TinyOS
Component Model
• Component has:
– Frame (storage)
– Tasks (computation)
– Command and Event
Interface
Messaging Component
Internal Tasks
Commands
Internal State
Events
TinyOS Application Component
Graph
Application Originates
Message
application
Thru-Route
Message
Routing Layer
routing
messaging
packet
byte
bit
sensing application
Messaging Layer
Radio Packet
Radio byte
RFM
photo
clocks
ADC
Temp
i2c
SW
HW
Related MAC mechanisms
CSMA
• Listening to the channel before transmission
• Pozitive or negative acknowledgments to
signal collusion
• Lean toward a fundamental assumption that
packet transmissions occur with a stochastic
distribution, that is very different the
correlated trafic found in sensor networks
• Aim to support many point-to-point flows
IEEE 802.11
• Aims to provide a wireless Ethernet illusion
• Design based on assumption of a single cell
scenario, with mobile stations always in range of
at least one base station
– Hand off when migrating from one cell to another
– No multihop scenario
• Assumes peer-to-peer communications rather than
many-to-one data propogation
Bluetooth
• Model of creation a “wireless cable” illusion
• Primary MAC protocal is a centrialized
TDMA protocal within piconet
– Relatively static ad-hoc network supporting a
small number of nodes within single cell
• No multihop scenario
• Inappropriate for sensor networks
Applicable Mechanisms
•
•
•
•
Listening Mechanism
Back off Mechanism
Contention Based Mechanism
Rate Control Mechanism
Self-Organization of a
Wireless Sensor Network
Self-Organization
• A self-organized network is an independent
collection of nodes in which enough
information—or the ability to retrieve such
information--is present in order to allow transfer
of information between any two nodes in the
network.
• Either at initialization or after a topologymodifying event
• Level can vary depending on the network
considered.
Spectrum of Self-Organization
Protocols for Self-Organization of a
Wireless Network
• Protocols must be able to enable network
operation during:
1. start up : nodes are booted up, and network is
formed.
2. steady state : energy reservoirs are full, can
support all the sensing, signal processing and
communication. Multihop network is formed in
this mode.
3. failure : re-organization, MAC and routing
algorithms for the formation of new links and
routes to the sink nodes.
Multihop Network
• Can operate in both sensor-to-sink and sinkto-sensor.
• Bulk of the traffic will belong to the former.
• Significant strain on the energy resources of
the nodes near the sink, that neighborhood
will be more susceptible to energy depletion
and failure.
Energy Conserving Techniques
• Sensor nodes will do local processing, as
opposed to exchanging raw data over air
• Protocols must reduce messaging overhead.
• These two will lead to the requirement of
highly localized and distributed algorithms
for data processing and networking.
Protocols for Self-Organization of a
Wireless Network(cont.)
• SMACS(Self-organizing Medium Access Control for
Sensor Networks): for network start up and link layer
organization
• EAR(Eavesdrop-And-Register)Algorithm: enables
seamless interconnection of mobile nodes in the field of
stationary nodes
• SAR(Sequential Assignment Routing): facilitates multihop
routing
• SWE(Single Winner Election)- MWE(Multi-Winner
Election): handle the necessary signalling and data transfer
tasks in local cooperative information proccessing.
Link Layer Issues
Channel Access Classes:
• Contention or explicit organization in time/freq. :
not suitable for sensor networks since it requires
monitoring channel at all times
• Organized channel access:
- determines network radio connectivity to
discover radio neighbors of each node
- assign collision free channels to links
* centalized channel assignment
* distributed assignment
SMACS= Neighbor Recovery+Channel
Assignmet
• Infrastructure building protocol that forms a
flat topology
• A distributed protocol which enables nodes to
discover their neighbors and establish
transmission/reception schedules for
communicating them without the need for any
local or global master nodes
EAR(Eavesdrop-AndRegister)Algorithm
• Offers continuous service to the mobile nodes
under both mobile and stationary constraints.
• Primary constraint: battery power; mobile and
stationary sensors must be established with as few
messages transmitted by stationary sensors as
possible.
• Hand off may not be required.
• Mobile nodes have the registry of the neighbors.
• Acks are avoided by timeouts, thresholds.
Routing
• Multihop Routing
- objective: to provide priority service with
robustness on a long term basis
- more energy will spent on route setup and
maintenance
• Cooperative Routing
- reducing overhead in setup since data
traffic is light
Multihop Routing
•
•
•
•
Minimum energy per packet
Minimum cost per packet
Creation of multiple paths
Parameters:
- energy resources estimated by maximum number
of packets
- additive QoS metric(higher metric= lower Qos)
(assumed low mobility)
SAR(Sequential Assignment
Routing)
• Selection of a path among multipath by the node
which generates the packet
• Objective: to minimize the average weighted QoS
metric throuhout the lifetime of the network
• Criteria:
- energy resource
- QoS metric
- Priority level of a packet
Cooperative Signal Processing
• Noncoherent
- raw sensor data will be preprocessed to be forwarded to
central node
- central node selection algorithms:
* SWE(Single Winner Election)
* ST(Spanning Tree)
• Coherent
-Limited number of sensor generating data
- Explicit computation of minimum energy paths
- MWE() is used to decrease energy cost.
-Longer delay, higher overhead, lower scalability.
References
• Katayoun Sohrabi, Jay Gao, Vishal Ailawadhi, and Gregory J.Pottie,
“Protocols for Self organization of a Wireless Sensor network,” IEEE
Pers Commun., Oct. 2000, pp. 16-27
• Christopher A. St. Jean, “Self-Organization in Ad Hoc and Multihop
Wireless Communication Networks,” Symposium on Multi-hop/Ad-hoc
Wireless Networks, June 2002, France.
• J. Jamont and M. Occello, “Using Self-Organization for Functional
Integrity Maintenance of Wireless Sensor Networks,” IEEE Proc.,
France, 2003.
• R.E. Van Dyck, “Detection Performance in Self-Organized Wireless
Sensor Networks,” National Institute of Standards and Technology
Gaithersburg, Maryland, USA
ROUTING
•Flooding
•Gossiping
•Spin
•Directed Diffusion
•Clustering
Flooding & Gossiping
• Flooding:
– Diffuse copies of message to all neighbors
– Problems:
• Implosion
• Overlap
• Resource Blindness
• Gossiping:
– Diffuse one copy to random neighbors
– Solves implosion problem
– Problems:
• Overlap
SPIN
• Overcome the problems of flooding
• Negotiation and Resource-adaptation
– Negotiation: helps ensure only useful
information will be transferred
– Resource manager: keeps track of resource
consumption
• Disseminate information with low latency
and conserve energy at the same time.
SPIN
• ADV, REQ, DATA
• Spin1: do not consider energy consumption
• Spin2: if energy is low level, reduce its
participation
• in terms of energy,
– Spin1 uses 25% as much energy than flooding
– Spin2: 60% meta-data per unit energy than
flooding.
Directed Diffusion
• Data centric
• Attribute-naming
• interest including timestamp, gradient, data rate,
duration(lifetime)
• Reactive routing
• Neighbor-to-neighbor
• Can be efficient in highly dynamic networks(changes
in topology is not important)
• trade off some energy efficiency for increased
robustness and scale.
LEACH
•
•
•
•
•
Clustering based
Min. Energy dissipation
Randomly select nodes as clusterheads
Setup & steady phases
Clusterhead advertise that they are
clusterheads
• Based on signal strength(cluster members
determined)
References
• C. Intanagonwiwat, R. Govindan, D. Estrin and J.
Heidemann, “Directed Diffusion for Wireless Sensor
Networking”, in IEEE/ACM Transactions on Networking,
v.11, no. 1, February 2003.
• J. Kulik, W. Rabiner, and H. Balakrishnan, “Adaptive
protocols for information dissemination in wireless sensor
networks,” in Proc. 5th Annu. ACM/IEEE Int. Conf.
Mobile Computing and Networking(MobiCom’99), Seattle,
WA, 1999, pp. 174–185.
Dynamic Power Management in
Wireless Sensor Networks
A.Sinha and A.Chandrakasan, IEEE Design Test
Comp.,Mar./Apr.2001
Massachusetts Institute of Technology
Description
• Energy savings via 5 power saving modes
• Intermode transition policies investigated
Sensor Network & Node
Architecture
Nodek
Ck
R
Sensor
A/D
Micro-OS
StrongARM
Memory
Battery and DC/DC converter
Radio
Communication Models
1) Direct Transmission
2) Multihop
3) Clustering
Useful Sleep States for the Sensor
Nodes Sensor,
Sleep State
StrongARM
Memory
Radio
A-to-D
converter
s0
Active
Active
On
Tx,Rx
s1
Idle
Sleep
On
Rx
s2
Sleep
Sleep
On
Rx
s3
Sleep
Sleep
On
Off
s4
Sleep
Sleep
Off
Off
Tx: Transmit
Rx:Receive
Event Generation Model
•
R: Temporal event behavior over the entire sensing region=> Poisson process with an average
event rate lambda-tot
•
Spatial distribution of events: independent probability distribution P XY(x,y)
•
pek=prob. that an event is detected by nodek, given the fact that it occurred in R.
=……….
Pk(t,n)= prob.that “n” events occur in time “t” at node k.
Pk(Tth,0)= prob. of no events occurring in Ck over threshold interval Tth
=……………
Pth,k(t)= prob.that at least one event occurs in time t at nodek
=1- Pk(Tth,0)
State Transition Latency & Power
Power
Active
ti
Idle
Active
s0
P0
Pk
sk
Pk+1
sk+1
t1
t2
taud,k
tauu,k
taud,k+1
tauu,k+1
Steady State Shutdown Algorithm
If(eventOccurred()=true){
processEvent();
++eventCount;
lambda_k=eventCount/getTimeElapsed();
for (k=4;k>0;k--){
if(computePth(Tth(k)) < pth0)
sleepState(k);
}
}
Missed Events
ps4=prob.that no events occur in ts4,k
t s4 =time duration in s4 mode
=- ln(ps4)/lamdak
Transition Algorithm to almost-off state:
No
ComputePth(Tth(4))<pth0
Yes
No
lamdak>0
s3
Yes
Prob.(1-ps4)
Sleep?
Prob. ps4
Compute ts4,k
s4
S3
Next state test