1. Data Link Layer Architecture for Wireless Sensor Networks Charlie Zhong September 28, 2001

2. Outline  Background  Proposed solution  Future work

3. I. Background  Differentiation  Sensor network requirements  Data link layer functions and requirements  Challenges  Existing work

4. How is wireless sensor network different?  Energy consumption control  Disaster mitigation  Traffic management  Not much Qos, mobility, data rate;  but easy maintenance, long operation time, minimal human involvement

5. Sensor Network Requirements  Desired performance (e.g. how good the environment control is)  Easy setup  Simple maintenance/diagnostics  Low cost  Security  Scalability, size etc.

6. Data Link Layer DLL functions:  transfers data between network and physical layers;  power control, error control, access control  computes location  maintains neighborhood info Design requirements:  Supports required functions Communications with required reliability Location as part of information  Power-efficient  Distributed  Requires no global synchronization  Scalable, robust  Easy setup and maintenance Network Data Link Physical Transport Application

7. Challenges  What to optimize  The design of a subsystem is very dependent on that of another  How to compare two different designs Need a design method and analysis

8. Existing Works  802.11 power management: need global synchronization  UCLA: distributed scheduling  GTE: topology control  Tu-berlin: combined tuning of RF power and MAC Metrics proposed are not accurate, very few qualitative comparison, not for entire data link layer

9. Metrics Proposed  Power on time  Time spent on utilizing TX and RX  Total number of correctly transmitted packets during the lifetime of battery  Signal energy per successfully transmitted bits

10. What is power?  Communications: Value comes from information bits, not from OH bits, acks, handshakes to setup Values comes from the transfer from source to destination, not every hop  Processing: Value comes from how you use information Encoding/compression/redundancy

11. Our Solution A systematic approach: 1.Identify the goal for optimization 2.Perform functional break down 3.Understand the complicated inter-dependency between the design of different subsystems 4.Quantify design metrics, know the tradeoffs 5.Compare different algorithms 6.Predict the direction for improvements

12. Clean the Mess Before After

13. Outline  Background  Proposed solution  Future work

14. Our Solution  Optimization goal  UML functional description  Case study: power control subsystem Interactions between subsystems Design metrics Comparison of two algorithms Direction for improvements

15. Optimization Goal  Cost: local battery source  Value: desired functions  Goal: the time the desired functions can be maintained should be as long as possible for fixed energy cost Network Life

16.  Definition: the time network stays functioning for given power supply  How to quantify it: The time network stays connected (T1): max power consumption T1+the time network is still functioning after the 1 st node dies

17. Functional Description Unified Modeling Language

18. VCC Implementation Virtual Component Co-design

19. System Operation InitializationMaintenanceData Communication

20. Case study: power control  Controls the transmit power  Topology control for desired connectivity  Compensate topology changes incurred by mobility and dead nodes  Controls a node’s neighborhood

21. Interactions with other Subsystems S D Connectivity Spatial reuse Battery drain Eb/No Pb Interference Error performance Retransmissions Load balancing Performance degradation Collisions

22. Design Metrics Power Control BER Connectivity # ch available modulation coding Collision rate Transmit power: P T Simplified model: Assumptions: 1.Number of neighbors, or degree d, is used to approximate node connectivity 2.Nodes are uniformly distributed with density D 3.Channel assignment ensures every interferer is using a different channel 4.There is no interference between channels Radius: r Receiver sensibility: C BER: p Max # of retransmissions: N For given d, find minimum P T Interference

23. Target BER p: BER p kt : packet error rate M:# of bits/packet N: max # of retransmissions Reliability: prob. of packet loss after N retransmissions=p kt N+1 Assumptions: BPSK modulation, no coding, BSC channel Target BER 10 ^-3 -> packet loss rate 0.45%

24. Tradeoffs  Node connectivity k>=1 is required; k>1 is desired to give network layer enough paths to balance loads with  The higher PT, the higher the connectivity  At higher P T, it is harder for channel assignment to control collisions and interference  For given link-level reliability, there exists optimum BER

25. Data Link Layer Tradeoffs NetworkTransport Physical layer TX power Data rate # channels ConnectivityTraffic densityLink-level reliability ReliabilityRedundancy Power Control MAC Collision rate Interference Local Address # addressesID BER # interferers # NBs Data link data rate

26. Comparison of two algorithms  Topology control only  Our algorithm

27. Direction for improvement  Pick target BER based on link-level reliability, modulation and error control coding scheme  Jointly optimize across network and data link layers for longer network life

28. Outline  Background  Proposed solution  Future work

29. Future Work  More accurate modeling  Simulations  Network implementation  Better quantification of network life