Biogeography based anticipatory computing framework for intelligent battle field planning

It is possible to go and physically observe any situation under the area of our reach, but this is not so for the areas beyond our physical boundaries. For the purpose, a methodology inspired from nature is proposed using remote sensing inputs based on swarm intelligence for the anticipatory computation of the regions beyond our borders. The paper presents a nature inspired anticipatory computing framework for intelligent preparation of the battlefield. The algorithm predicts the most suitable destination for the enemy troops to position their forces, for which it uses the population based optimization technique i.e. Biogeography Based Optimization. The paper also introduces a new concept of efforts required in migration to a high HSI solution for optimization in BBO and hence also proposes an advanced optimization technique that was originally proposed by Dan Simon in December, 2008 [5]. Hence, the algorithm can be used to improve the Ant Colony Optimization (ACO) approach, since it lacks the ability to predict the destination and can only find a suitable path to the given destination, leading to coordination problems and target misidentification which can lead to severe casualties. The algorithm can be of major use for the commanders in the battlefield who have been using traditional decision making techniques of limited accuracy for predicting the destination.