a biologically-inspired approach to designing wireless sensor networks matthew britton, venus shum,...
TRANSCRIPT
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
OUTLINE
• Introduction• System Requirements• KOS• Hardware Environment• Performance Analysis• Conclusion
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
INTRODRCTION (cont.)
• Biological Automata• Self-organise and self-op
timise• System adapt to dynami
c environments• Neighbor to neighbor int
eraction• Iterative–like process• Change slow to spread t
hrough the network
agent
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
INTRODRCTION(cont.)
• Iterative application• Quality of their result• Operation become simple and predictable
• For relatively high-latency requirement system
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
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
System Requirements(cont.)
• Data transport protocol• Gossip-protocol
• Like Flooding protocol
• Periodically exchange state to neighbor
A B
DBEF
GDE
Select a peer
Exchange viewCFG
C
System Requirements(cont.)
• Power management• Cluster, avoid multihop radio communication
• High integrity operation• System can adapt to failures, corrupted data or im
precision’s in parameters and still function sufficiently (Fault tolerance)
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
KOS Structure
• The kOS is divided into objects and methods.• Task execution is performed by specifying objects, m
ethods and execution times
Main routine
Object
Object
Method
Method
Method
Library routine#1
Library routine#2
KOS Structure (cont.)•The KOS functional abstraction
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
Task scheduling
Sleep
High priority scheduler
Low priority scheduler
High priority ISR
Low priority ISR
High priority interrupt
High priority interrupt
Low priority interrupt
Return to low priority ISR
Boot
Kos reset command
WDT time-outstart
Task scheduling Concept(cont.)
Sleep
Hardware RF Sensor UART
Ready Queue
High priority scheduler
ISRLow priority scheduler
ISR
Task
Run Preemption
Timer
run to completion
SchedulerTaskTask
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
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)
Message handling(cont.)
A
B
C
D
Gossip protocol
Periodically exchange state to neighbor
Message handling(cont.)
Radio Receive Buffer
Sensor TransmitBuffer
Radio Transmit Buffer
Sensor ReceiveBuffer
Radio module
ApplicationsSensor Module
SAM SAM
SAMSAM
SAM
SAD
SAD
SAD
SAD
•Data flow intra-node between application, radio module and sensor module
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
Hardware Environment
• MCU:• PIC18F452(8-bit 4MHz)
• 32K FLASH
• 1.5KRAM
• 200 bytes EEPROM• Sensor module• Radio module• LCD display
Performance Analysis
• Power usage
Performance Analysis(cont.)
• CPU duty cycle•4MHz operates at 1 million instructions per second
Performance Analysis(cont.)
• Memory usage
Conclusion
• Treat wireless sensor networks like biological automata
• Beneficial features : scalability , robustness, self-organisation
• Support distributed Application