EE 360 Lecture 16 Outline Sensor Network Applications

EE 360: Lecture 16 Outline Sensor Network Applications and In-Network Processing l Announcements 2 nd summary due today 12 am (1 day extension possible) l Project poster session March 15 5: 30 pm (3 rd floor Packard) l Next HW posted by tonight, due March 16 l Will extend final project deadline l l l Overview of sensor network applications Technology thrusts Cross-layer design of sensor network protocols Cooperative compression Distributed sensing, communications, and

Wireless Sensor Networks Data Collection and Distributed Control • Hard Energy Constraints • Hard Delay Constraints • Hard Rate Requirements 2

Application Domains l Home networking: Smart appliances, home security, smart floors, smart buildings l Automotive: Diagnostics, occupant safety, collision avoidance l Industrial automation: Factory automation, hazardous material control l Traffic management: Flow monitoring, collision avoidance l Security: Building/office security, equipment tagging, homeland security l 3 Environmental monitoring: Habitat monitoring, seismic

Wireless Sensor Networks l Revolutionary technology. l Hard energy, rate, or delay constraints change fundamental design principles l Breakthroughs in devices, circuits, communications, networking, signal processing and crosslayer design needed. l Rich design space for many industrial 4 and commercial applications.

Technology Thrusts Analog Circuits • Ultra low power • On-chip sensor • Efficient On/Off • MEMS • Miniaturized size • Packaging tech. • Low-cost imaging Networking • Self-configuration • Scalable • Multi-network comm. • Distributed routing and scheduling System-on-Chip • Integration of sensing, data processing, and communication in a single, portable, disposable device Wireless Sensor Networks Applications Wireless • Multi-hop routing • Energy-efficiency • Very low duty cycle • Efficient MAC • Cooperative Comm. Data Processing • Distributed • Sensor array proc. • Collaborative detection/accuracy improvement • Data fusion 5

Crosslayer Protocol Design in Sensor Networks l Application l Network l Access l Link l Hardware Protocols should be tailored to the application requirements and constraints of the sensor network

Cross-Layer Design with Cooperation Multihop Routing among Clusters

Double String Topology with Alamouti Cooperation l Alamouti 2 x 1 diversity coding scheme l At layer j, node i acts as ith antenna l Synchronization required l Local information exchange not required

Equivalent Network with Super Nodes l Each super node is a pair of cooperating nodes l We optimize: l link layer design (constellation l MAC (transmission time tij) l Routing (which hops to use) size bij)

Minimum-energy Routing (cooperative)

Minimum-energy Routing (non-cooperative)

MIMO v. s. SISO (Constellation Optimized)

Delay/Energy Tradeoff l Packet Delay: transmission delay + deterministic queuing delay l Different ordering of tij’s results in different delay performance l Define the scheduling delay as total time needed for sink node to receive packets from all nodes l There is fundamental tradeoff between the scheduling delay and total energy

Minimum Delay Scheduling 5 4 3 1 2 2!3 1!3 3!4 4!5 T 2!5 3!5 T l The minimum value for scheduling delay is T (among all the energy-minimizing schedules): T=å tij l Sufficient condition for minimum delay: at each node the outgoing links are scheduled after the incoming links l An algorithm to achieve the sufficient condition exists for a loop-free network with a single hub node

Energy-Delay Optimization l Minimize weighted sum of scheduling delay and energy

Transmission Energy vs. Delay

Total Energy vs. Delay

Transmission Energy vs. Delay (with rate adaptation)

Total Energy vs. Delay (with rate adaptation)

Cooperative Compression l Source data correlated in space and time l Nodes should cooperate in compression as well as communication and routing l Joint source/channel/network coding

Cooperative Compression and Cross-Layer Design l Intelligent local processing can save power and improve centralized processing l Local processing also affects MAC and routing protocols

Energy-efficient estimation s 2 1 s 2 Sensor 1 2 Sensor 2 g 1 g 2 g. K Different observation quality (known) l s 2 K Fusion Center Different channel gains (known) Sensor K We know little about optimizing this system l Analog versus digital l Analog techniques (compression, multiple access) l Should sensors cooperate in

Digital vs. Analog

Key Message Cross-layer design imposes tradeoffs between rate, power/energy, and delay The tradeoff implications for sensor networks and distributed control is poorly understood

Distributed Sensing, Communications, and Controller System

Applications

Joint Design of Control and Communications - Generally apply different design principles Control requires fast, accurate, and reliable feedback. l Networks introduce delay and loss for a given rate. l - Sensors must collect data quickly and efficiently - The controllers must be robust and adaptive to random delays and packet losses. - Control design today is highly sensitive to loss and delay - The networks must be designed with control performance as the design objective.

A Proposed Architecture External Environment Controller Sensing System Online Model Inner Loop (PID, H ) Mode and Fault Management Goal Mgmt (MDS) Online Optimization (RHC, MILP) Attention & Awareness Memory and Learning State Server (KF ->MHE) (KF (KF, -> MHE)

Potential Pieces of the Puzzle l Local autonomy l l Estimation, prediction, and planning l l Subsystems can operate in absence of global data Exploit rich set of existing tools Command buffering and prefetching l Increases tolerance to data latency and loss l Time stamps and delay-adaptive control l Modular design l Supervisory control via models, cost functions, modes

Summary l Cross layer design especially effective in sensor networks. l Node cooperation can include cooperative compression l l Cooperative gains depend on network topology and application. Cross layer design must optimize for application l Requires interdisciplinary understanding, e. g. for control

Presentation l An application-specific protocol architecture for wireless microsensor networks l By W. Heinzelman, A. P. Chandrakasan and H. Balakrishnan l Presented by Mainak Chowdhury