# Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms
## 5 Comparison of the Algorithms
### Communication Needs and Adaptation to Surveillance  
As we have seen in the previous section, the proposed algorithms can be classified attending to objective measurements depending on the type of scenario. However, some of the algorithms make use of intensive communications between the agents, whereas others only need sharing information in specific moments. This may be a drawback when using them in real systems. On the other hand, these algorithms can be used in similar missions, such as surveillance and patrolling, although some modifications might need to be done. The algorithms are qualitatively analyzed hereafter regarding these two issues.  
Figure 17: Efficiency (**a**) and fitness (**b**) for the scenario with obstacles inside the area.  
Figure 18: Efficiency (**a**) and fitness (**b**) for the scenario with the probability distribution of the location of the targets and obstacles inside the area.  
* A1, behaviors set: This algorithm requires a demanding communication system because the behaviors implemented need up-to-date information in order to update the individual map of pheromones, calculate the resulting forces, etc. Surveillance and patrolling are easy to implement: L3 may be eliminated, and visited and non-visited cells may be equally treated; this way, once a zone is visited and its level of pheromones is reduced, it will gradually create pheromones. After some time, it will become a tractor for the agents, which will then return periodically to it.
* A2, random: The random movement only needs communication between agents when they are close and a collision may take place, not needing to share information with other agents. Surveillance and patrolling missions are already covered, since a random walk will statistically revisit the areas with some frequency.
* A3, closest: The requires updated information to know which cells have not been visited yet, besides short-range communication in case a collision may occur. Although the transmitted information is less than for A1, it is also considered as heavy. For surveillance and patrolling, the \"age\" of the cell (measured as time passed since it was last observed) may be used similarly as the probability map.
* A4, boundary: This algorithm needs the same information as A3, which is considered as high. The surveillance task can only be carried out if the essence of the behavior is lost; if for instance, the decision is made as a weighted sum of the isolation index and the age of the cell, the compaction of the search, which is the main value of the algorithm, will be probably lost. Note that the algorithm makes heavy use of the distinction between visited and non-visited cells, which cannot be easily overridden in persistent missions.
* A5, energy: this algorithm is basically similar to the random movement regarding the communication complexity and its use in surveillance and patrolling.
* A6, billiard: similarly to A2 and A5, the billiard movement only needs the agents to share information if a collision may take place. The surveillance task is already included in the algorithm, since it recursively visits the cells.
* A7, lanes: This requires only medium communications because the agents must only share the lanes they are visiting, which happens with low frequency. The surveillance mission is fulfilled if the visited lanes are marked with incremental numbers (instead of visited and non-visited). The proximity of the lanes and their visit index (i.e., the number of times the lane has been observed) may be then considered together. To do this, a weighted decision may be made.