摘要： Nowadays, the processing of data obtained as a result of airborne laser scanning by a group of unmanned aerial vehicles includes up to eight different stages. From the point of view of organizing such processing, it is reasonable to use modern cloud technologies. The paper proposes a new method for processing this type of data based on the social model of completing game quests. Portions of data arrive at a computing system consisting of several clouds where, in turn, multifunctional SaaS nodes operate. Each of the nodes can process one data portion once, which allows to exclude the principle of exclusive use of one node for all stages of processing a data portion. The paper proposes an original algorithm for determining the optimal node for the next stage of processing, which takes into account: the time of data portions movement between SaaS nodes, in fact, processing and waiting in the node queue. Due to carried out experiments, it was found that the implementation of the developed quest method allows to reduce the workload of SaaS nodes by the uniform distribution of processing between all nodes, which was to an average of 30%. Additionally, in the case when the number of processing nodes is less than three, the efficiency of the method decreases to zero. This paper suggests that the ques method can also be used on board of the nodes of a flying sensor network during airborne laser scanning of the area in rapid-response systems.