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Coordination in sensor, actuator and robot networks Patrick Zeller Wireless Ad Hoc Networking University of Ottawa 21. November 2011 Patrick Zeller Coordination in sensor, actuator and robot networks

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Page 1: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Coordination in sensor, actuator and robotnetworks

Patrick Zeller

Wireless Ad Hoc NetworkingUniversity of Ottawa

21. November 2011

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 2: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Overview

1 Introduction: Model and Problem

2 Sensor-Sensor Coordination

3 Sensor-Actor CoordinationDEPR

4 Actor-Actor CoordinationAuction Aggregation Protocols

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 3: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Overview

1 Introduction: Model and Problem

2 Sensor-Sensor Coordination

3 Sensor-Actor CoordinationDEPR

4 Actor-Actor CoordinationAuction Aggregation Protocols

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 4: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Model

sensor: low-cost, low-power, detectphysical condition/event andtransmit to actors

actor/robot: resource-rich, collectsensor data and act accordingly

event: physical phenomenon,requires action by actuators

e

e

sensor

actor

event

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 5: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Model

Level 1:sensor-sensor

Level 2:sensor-actor

Level3:actor-actor

cluster headsensor

actor

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 6: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Overview

1 Introduction: Model and Problem

2 Sensor-Sensor Coordination

3 Sensor-Actor CoordinationDEPR

4 Actor-Actor CoordinationAuction Aggregation Protocols

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 7: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Sensor-Sensor Coordination

sensor-sensor coordination problem:sense in efficient way⇒ min. energy consumption, max. lifetime and coverage

techniques: area coverage, sleeping in turns, clustering,grid-partitioning

as seen in lecture!

cluster headsensor

figure: I.Stojmenovic

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 8: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Overview

1 Introduction: Model and Problem

2 Sensor-Sensor Coordination

3 Sensor-Actor CoordinationDEPR

4 Actor-Actor CoordinationAuction Aggregation Protocols

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 9: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Sensor-Actor Coordination

sensor-actor coordination problem:establish efficient data paths from sensors to actors⇒ min. energy consumption, min. delay

figure taken from [1]

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 10: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Reliability

Definition

Sensor data packets received by an actor within a given latencybound are reliable.The event reliability is the ratio of reliable data packets over allpackets in the decision interval.The event reliablility threshold is the minimum event reliabilityrequired.

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 11: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Sensor-Actor Coordination Problem as ILP Problem

integer linear programming: optimal solution for minimumenergy da-trees such that reliability constraint is met

... you do not need to know this!

complete topology information needed, communicationoverhead, NP complete⇒ use distributed algorithm instead

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 12: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

DEPR: Distributed Event-driven Partitioning and Routing

approximate solution

local information

greedy next-hop selection

feedback from actors

sensors probabilistically increase ordecrease transmission power basedon feedback

synchronized network

figure taken from [1]

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 13: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

State transitions of sensors in DEPR

IDLE START-UP

SPEED-UP

AGGREGATION

[event sensed]OR[used as relay]

[reliability too low]

[reliability too low]

[reliability too high]

[reliability too high]

actors calculate collective(!) reliability from all sensors in theirtree: reliability = reliable packets

all packets

sensors probabilistically increase or decrease transmissionpower based on feedback from actors

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 14: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Start-Up State

entered when sensing event or chosen as next hop by othersensor

sensor i selects minimum cost next hop by two hop rule:costj = constant + energy(i , j) + energy(j , actor closest to j)

estart-up

1. 2.

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 15: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Speed-Up State

entered when reliability below threshold ⇒ reduce delay

greedy routing: next hop is node within range and closest toany actor

e

1. 2.

feedbacke

speed-up

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 16: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Aggregation State

entered when reliability above threshold ⇒ reducetransmission power

next hop is closest node that is part of da-tree + rules

rules:- if part of same tree, must be closer to actor- if in different tree, I must be leaf and next hop closer to itsactor than I am to this actor

e

1. 2.

feedbacke

aggregation

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 17: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Handling Voids

sensor enters recovery mode when no neighbor is closer totheir closest actor than I am to my closest actor⇒ use face traversal

in speed-up state, choose highest hop number on recoverypath as next hop

1

2

3

45

speed up

face traversal

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 18: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Overview

1 Introduction: Model and Problem

2 Sensor-Sensor Coordination

3 Sensor-Actor CoordinationDEPR

4 Actor-Actor CoordinationAuction Aggregation Protocols

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 19: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Actor-Actor Coordination

actor-actor coordination problem: allocate acting tasks toactors/robots in “optimal” way

optimization dimensions:- action completion time- energy consumption- travel distance

different versions of task allocation problemhere: event reported to one robot, find best robot to respond

e

robot/actor

evente

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 20: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Auction based Solution: SAP

Simple Auction Protocol (SAP): flood request for serviceto all actors

retransmit request for service exactly once

actors reply with offer by seperate routing task⇒ many messages, high response time but optimal solution

erequest for service

offer/bid

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 21: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Improvement k-SAP

k-SAP: only flood request for service to k-neighborhood

actors reply with offer by seperate routing task

e

request for service

offer/bid1-SAP:

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 22: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Improvement SAAP

SAAP: Simple Auction Aggregation Protocolinclude ID of parent in retransmission of request for service⇒ creates response treeuse tree to report back: wait for bids of children, reply withbest bid in subtreeif node hears noone listing it as parent, it becomes leaf andstarts reporting back

e

offer/bid8 4

2

4

R1R2

R4

R5

cost(R1)=2cost(R2)=3cost(R3)=5cost(R4)=4cost(R5)=8

R3

⇒ combine improvements to k-SAAPPatrick Zeller Coordination in sensor, actuator and robot networks

Page 23: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Improvement k-AAP

k-AAP: robots already learned cost of all robots in theirk-neighborhoodinclude best known cost C in retransmission of request forserviceonly retransmit when cost ≤ C in k-hop neighborhoodleafs start reporting backuse tree to report back, reply with best bid in subtree

eR1

R2

R4

R3

cost(R1)=2cost(R2)=3cost(R3)=3cost(R4)=1cost(R5)=5cost(R6)=5cost(R7)=5cost(R8)=5cost(R9)=4

R8R5

R9

R7

R6C=1

2-AAP

only R1, R2 retransmit

C=1

C=1

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 24: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Example: 2-AAP

eR1

R2

R4

R3

cost(R1)=2cost(R2)=3cost(R3)=3cost(R4)=1cost(R5)=5cost(R6)=5cost(R7)=5cost(R8)=5cost(R9)=4

R8R5

R9

R7

R6C=1

C=1

C=1

eR1

R2

R4

R3

R8R5

R9

R7

R61

1

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 25: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Summary

Purpose: learn techniques and algorithms used in coordinationof sensor-actor/robot networks

Sensor-Actor Coordination: DEPR-Protocol: creation of datareporting trees from sensors to actors

Actor-Actor Coordination: Auction-based protocols for taskassignment with reduced message overhead

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 26: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Questions

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 27: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Question 1

eR1

R2R4

cost(R1)=5cost(R2)=6cost(R3)=8cost(R4)=4cost(R5)=2cost(R6)=4cost(R7)=4cost(R8)=3cost(R9)=1

R7

R5

R6

R3

R8

R9

k-AAP is an auction based protocol in robot-robot coordination to find the best robotto respond to an event reported to a collector robot. Every robot knows the actingcost of all the robots in its k-neighborhood. Starting from the collector robot, a requestfor service is broadcasted. This message includes the value C of the best cost that therobot that transmitted this message is aware of. Every robot retransmits the messageonly if there is a robot with cost <= the received C in its k-neighborhood and updatesC accordingly.Which robots will retransmit the request for service when an event is reported to collector robot R1 and 2-AAP is used? What is the value of C in each message?

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 28: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Answer 1

eR1

R2R4

R7

R5

R6

R3

R8

R9

C=4

C=4

C=2C=2

C=2

C=3

C=1

C=1

R1 retransmits, C=4R2 retansmits, C=2R4 retransmits, C=2R6 retransmits, C=3R7 retransmits, C=1R8 retransmits, C=1R3,R5,R9 don't retransmit

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 29: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Question 2

DEPR is a distributed protocol in sensor-actor coordination which is used to find data aggregation trees from sensors to actors. According to feedback from the actors aboutobserved reliability/delay, sensors transition into a speed-up or an aggregation state. Inthe speed-up state the next hop is chosen as the node within transmission range whichis closest to any actor. In the aggregation state a node i chooses its next hop j as thenode that is closest to itself for which the following conditions are met:- if i and j are in the same tree, j must be closer to the actor- if i and j are in a different tree, i must be leaf and j closer to its actor than i is to the actor of jHow do the data aggregation trees change if N1 and N2 enter the aggregation stateand N3,N4,N5 enter the speed-up state?

tran

smis

sion

ran

ge

N1N2

N3

N4

N5

N6

N7

N8

N9N10

A1

A2

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 30: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Answer 2

N1N2

N3

N4

N5

N6

N7

N8

N9N10

- N2 changes next hop to N1- N1 changes next hop to N7- N3 changes next hop to A2- N4 changes next hop to A2- N5 changes next hop to A2

A1

A2

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 31: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Question 3

DEPR is a distributed protocol in sensor-actor coordination which is used to find data aggregation trees from sensors to actors. Actors broadcast collective feedback aboutobserved delay of sensor data packets to all sensors in their tree. Data packetsreceived by an actor within a given latency bound are called reliable. The reliabilityis the ratio of reliable data packets over all packets received by an actor in an interval.Assume that every sensor shown below generates one packet of sensor data perinterval. Each sensor forwards the packets towards the actor as soon as they aregenerated or received. One hop takes 1 unit of time. The intervals are long enough sothat every packet reaches the actor before another interval starts. Packets with latency<=2 are considered reliable. What is the value of the reliability observed by actor A1?The minimum reliability required by the application is 2/3. To which state will some nodesprobably transition to after receiving feedback from the actor?

A1

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 32: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Answer 3

A1

reliability observed by A1: 7/127/12 < 8/12=2/3 so reliability is too low and some nodes willprobably transition to the speed-up state

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 33: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

Thank you!

Patrick Zeller Coordination in sensor, actuator and robot networks

Page 34: Coordination in sensor, actuator and robot networks · DEPR: Distributed Event-driven Partitioning and Routing approximate solution local information greedy next-hop selection feedback

References

1 Melodia, T.; Pompili, D.; Gungor, V.C.; Akyildiz, I.F.; , ”Communication and Coordination in WirelessSensor and Actor Networks,”Mobile Computing, IEEE Transactions on , vol.6, no.10, pp.1116-1129, Oct.2007

2 Ivan Mezei, Veljko Malbasa, and Ivan Stojmenovic. 2009. Auction Aggregation Protocols for WirelessRobot-Robot Coordination. In Proceedings of the 8th International Conference on Ad-Hoc, Mobile andWireless Networks (ADHOC-NOW ’09), Pedro M. Ruiz and Jose Joaquin Garcia-Luna-Aceves (Eds.).Springer-Verlag, Berlin, Heidelberg, 180-193.

3 Haidong Yuan; Huadong Ma; Hongyu Liao; , ”Coordination Mechanism in Wireless Sensor and ActorNetworks,”Computer and Computational Sciences, 2006. IMSCCS ’06. First InternationalMulti-Symposiums on , vol.2, no., pp.627-634, 20-24 June 2006

4 Gasparovic, B.; Mezei, I.; , Auction aggregation protocols for agent-based task assignment in multi-hopwireless sensor and robot networks,Advanced Intelligent Mechatronics (AIM), 2011 IEEE/ASMEInternational Conference on , vol., no., pp.247-252, 3-7 July 2011

5 Mezei, I.; Malbasa, V.; Stojmenovic, I.; , ”Greedy extension of localized auction based protocols for wirelessrobot-robot coordination,Intelligent Systems and Informatics, 2009. SISY ’09. 7th International Symposium

Patrick Zeller Coordination in sensor, actuator and robot networks