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1 Building Pervasive Computing Applications on Sensor Networks Rutgers, The State University of New Jersey

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Presentation on theme: "1 Building Pervasive Computing Applications on Sensor Networks Rutgers, The State University of New Jersey"— Presentation transcript:

1 1 Building Pervasive Computing Applications on Sensor Networks Rutgers, The State University of New Jersey

2 IAB, May 13, 2004 2 Introduction: Sensor Networks Global Internet (~2000) Cell Phones Everywhere (~2000) Telecom Information Tech Digital Media Convergence (2000-2010) Internet + Telecom The Physical World virtualized via sensors & actuators Global Internet for data & telecom The Virtual World Wireless Sensor Nets Pervasive Computing (2015-) data control

3 IAB, May 13, 2004 3 Future Wireless: Pervasive Systems Mobile Internet (IP-based) Overlay Pervasive Network Services Compute & Storage Servers User interfaces for information & control Ad-Hoc Sensor Net A Ad-Hoc Sensor Net B Sensor net/IP gateway GW 3G/4G BTS Pervasive Application Agents Relay Node Virtualized Physical World Object or Event Sensor/ Actuator

4 IAB, May 13, 2004 4 (Frictionless Capitalism)**2  Find goods and services on your PDA as you walk through town  Walk into your dept store and pick up what you need (no cashier!) “Smart” Transportation systems  get routed around traffic jams in real-time  receive collision avoidance feedback, augmented reality displays  be guided to an open parking spot in a busy garage Airport logistics and security  Walk on to your plane (except for physical security check)  Find your (lost) bags via RFID sensors  Airport authorities can screen passenger flows and check for unusual patterns Smart office or home  Search for physical objects, documents, books  Migrate your electronic media and documents between devices  Maintain a “lifelog” that stores a history of events by location  know where your co-workers and family members are Future Wireless: Pervasive Applications

5 IAB, May 13, 2004 5 Sensors  Tiny, low-power, integrated wireless sensors (hardware)  Embedded OS and networking capabilities (software) Ad-hoc wireless networks  Self-organizing sensor networks  Scalable, capable of organic growth  Interface to existing 3G/4G cellular and WLAN  Power efficient operation  Congestion control Pervasive computing software  Dynamic binding of application agents and sensors  Real-time orchestration of sensor net resources  Robust, secure and failsafe systems  Programming paradigm for sensor networks Augmented reality, new displays, robotics, control, information processing... Future Wireless: Key Technologies for Pervasive Systems emerging computer hardware category, optimized for size/power new type of wireless network without planning or central control fundamentally different software model - not TCP/IP Windows or Unix!!...beyond the scope of this talk

6 6 Enabling Technologies for Pervasive Systems

7 IAB, May 13, 2004 7 Integrated sensor/actuator + low-power microprocessor + radio Single chip or compact module Wireless networking Energy efficient design Applications of sensors include: Verticals: factory automation, security, military, logistics, transportation,.. Horizontal market: smart office, home  pervasive computing Integrated wireless sensors are the “next microprocessor”... MIT DVS Crossbow Sensor UC Berkeley MOTE Sensor Technology: Hardware

8 IAB, May 13, 2004 8 Sensor Technology: MUSE Prototype “Multimodal” wireless sensor hardware being developed with NJCST funding...  novel ZnO materials for tunable sensors  integration with low-power wireless transceiver designs  focus on an integrated system-on-package or system-on-chip  integrated ad-hoc networking software (as outlined earlier)  sensor applications, including medical heart monitors, etc. Sensor Device Modem, CPU, etc RF SensorRF Modem/CPU ZnO SAW filter, MEMS, etc. CMOS chip Multimodal ZnO device Reduced functionality, optimized for low power consumption… Embedded ad-hoc wireless net software 2002-04 target: Multi-chip module for sub-802.11b Early medical applications at UMDNJ 2005-06 target: Single chip prototype Pre-commercial applications w/ partners

9 IAB, May 13, 2004 9 Sensor Technology: Multimodal ZnO device “Tunable” ZnO sensor developed by Prof. Y. Lu’s group  Can be “reset” to increase sensitivity, e.g. in liquids or gas  Dual mode (acoustic and UV optic)  Applicable to variety of sensing needs Courtesy of: Prof Y. Lu, Rutgers U

10 IAB, May 13, 2004 10 Sensor Networking: Congestion Alleviation Resource control schemes to alleviate transient congestions in sensor networks  Transient congestions are common  Throttling traffic is not always an option (e.g., an heart emergency generates a large volume of data within a short time frame)  Sensor networks have elastic path capacity (e.g., variable transmission power, directional antenna, etc)  We can also use multiple routing paths to guarantee reliable event delivery  Timely and accurate congestion level monitoring is the key

11 IAB, May 13, 2004 11 Pervasive Computing: Software Model Ubiquitous or pervasive computing scenarios require a fundamentally new software model (…not TCP/IP or web!!):  Large number of context-dependent sources/sensors with unknown IP address  Content-driven networking (…not like TCP/IP client-server!)  Distributed, collaborative computing between “sensor clusters”  Varying wireless connectivity and resource levels Pervasive/Ubiquitous Computing Software Model Pervasive Computing Application Agent 2 Agent 1 Agent 3 Sensor Cluster A Sensor Cluster B Run-time Environment (network OS) Resource Discovery Ad-hoc Routing OS/Process Scheduling Overlay Network for Dynamic Agent Sensor Association

12 IAB, May 13, 2004 12 Pervasive Computing: System Model <> Sensors & Actuators Hierarchical Ad-Hoc Data Network Content Network Autonomous Agents Affinity Groups Courtesy of Prof. Max Ott

13 IAB, May 13, 2004 13 Self Organizing Overlay Content Network Discovery/Messaging (Content-DHT/ Associative Rendezvous) NeTS Applications (Autonomic Living, Ad hoc Control) Opportunistic Interactions Coordinate Flows Ad Hoc Routing Self Configuration Orbit Testbed Meteor Middleware Stack Programming Model Security: Ontology, Taxonomy Authorization Authentication Trust Software Model: Pervasive Computing Stack Wireless/Wired Infrastructure Prof. Manish Parashar: Programming Model & Resource Discovery

14 IAB, May 13, 2004 14 Pervasive Computing: Content Routing “Content routing” method for association between sensor devices, end-users and application programs  Use of XML content multicast to dynamically find consumer/producer match  XML multicast can be implemented as an overlay network on IP tunnels Sensor content multicast data XML descriptor XML Interest Profile XML data Application Programs End-user devices Network Infrastructure Radio Forwarding Node Storage Routing Concept of Using Content Multicast for Data-Centric Software Model

15 IAB, May 13, 2004 15 Pervasive Computing: Process Orchestration Programming ad hoc control systems – Coordinated Flows  Dynamic binding of application with sensors & actuators  Orchestration of computing and network resources in real-time Campus Parking Service Data Center Check registration, Deduct parking fee Allocate closest available space Check parking space availability Incoming Car ( check ID: Registered student/faculty/staff, guest reservation? Fee deduction) Look for parking space: subscribe (plate-num, car-type, IAB guest) Look for parking space subscribe (plate-num, car-type, student) Monitor incoming car Monitor available space Parking Center courtesy of Prof. Manish Parashar

16 IAB, May 13, 2004 16 FN MN Micro-level Cluster interface Pervasive Computing Platform: Scheduling & Network OS FN MN Micro-level Cluster interface FN MN Micro-level Cluster interface Cluster I: A cluster is formed because each sensor group provides certain data or functionality that is necessary to perform the specified task. A sensor group can participate in multiple clusters Work must be dynamically assigned to each group based on everyone’s energy budget, load, etc. Each sensor group should schedule its work for different clusters according to other members in these clusters. Micro-level scheduling issues: which sensor nodes should be active while others sleep? which sensor nodes should be sending back their readings? how to split a task between a group of sensor nodes? FN MN Micro-level Cluster interface

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