off by one power-save protocols corey andalora keith needels

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Off By One Power-Save Protocols Corey Andalora Keith Needels

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Off By OnePower-Save Protocols

Corey Andalora

Keith Needels

Agenda

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

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!

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.

Protocol Energy Consumption [2]

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.

BECA/AFECA

This paper was an early power save protocol.

Two algorithms are presented:BECA: Basic Energy-Conserving AlgorithmAFECA: Adaptive Fidelity Energy-Conserving

Algorithm

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.

BECA Node States

Route Setup in BECA

All nodes are initially asleep when A decides to send data to B.

A

B

CD E

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.

A

B

CD E

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.

A

B

CD E

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.

A

B

CD E

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

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.

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.

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!

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

AODVAFECA extends network lifetime by 55% over

AODV A fourfold increase in AFECA node density

doubles network lifetime.

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.

GAF: Geographical Adaptive Fidelity

Main ideas:Each node knows its locationNodes 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.

Adjacent Grids

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

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?

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!

R

x

x

x

x

x

x

x

Grid Square Size – Easy Math

From high school: a2+b2=c2

(x)2+(2x)2=R2

R

x

x

x

x

x

x

x

Grid Square Size – Easy Math

5

Rx

From high school: a2+b2=c2

(x)2+(2x)2=R2

Active Nodes

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

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.

Active Nodes

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

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.

GAF Node States

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.

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?

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.

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.

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:1. Battery level2. Neighbor count

Nodes switch state periodically between being a coordinator and being a non-coordinator.

Span Achieved Goals

1. Elect enough coordinators so that every node is in radio range of at least one coordinator.

2. Rotate the coordinators in order to ensure that all nodes share the task of providing global connectivity roughly equally.

3. Minimize the number of nodes elected as coordinators.

• Increases network lifetime• No significant loss of capacity or increase in latency

4. Elect coordinators using only local information in a decentralized manner.

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

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 nodeR = random value between 0 and 1T = 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.

Coordinator Withdrawal

WT = 3 x Ni x T

tentative

coordinator

sleeping

after WT

every pair of neighbors can reach each other through another coordinator

after CT

after delay

Span HELLO Packets

Source ID Node position Is Coordinator Is Tentative Coordinator list Neighbor list

Span Scenario

Any questions on Span?

UML: AdHocNodeNodeRangeListener

+Point getPosition()+void nodeEnteredRange(AdHocNode node)+void nodeLeftRange(AdHocNode node)

NodePowerListener

+nodeTurnedOn(AdHocNode node)+nodeTurnedOff(AdHocNode node)

AdHocNode

-int nodeId-AdHocWorld world-Point position-Point movement-double batteryLevel-boolean isOn-Vector<AdHocNode> neighbors-Vector<NodePowerListener> listeners

+void sendPacket(Packet packet)+void start()

Packet

-AdHocNode source-AdHocNode destination-Date startTime-int size

UML: AdHocWorld

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()

PacketListener

+void packetDelivered(Packet packet)+void packetLost(Packet packet)

UML: Algorithms

AdHocNode

SpanNode

GAFNode

AFECANode

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.