1. A Biologically-Inspired Approach to Designing Wireless Sensor Networks Matthew Britton, Venus Shum, Lionel Sacks and Hamed Haddadi The University College London, London,UK EWSN’04

2. OUTLINE Introduction System Requirements KOS Hardware Environment Performance Analysis Conclusion

3. INTRODRCTION Biological Automata have a number of desirable characteristics such as ： scalability robustness simplicity self-organization There are significant advantages in treating some classes of sensor networks as Biological automata–like system

4. INTRODRCTION (cont.) Biological Automata Self-organise and self- optimise System adapt to dynamic environments Neighbor to neighbor interaction Iterative–like process Change slow to spread through the network agent

5. INTRODRCTION(cont.) Application to sensor network To limit communication to short range Avoid the centralize algorithm (power mangement) Scalability For environmental monitoring the size of the spatial field of interest will not be unknown in design phase Simplicity of mangement Self-organising and self-optimised (robust) Dynamic environment and requirment In environmental monitoring various temporal phases of operation

6. INTRODRCTION(cont.) Iterative application Quality of their result Operation become simple and predictable For relatively high-latency requirement system

7. INTRODRCTION(cont.) Goal- Decentralised management Self-organisation and autonomy Robustness to topological change Limited processing power of individual nodes Power control for individual nodes Adaptation to dynamic environments and changing roles

8. System Requirements Coordination (distributed algorithm) Nodes within the same area interact and understand the phenomenon Representative node coordinate other nodes action (save energy ) “ Horizontal ”  Layers of network function upon a network of nodes “ Vertical ”  tasks within one of these node

9. System Requirements(cont.) Data transport protocol Gossip-protocol Like Flooding protocol Periodically exchange state to neighbor A B D B E F G D E Select a peer Exchange view C F G C

10. System Requirements(cont.) Power management Cluster, avoid multihop radio communication High integrity operation System can adapt to failures, corrupted data or imprecision’s in parameters and still function sufficiently (Fault tolerance)

11. KOS Features Modularity of application design Simple execution model single-tasking,run to completion model Highly communication oriented (messaging interface) Power awareness Adaptive scheduling Simple processing load control Adjust the execution periods of iterative app

12. KOS Structure The kOS is divided into objects and methods. Task execution is performed by specifying objects, methods and execution times Main routine Object Method Library routine#1 Library routine#2

13. KOS Structure (cont.) The KOS functional abstraction

14. KOS Operation Task scheduling Sleep/activity/sleep cycle Schedule object manage transitions Messaging handling SAD (SECOAS APP Message Protocol) SAM (SECOAS Data Message Protocol) Robustness of operation

15. Task scheduling Sleep High priority scheduler Low priority scheduler High priority ISR Low priority ISR High priority interrupt Low priority interrupt Return to low priority ISR Boot Kos reset command WDT time-outstart

16. Task scheduling Concept(cont.) Sleep Hardware RFSensorUART Ready Queue High priority scheduler ISR Low priority scheduler ISR Task Run Preemption Timer run to completion Scheduler Task

17. Task scheduling(cont.) The biological automaton characteristic of iteration to design application Scheduler can control the period of its execution. Reduce power consumption when the node’s battery power is low. KOS use an off-line analysis to gauge the duty cycle of each object’s iteration

18. Message handling The message object is scheduled periodically after radio and sensor interface message are received SAM is used by objects for intra- and inter-node communication (between application) SAD is used between application and sensor module Using message-handling services and gossip protocol disseminate information around network (policies or application parameters)

19. Message handling(cont.) A B C D Gossip protocol Periodically exchange state to neighbor

20. Message handling(cont.) Radio Receive Buffer Sensor Transmit Buffer Radio Transmit Buffer Sensor Receive Buffer Radio module Applications Sensor Module SAM SAD Data flow intra-node between application, radio module and sensor module

21. Robustness of operation Reboot itself in an attempt to bypass any intermittent problems WDT Application will operate given unknown radio connectivity conditions If information is unavailable for short periods of time, this simply halts the iterative process for that time period Application will load-controlled by the scheduler Change periodicity of these application

22. Hardware Environment MCU: PIC18F452(8-bit 4MHz) 32K FLASH 1.5KRAM 200 bytes EEPROM Sensor module Radio module LCD display

23. Performance Analysis Power usage

24. Performance Analysis(cont.) CPU duty cycle 4MHz operates at 1 million instructions per second

25. Performance Analysis(cont.) Memory usage

26. Conclusion Treat wireless sensor networks like biological automata Beneficial features ： scalability, robustness, self-organisation Support distributed Application