Abbasi et al. [28] proposed a self-healing, lightweight and localized distributed recovery algorithm that includes the application level tasks constraints on the actors’ mobility while restoring the network connectivity. The idea is to take application level constraint on actor
mobility based upon certain emergency. In such type of scenario, the authors considered some natural disaster like earth quake or hurricane and used UMRV (unmanned robotic vehicles) equipped with sensors for helping the victims. The job of these sensors is to probe the
existence of human live being in the vicinity and report it to the actors. After receiving such type of report, the nearby actors are responsible to reach the location and provide necessary
life support until the rescue team arrives. Therefore, at the time when an actor is busy in providing emergency help to a survivor under rubbles, task termination and mobility of this unit may cause serious damage to the operation. However, after completing the operation,
the unit can be mobilized to any location without constraints. For constrained mobility, the authors have used mobility index (MRI) value for each actor based on its availability to move and mobility potential index (MP) value to calculate the number of neighboring actor which
it can moves. This MRI is then used to decide whether an actor is involved in the connectivity restoration process or not. Now, every actor in this approach would maintain MRI and MP in the range (0-l). MRI is entirely based on the importance of current task. A MRI zero means the actor is free; while a value one means the actor cannot move. In addition to MRI, each node would maintainMP by tracking its 1-hops neighbors and MRI has highest priority over
MP. C2AM approach has three steps: