TinyOS

1. TinyOS

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

3. TinyOS Application Component Graph Application Originates Message sensing application application Thru-Route Message Routing Layer routing Messaging Layer messaging Radio Packet packet Radio byte Temp byte photo SW HW RFM ADC i2c bit 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 networkis an independent collection of nodes in which enough information—orthe ability to retrieve such information--is presentinorder to allow transfer of information between any twonodes 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. 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

25. ROUTING Flooding Gossiping Spin Directed Diffusion Clustering

26. 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

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”, inIEEE/ACM Transactions on Networking, v.11, no. 1, February 2003. • J. Kulik, W. Rabiner, and H. Balakrishnan, “Adaptive protocols forinformation 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 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 t1 t2 taud,k tauu,k taud,k+1 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))<pth0Next state test Yes No lamdak>0 s3 Yes Prob.(1-ps4) Sleep? S3 Prob. ps4 Compute ts4,k s4