Mobility is one of the main factors affecting the design and performance of wireless networks. Mobility modeling has been an active field for the past decade, mostly focusing on matching a specific mobility or encounter metric with little focus on matching protocol performance. Recently, new generations of wireless and mobile services have emerged based on communal aspects of mobile societies; conventionally not considered in mobility modeling. This study investigates the adequacy of existing mobility models in capturing various aspects of human mobility behavior (including communal behavior), as well as network protocol performance. This is achieved systematically through the introduction of a framework that includes a multi-dimensional mobility metric space to measure individual, pair-wise (encounter) and group (community) metrics.

We then introduce COBRA, a new mobility model capable of spanning the mobility metric space to match realistic traces. A methodical analysis using a range of protocol (epidemic, spray- wait, Prophet, and Bubble Rap) dependent and independent metrics (modularity) of various mobility models (SMOOTH and TVC) and traces (university campuses, offices, and theme parks†) is done.

Our results indicate significant gaps in several metric dimensions between real traces and existing mobility models. Our findings clearly show that COBRA matches communal aspect and realistic protocol performance, reducing the overhead gap (w.r.t existing models) from 80% to less than 12%, showing the efficacy of our framework based upon the metric space matching. We hope for our new mobility model to provide a more realistic and accurate alternative for mobility modeling; to aid in the analysis, simulation, and the design of future communication protocols.

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