Collaborative Data-Foraging Based on Spatio-Temporal Indirect Communication

In nature, social insects living in dynamic environments must seek for valuable food resources that may disappear. They collaborate by sharing the location of the resources with the colony to reach and retrieve as much food as possible. Similarly, through Data-foraging mobile sensors retrieve samples in environments where the sources location and their relevance change continuously. As social insects, Collaborative Data Foraging (CDF) is intended to share information through the exchanging of messages among multiple sensors. Indeed, an essential task in CDF is to determine from the individual views of sensors, where and when the samples were retrieved. Currently, most of the proposed solutions regarding data retrieval for dynamic environments assume direct communication among the mobile entities or that a shared global view of the environment is available. However, direct communications are difficult to achieve in dynamic environments due to the lack of perdurable transmission links among sensors. In addition, the distributed asynchronous nature of the problem makes unachievable to agree on a shared long-term global view. This paper presents a collaborative data-foraging mechanism based on spatio-temporal indirect communication for multiple mobile sensors. A novel bio-inspired message unit called pheromone is introduced, acting as an intermediary in the collaboration process. The presented solution requires neither coupled enduring transmissions links nor global temporal references to preserve the coherence of the interactions. The pheromone-based solution captures both spatial and temporal references, by establishing fuzzy-causal relations to determine when and where the samples were retrieved.