Random way point mobility

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elvin eziama
elvin eziama on 15 Mar 2017
Commented: Image Analyst on 15 Mar 2017
I was told that I have to run genMobileData.m in order to generate the data (mat) files.
but genMobileData.m requires another mat file for input, which can be generated using the toolkit found at
http://www.mathworks.com/matlabcentral/fileexchange/30939-random-waypoint-mobility-model told with http://www.mathworks.com/matlabcentral/fileexchange/30939-random-waypoint-mobility-model, which are test_Execute.m, Generate_mobility.m , and test_animation.m. Honestly I have tried using them to generate these data to be used in analyzing mobile adhoc network trust management based on the directive given, which are as follows:==================================== Data Generation ====================================
Random Way Point modibility model: use files in Random_Waypoint. Entry point: test_Execute.m For more information: http://www.mathworks.com/matlabcentral/fileexchange/30939-random-waypoint-mobility-model --> ./mobility_track_input/vs_node_50_7_24.mat
Use 'genMobileData.m' for other input generation and data pre-processing: * process the 1-hop neighbors -> encMat_50_7_24.mat * number of service requests in queue * number of concurrent requests * cost/reward --> 20000 results will be generated and stored in allData60_20000.mat * malicious nodes -> malNode1.mat * distributing data to each nodes --> accHist_50_7_24.mat
Use 'preprocess_accHist.m' for preprocessing data based on recommendation attacks --> aggrHist_mal***_50_7_24.mat
Use 'genServiceHistory.m' * binary service satisfaction --> 'servBin_50_7_24.mat' * similarity for nodes (used for Adaptive trust) --> sim_adaptive.mat
NOTE: you should manually input your \beta_j @gt_weight
For Beta Reputation: Binary observations are accumulated by 'preprocess_accHist.m' --> numInd_mal***_50_7_24.mat
For Adaptive Trust: Binary observations are discounted by time 'preprocess_accHist_forAdaptiveTrust.m' --> TrustMat_***_50_7_24.mat

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