Exploring Multicore-based Hardware/Software Architectures for Mobile Edge Computing Device
Exploring Multicore-based Hardware/Software Architectures for Mobile Edge Computing Device. IMPACT Lab Arizona State University. Outline. Mobile edge computing, mobile edge computing devices (MECD) Wireless sensor network (WSN) applications Desirable MECD features
Exploring Multicore-based Hardware/Software Architectures for Mobile Edge Computing Device
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Exploring Multicore-based Hardware/Software Architectures for Mobile Edge Computing Device IMPACT Lab Arizona State University
Outline • Mobile edge computing, mobile edge computing devices (MECD) • Wireless sensor network (WSN) applications • Desirable MECD features • Explore multi-core architectures for MECD
Wireless Sensor Network Hierarchy Back-end servers MECD Mobile edge computing device Networked Sensors
WSN Applications • Botanical garden (Ken) • Ayushman (Krishna) • Smart container (Guofeng) • Kids network (Su) Pay attention to: • Structure hierarchy • Potential term project topic
Physical layer impact • High temperatures reduce transmission range. 8 dB at 65 C. • No WiFi farther out. Extension requires self-powered nodes. Solar power [1,2] • Node power consumption. How to measure? [1] http://www.ee.ucla.edu/~kansal/papers/sensys_hsu_05.pdf [2] http://camalie.com/WirelessSensing/WirelessSensors.htm
Operating system projects • TinyOS vs. Contiki comparison • Both run on Tmote • Contiki adds protothreads and dynamic program swapping • TinyOS documentation • Hardware abstraction: MSP430, AVR128L; CC1000, CC2420
Organization Environmental Sensors (Temperature, Humidity) Patient Internet Local Gateway External Gateway Central Server Medical Professional Body Based Intelligence Home/Ward Based Intelligence Biomedical Sensors (EKG, BP) Medical Facility Based Intelligence Ayushman Vision Rationale: • Aging Population • Increasing healthcare cost • Shortage of medical personnel Goals: • Remote health monitoring (HM) • Test-bed for HM systems • Employ off-the-shelf components • Wireless biosensors • Wearable/in-vivo Desirable Properties: • Self-configuring • Real-time • Scalable Challenges: • Integration of diverse technologies • Minimize data loss • Reliability • Maintaining safety & security Status: • System development and Integration
Kids Networks Su Jin Kim
Social Science Project • How children’s social interactions (especially preschool) relate to their school success • Observation: • For 10 seconds, observe a target child • Identify the peers that he or she is interacting with • Collect data about interactions (e.g. positive emotions, negative emotions, aggressive behavior)
KidNet Project • Motivation • Apply it to older children who may not stay in the same classroom all day • Goals • Record the peers and duration of interacting • Interacting: within some small distance (2-3 ft.) • Track students’ location for safety and security • Advantages • Automatic, Real-time, Scalable
Proximity & Localization • Wearable Proximity Sensors • Detection of proximity • Duration of proximity • Localization using fixed nodes • Location of each child
Challenges • Accuracy • Detecting an object within 2-3 ft. • Energy • Should operate at least 10 hours • Wearable and Safe Devices • Should not be heavy and hurt kids • Reliable Communication • Indoor: reflection, blockage etc. • Scalability • Need to be expand to an entire school
Smart Shipping Container • Rationale • government needs • business needs • Goals • RFID, environmental sensing, communication, event detection, … • Challenges • mobile, large number, non-technical issues, …
RFID Reader MICAz mote TelosB mote TelosB mote ML Cargo Tag Sensors Sensors MICAz mote MICAz mote MICAz mote Container: architecture INTER-Container TelosB mote Attached to nearby containers. Proximity motes form an ad hoc (multi-hop) inter-container network. GPS Receiver 1 MICAz mote Container(s) External Hosts Stargate Internal Wireless Sensor Networks USB Memory Card MICAz mote 2.4 GHz 2.4 GHz USB 51-pin Stargate Managing Internal network (hardware, power and security); data processing, & routing outgoing packets to external interface. Ethernet Mobile Computing Computers at point of work (Handhelds) & at the Data Center. Held by custom officers and load/unload workers. Querying current and historical data and DB downloading from the logging systems. Enterprise Servers: Computers at the Data Center. Collecting real-time data from containers, managing DB & responding to critical events reported by containers. 802.11 RS232 PCMCIA Compact Flash GPRS PCMCIA Modem 802.11 Compact Flash card Cellular Network
Container: pictures RFID Reader + MicaZ Mote Stargate TeloB MicaZ
Mobile Edge Computing Device (MECD) • Back-end servers • High computing power • Global decision/policy maker • Interface to users • Physically fixed • MECD • Mobile • Unmanned • Comm. with server & sensors • via multiple types of networks • Dealing with large amount of • sensors • Networked Sensors • Large number • Mobile • Small form factor • Sensing and limited wireless • comm. capability Scalable reliable Low system cost, flexible
Desirable MECD Features • High processing power • Localized data processing • Database management • Event detection • Alert generation • Distributed infrastructure management • Security • Reliability • Real-time • Power efficiency • Network management • self-configurable, self-diagnostic, self-healing • ZigBee, WiFi, WiMAX, Bluetooth, GPRS and Ethernet
Desirable MECD Features (cont’d) • Low power consumption • Mobile & unmanned • Virtualization • Integrating various types of sensors from different vendors • MultiOS • Ease of development • Low cost
Exploring Multi-core Architectures • High processing power • Low power consumption • Low cost
Multi-core processor: high processing power • Homogenous (symmetric): • Symmetric multiprocessing (SMP) • Heterogeneous: Dedicated cores and diverse special purpose cores for hardware acceleration • Data processing • Distributed management • Network protocol • VPRO®
Multi-core processor: low power consumption • Reduced dynamic power • Each processor core can be individually turned on or off • Each processor core can run at its own optimized supply voltage and frequency • Fine-grain & ultra fine-grain power management and dynamic voltage and frequency scaling • Dynamic task assignment
Multi-core processor: low cost • Reduced hardware • SDR (software defined radio) enabled by a multi-core processor
Approach & Deliverable • Approach • Design & analysis to improve the understanding of multi-core processor’s application to MECDs • Deliverable We will answer the following fundamental questions: • A set of feasible multi-core based architectural designs that addresses the emerging requirements for MECDs • An optimal multi-core based architecture (in terms of both computing and communication addressing multiple types of networks and topology) for MECDs • Challenges and restrictions of using multi-core processors in MECDs
RA Opportunity • Motivated graduate student • Strong problem solving skills Talk to Dr. Gupta