiple sensing elements Fabrication compatibility of heterogeneous nature Using ion free polymer based sensing material Taking the advantage of low temperature process of inkjet printing technology

51 Conclusions Shift the new design paradigm of sensor nodes More sensing elements More calculation capabilities Lower power consumptions Lower manufacturing cost Harness advantages heterogeneous integration Pave the way toward M2M applications

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