1. TinyOS

2. Component Model Component has: Frame (storage) Tasks (computation)
Command and Event Interface
Messaging Component
Internal State
Internal Tasks
Commands
Events

3. TinyOS Application Component Graph
Application Originates
Message
sensing application
application
Thru-Route
Message
Routing Layer
routing
Messaging Layer
messaging
packet
Radio Packet
byte
Radio byte
Temp
photo SW HW
bit
RFM
ADC
i2c
clocks

4. Related MAC mechanisms

5. 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

6. 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

7. 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

8. Applicable Mechanisms
Listening Mechanism
Back off Mechanism
Contention Based Mechanism
Rate Control Mechanism

9. Self-Organization of a Wireless Sensor Network

10. 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 topology-modifying event
Level can vary depending on the network considered.

11. Spectrum of Self-Organization

12. 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.

13. Multihop Network
Can operate in both sensor-to-sink and sink-to-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.

14. 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.

15. 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.

16. 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

17. 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

19. EAR(Eavesdrop-And-Register)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.

20. 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

21. 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)

22. 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

23. 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.

24. 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
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

25. Flooding Gossiping Spin Directed Diffusion Clustering
ROUTING
Flooding
Gossiping
Spin
Directed Diffusion
Clustering

26. Flooding & Gossiping Flooding: Gossiping:
Diffuse copies of message to all neighbors
Problems:
Implosion
Overlap
Resource Blindness
Gossiping:
Diffuse one copy to random neighbors
Solves implosion problem

27. 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.

28. 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.

29. 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.

30. 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)

31. 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.

32. Dynamic Power Management in Wireless Sensor Networks
A.Sinha and A.Chandrakasan, IEEE Design Test Comp.,Mar./Apr.2001
Massachusetts Institute of Technology

33. Description Energy savings via 5 power saving modes
Intermode transition policies investigated

34. Sensor Network & Node Architecture
Nodek Ck R
Sensor
A/D
Micro-OS
StrongARM
Memory
Radio
Battery and DC/DC converter

35. Communication Models
1) Direct Transmission
2) Multihop
3) Clustering

36. Useful Sleep States for the Sensor Nodes
StrongARM
Memory
Sensor,
A-to-D converter
Radio s0
Active On
Tx,Rx s1
Idle
Sleep Rx s2 s3
Off s4
Tx: Transmit
Rx:Receive

37. 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 PXY(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)

38. State Transition Latency & Power
Power ti
Active Idle Active s0 P0
Pk sk
Pk+1 sk+1
t t2
taud,k tauu,k
taud,k tauu,k+1

39. 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); }

40. 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 Next state test
Yes
lamdak> s3
Yes Prob.(1-ps4)
Sleep? S Prob. ps Compute ts4,k s4