Download pptx - 應急蜂巢式行動網路建構排程

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CCN()CCN22OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

33

44

55OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

66Myth

()

7

7Service destruction in the base stationThe destruction of the strong earthquakesPower outageThe backhaul of the base station was destroyed

Critical hardware equipments were knocked downPower outageBroken cooling system and overheated switch

8

8

993G 3G SGSNGGSNMSC/VLRGMSCPLMN , PSTN ,ISDN , etcInternet

USIMMECuUuNodeBHLRRNCRNCCNExternal NetworksUTRANUE1231010OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

1111Golden 72 HoursThe survival rate is 90% within 24 hours; 50% between 25 and 48 hours; 20% between 49 and 72 hours. The chances of survival over 72 hours are quite rare.

: http://baike.baidu.com12121313OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

1414Challenges and needs of constructionEasy access to the equipmentsRapid constructionLow cost

Challenges and needs of system operationLarge amount of terminals and low deployment costEasy to use without special trainingPriority-Based admission controlMobility Support1515OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

1616 -(Walkie-Talkie)

(e.g. )

17

17(Amateur radio)

18 -

18(MEO: Medium-Earth Orbit)5000~15000km(Odyssey)(LEO: Low-Earth Orbit)500~1500kmMotorola(Iridium)

19 -19

-202018118

21 -

21Specialized Emergency Communication Systems

22

A hand-held Project 25 radio used in US systems Project 2522MANET(Mobile Adhoc Network )

P2PnetMulti-hop Ad-Hoc Network MANETInternetVoIP

- MANET2323Autonomous Networked Robots for the Establishment of Wireless Communication in Uncertain Emergency Response Scenarioswireless ad hoc network

An Integrated Communication-Computing Solution in Emergency Management (heterogeneous meshed communication system)

Ad Hoc Communications for Emergency Conditionsad hoc2424Walkie-TalkieAmateur radio()()Project 25()MANET2525OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

2626Structure of Contingency Cellular Network (CCN)Connected station()Isolated station()Contingency Recover Package()Power moduleInter-Cell Communications Module (ICC Module)Emulated Controller Module (EC Module)Satellite Communications Module (option)

272728Structure of Contingency Cellular Network (CCN)

2829

Structure of Contingency Cellular Network (CCN)2930Walkie-TalkieAmateur radio()()Project 25()MANETCCN30The procedure of deployment and operationStage 1: Damage Assessment PhaseStage 2: Planning PhaseStage 3: Deployment PhaseStage 4: Operation Phase

3131IntranetIntranetpriority based admission control policyEC-moduleforwarding treeCCN


3333NP-complete problem:

(Single-Operation)

(Multiple -Operation)

3434NPC problem -(Single-Operation)

(Single-Machine Scheduling)

(Parallel-Machine Scheduling)

3535Common algorithm(Exact Algorithm)(Branch and Bound)(Dynamic Programming)

(Meta-heuristics)Hill-Climbing AlgorithmTaboo Search AlgorithmSimulated AnnealingGenetic AlgorithmParticle Swarm Optimization AlgorithmAnt Colony Optimization Algorithm3636(Exact Algorithm)(Branch and Bound)()

(Dynamic Programming)3737(Meta-heuristics)Hill-Climbing Algorithm

Taboo Search Algorithm

Simulated Annealing

3838(Meta-heuristics)Genetic Algorithm

Particle Swarm Optimization Algorithm

Ant Colony Optimization Algorithm

3939OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Conclusion

4040:CCN()CCN

:CCN


4242

ScheduleCCN

Forwarding TreeCCN

CCN()()43

43Model 144

44Model 245


4646CCN deployment scheduling problem is NP-Complete

47

4748

48CCN-DS is NP-completeGiven an instance A:[J, P, W] in SMS, we can find an instance B:[N, L, W, E, n] in CCN-DS, such that an optimal solution for B is also an optimal solution for A.Let N = JL = PW = WE = { }n = 149

ABCDEABCDERootSMS problemCCN-DS problem49OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

505051Heuristics algorithm design part one1.Greedyinitial solution2.Iterativeinitial solution better solution51Greedy - 1 NP Complete Greedy

profit

profit

profit

schedule

5252Greedy - 2A=1B=7C=2D=10E=3F=20G=15Profit(A)=1+(7+2)*level weight 1 +(10+3+20+15)* level weight 2

(1 > level weight 1 > level weight 2 > 0) profit53x1x2x3x4profit53Greedy - 3ABC=20D=5E=12FGscheduling[A,B](C=20,D=5,E=12)Cscheduling[A,B,C](D=?,E=?,F=?,G=?)profit5454Greedy algorithm -Flow DiagramGreedy algorithmprofit profit Output : Schedule 5555Part one algorithm -Flow DiagramGreedy algorithm initial solutionyschedule>0profitGreedyYNYNNY565657Heuristics algorithm design part one1.Greedyinitial solution2.Iterativeinitial solution better solution57EX:(3 1 2 5 4)->(3 2 1 5 4)->(3 2 1 5 4)->(3 2 4 1 5)->(4 3 2 1 5)->(5 4 3 2 1)

(2) (2)(1)priority scheduling (5 4 3 2 1)3.profit5858initial solution priority scoreYNschedule profitFinal solutionNYInitial solution59Part two algorithm -Flow Diagram59Pseudo CodeAlgorithm(CCN_TreeData){if(countTreeLevel < considnerTreeLevel){if(LevelDecreasesWeight < 1){initialSchedule = greedyAlgorithm(TreeData, countTreeLevel, LevelDecreasesWeight);}}finalSchedule = improve(initialSchedule);}

greedyAlgorithm(TreeData, countTreeLevel, LevelDecreases){while(NodeIsLegal && AllLegalNode!=null){maxNodeProfit = compare( countProfit(AllLegalNode) );initialSchedule.add(maxProfitNode); }}

countProfit(AllLegalNode){if(nodeLevel < countTreeLevel && nodeLevelWeight > 0){nodeProfit = profit(node,time) + profit(childrenNode, time)*childrenNodeLevelWeight;}}

profit(node, time){profit = nodeMathFunction(time);}

Improve(initialSchedule){start with the smallest priority node;if(the node is not revise && exist lower priority nodes place before than the node in the initialSchedule){change the schedule(move the higher priority node before than the lower one) ;}}6060OutlineIntroduction Communication systems crashRescue time and survival rateGrant challenge of contingency communicationRelated workCommon contingency communication systemsContingency cellular networkScheduling problemCCN deployment scheduling problemDefinitionTime complexity analysisAlgorithm designEvaluation Summary

6161

CCN deployment scheduling problem Enumerative algorithmGreedy algorithmCCN-DS algorithm

1 1 nn>1

1011121314100

6262total profittotal profittotal profitschedule total profit

Deviations from optimum solution =1 [(-) / (-)]= : 1= : 0

EX=1000=950=8001-[(1000-950)/(1000-800)]=0.75

6363Profit function 1

profit functionhard deadlinehard deadline()

6464Profit function 2profit functionsoft deadline(72)hard deadline

6565Profit function 3profit function

6666nodeNext nodeInitial Profit Slope1 Slope2Restore Time 1:2:3:Queue :(filter)67672.nodePriority score=Start Profit * Hard Deadline score * Slope1 * Slope2 * Model score

Start Profit Restore TimeHard Deadline: Slope1 Slope2 : ()

EX : Start Profit=70firth=7020

Download pptx - 應急蜂巢式行動網路 建構 排程

Download pptx - 應急蜂巢式行動網路建構排程