Off By One Power-Save Protocols

1. Off By OnePower-Save Protocols Corey Andalora Keith Needels

2. Agenda • Paper 1: BECA / AFECA • Paper 2: GAF • Paper 3: Span • Framework Design

3. Power Save Protocols • Our topic for this project is power save protocols. • Power save protocols save energy by keeping node radios off as much as possible. • Why completely turn radios off? • Radio power usage is dominated by the idle state!

4. Power Save Protocols • A node sending data at 2 Mbps and receiving data at 2 Mbps from each of four neighbors uses only 1% more power than an idle interface. [4] • So by reducing the amount of transmissions, reducing the transmission radius, reducing packet size, etc. you can only hope to save a fraction of 1% of energy usage.

5. Protocol Energy Consumption [2]

6. Adaptive Energy-Conserving Routing for Multihop Ad Hoc Networks Ya Xu, John Heidemann, and Deborah Estrin. “Adaptive energy-conserving routing for multi-hop ad hoc networks.” Technical Report 527, USC/Information Sciences Institute, October 2000.

7. BECA/AFECA • This paper was an early power save protocol. • Two algorithms are presented: • BECA: Basic Energy-Conserving Algorithm • AFECA: Adaptive Fidelity Energy-Conserving Algorithm

8. BECA • Each node wakes up every Ts seconds and listens for traffic for Tl seconds. • If no traffic for this node is received within Tl seconds, go back to sleep for another Ts seconds. • If traffic is received, go into the active state. • Transition back into the sleep state when no traffic is received for Ta seconds.

9. BECA Node States

10. Route Setup in BECA • All nodes are initially asleep when A decides to send data to B. B C D E A

11. Route Setup in BECA • A continues to try to send RREQs to C. Within Ts seconds, C enters listening state and receives the RREQ, and C then enters the active state. B C D E A

12. Route Setup in BECA • C continues to try to send the RREQ to B, D, and E, until within Ts seconds they receive it and transition into the active state. • B replies with the RREP and starts communicating with A via C. B C D E A

13. Route Setup in BECA • Since no traffic is being passed through D and E, within Ta seconds they will enter the sleeping state. Now only the nodes that need to be awake are awake. B C D E A

14. BECA • This is a very simple power save protocol. • Should not be used with “a priori” routing algorithms like distance vector. • Can you see why? • Results show nodes save an average of 40-50% of their energy over plain AODV! From http://www432.pair.com/linton/hugg/gorecan.jpg

15. AFECA • Everything is the same as BECA, except node sleep time varies with network density. • When a node overhears a neighbor, it adds the neighbor to a neighbor set. After some time (Te) without overhearing this neighbor, the neighbor is removed from the neighbor set. • Let N be the number of nodes in the neighbor set.

16. AFECA Sleep Time • AFECA sleep time is denoted by TSA. • Tsa = Random(1,N) x Ts • What do we gain by sleeping for Tsa instead of Ts? • In dense areas, we should be able to sleep longer (on average) since there are more nodes capable of routing traffic.

17. AFECA Issues • AFECA is only intended for networks of uniform density. • The middle node below has a high number of neighbors, so he sleeps longer. This is bad!

18. AFECA Results • AFECA saves 2-5% more energy over BECA • The big advantage of AFECA is network lifetime (time until all nodes die): • BECA extends network lifetime by 20% over AODV • AFECA extends network lifetime by 55% over AODV • A fourfold increase in AFECA node density doubles network lifetime.

19. Geography-informed Energy Conservation for Ad Hoc Routing Ya Xu, John Heidemann, and Deborah Estrin. “Geography-informed energy conservation for ad hoc routing,” in Proceedings of 7th Annual International Conference on Mobile Computing and Networking, pp. 70-84, July 2001.

20. GAF: Geographical Adaptive Fidelity • Main ideas: • Each node knows its location • Nodes are partitioned into grid squares, where any two nodes in adjacent grid squares are within range of each other. • At any given time, only one node in each grid square needs to be awake to route data. • Active grid square nodes are cycled.

21. Adjacent Grids • Any node in the yellow grid squares are within range of all nodes in the red grid square.

22. Grid Square Size • All nodes (red circles) are within range of each other. If R is our radio range, how big can our grid squares be?

23. Grid Square Size • Our grid squares have to be small enough for these two nodes (worst case) to reach each other. Let R be our node’s radio range and x be the grid square’s width. Solve for x! x x x x x R x x

24. Grid Square Size – Easy Math • From high school: a2+b2=c2 • (x)2+(2x)2=R2 x x x x x R x x

25. Grid Square Size – Easy Math • From high school: a2+b2=c2 • (x)2+(2x)2=R2

26. Active Nodes • Here is an example ad-hoc network broken up into grids. Only the red nodes are on, the yellow nodes can sleep.

27. Active Nodes • After a while, some of the inactive nodes will take over the role of the active node when the current active node’s power level drops below theirs.

28. Active Nodes • In this image, three inactive nodes have taken over the role of active node for their grid square.

29. GAF Node States • Sleeping: Radio is in sleep mode. • After Ts seconds, node enters discovery state. • Discovery: Nodes are in the process of selecting this grid square’s active node. • After Td seconds with no other higher ranking node becoming active, node enters active state. • If a higher ranked node sends a discovery message, this node re-enters the sleep state. • Active: This node is acting as a grid square’s active node. • If a higher ranked node sends a discovery message, this node re-enters sleep state. • After Ta seconds, this node re-enters discovery state.

30. GAF Node States

31. Paper Results • GAF saved each node an average of 40-60% of its energy over bare AODV. • Varies between 40-60% based on simulated node movement patterns. • GAF was able to triple to quadruple network lifetime over AODV. • Higher node density increases network lifetime. • Practically no increase in latency or decrease in packet loss if GAF nodes are transit only.

32. GAF Wrap-Up • Parameters are customizable (Ts, Td, Ta, etc.) • Ranking is customizable (usually, your amount of remaining power is your rank.) • Like Span, GAF runs independently of the routing protocol. • Since the active node might move out of its grid square before the other nodes wake up, active nodes can advertise the time they expect to leave the grid square. • Any questions on GAF?

33. Span: An Energy-Efficient Coordination Algorithm for TopologyMaintenance in Ad Hoc Wireless Networks Benjie Chen, Kyle Jamieson, Hari Balakrishnan, and Robert Morris. “Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks.” ACM Wireless Networks Journal, 8(5), 481-494, September 2002.

34. Span Requirements • Allow as many nodes as possible to turn their radio receivers off most of the time. • Forward packets between any source and destination with minimally more delay than if all nodes were awake. • Provide about as much total capacity as the original network, since otherwise congestion may increase. • Don’t make assumptions about link layer’s facilities for sleeping. • Inter-operate with whatever routing system the ad hoc network uses.

35. Span Approach • Distributed backbone selection algorithm. • Nodes periodically decide whether to sleep or stay awake. • Nodes announce coordinator willingness by a random time interval two factors: • Battery level • Neighbor count • Nodes switch state periodically between being a coordinator and being a non-coordinator.

36. Span Achieved Goals • Elect enough coordinators so that every node is in radio range of at least one coordinator. • Rotate the coordinators in order to ensure that all nodes share the task of providing global connectivity roughly equally. • Minimize the number of nodes elected as coordinators. • Increases network lifetime • No significant loss of capacity or increase in latency • Elect coordinators using only local information in a decentralized manner.

37. Coordinator Eligibility Rule • A non-coordinator node should become a coordinator if it discovers, using only information gathered from local broadcast messages, that two of its neighbors cannot reach each other either directly or via one or two coordinators. C N N

38. Backoff Delay Ni = the number of neighbors for node i Ci = the number of added connections among neighbors if i were coordinator. Er = remaining energy of node Em = maximum energy of node R = random value between 0 and 1 T = round-trip delay of a packet • The likelihood of becoming a coordinator falls as a coordinator uses up battery. • A node that connects partitions together will always be elected a coordinator.

39. Coordinator Withdrawal WT = 3 x Ni x T sleeping every pair of neighbors can reach each other through another coordinator tentative after delay after CT coordinator after WT

40. Span HELLO Packets • Source ID • Node position • Is Coordinator • Is Tentative • Coordinator list • Neighbor list

41. Span Scenario Any questions on Span?

42. NodeRangeListener NodePowerListener +Point getPosition() +void nodeEnteredRange(AdHocNode node) +void nodeLeftRange(AdHocNode node) +nodeTurnedOn(AdHocNode node) +nodeTurnedOff(AdHocNode node) Packet AdHocNode -AdHocNode source -AdHocNode destination -Date startTime -int size -int nodeId -AdHocWorld world -Point position -Point movement -double batteryLevel -boolean isOn -Vector<AdHocNode> neighbors -Vector<NodePowerListener> listeners +void sendPacket(Packet packet) +void start() UML: AdHocNode

43. PacketListener +void packetDelivered(Packet packet) +void packetLost(Packet packet) AdHocWorld -Dimension size -double transmitRange -double transferRate -double consumptionRateOn -double consumptionRateOff -double maxSpeed -Vector<AdHocNode> nodes -Graph<AdHocNode> graph +AdHocNode getNextNode(AdHocNode src, AdHocNode dest) +void start() UML: AdHocWorld

44. UML: Algorithms AdHocNode SpanNode AFECANode GAFNode

45. Questions? • Ya Xu, John Heidemann, and Deborah Estrin. “Adaptive energy-conserving routing for multi-hop ad hoc networks.” Technical Report 527, USC/Information Sciences Institute, October 2000. • Ya Xu, John Heidemann, and Deborah Estrin. “Geography-informed energy conservation for ad hoc routing,” in Proceedings of 7th Annual International Conference on Mobile Computing and Networking, pp. 70-84, July 2001. • Benjie Chen, Kyle Jamieson, Hari Balakrishnan, and Robert Morris. “Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks.” ACM Wireless Networks Journal, 8(5), 481-494, September 2002. • Stefano Basagni, Marco Conti, Silvia Giordano, and Ivan Stojmenovic. Mobile Ad Hoc Networking. John Wiley & Sons, 2004. ISBN 0-471-37313-3.