Implementation and Simulation of a Mobile Sensor Network Using Lambda Architecture
The field of swarm robotics has continued to grow in recent years, branching into new fields that require more complex algorithms and faster response times to control. One example of these new fields is the mobile sensor network; a swarm where each agent acts as a sensor and is able to optimize it's abilities by moving the sensors. This thesis proposes an algorithm in order to control a mobile sensor network through the use of cloud computing and the Lambda architecture. The paper formulates the different components to such an algorithm, then simulates the algorithm in a Gazebo simulation. Different cloud architectures are compared in simulation in order to assess the optimal one for this application. Finally, data reduction techniques are applied in order to enhance the capabilities of the algorithm through the use of a formulated optimization problem and simulated annealing.