Discovering Socio-Behavioral Metrics in Mobile Ad-Hoc Systems


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Abstract


This paper proposed and developed socio-metrics for MANET performance evaluation. It is assumed that a MANET node is a socio-cognitive-technology system whose entities assume the behaviors of human and technology agents. Using the principles of network connectivity, we identify both intrinsic- and system level extrinsic- factors for the model development. The values of the intrinsic- and extrinsic- variables are generated using known fuzzy models. We analyze the contributions of the socio-metrics to the overall MANET system performance. The simulation outcomes inform that: (a) MANET nodes seek to achieve the same system goals after a significant period of interaction. We observe this as (a) MANET with less trust (10%) initially increased its trust level to about 25% after nine iterations of a simulation experiment; (b) Nodes will collaborate to achieve a singular system level goal as shown in balancing elements of the system level performance where high cooperation and self-awareness scores were reduced so as to create more trust and shared information awareness. This was achieved by incorporating behavior updating mechanisms into the simulation model. The learning mechanisms systematically train nodes in the MANET system to cooperate, trust, share information, and have self-awareness by adjusting their individual achievement weights
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Keywords


Fuzzy Markov Decision Process; Possibility Distribution; MANET

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