Although the holy grail to store and manipulate data in Edge infrastructures is yet to be found, state-of-the-art approaches demonstrated the relevance of replication strategies that bring content closer to consumers: The latter enjoy better response time while the volume of data passing through the network decreases overall. Unfortunately, locating the closest replica of a specific content requires indexing every live replica along with its location. Relying on remote services for such a aim enters in contradiction with the properties of Edge infrastructures as locating replicas may effectively take more time than actually downloading content. At the opposite, maintaining such an index at every node would prove overly costly in terms of memory and traffic. In this paper, we propose a decentralized implementation of content indexing called AS-cast. Using AS-cast, every node only indexes its closest replica; and all connected nodes with a similar index compose a partition. AS-cast is (i) efficient, for it uses partitions to lock down the traffic generated by its operations to relevant nodes, yet it (ii) guarantees that every node eventually acknowledges its closest replica despite concurrent operations. Our prototype, implemented on PeerSim, shows that AS-cast scales well in terms of generated messages and termination time. As such, AS-cast can constitute a novel building block for geo-distributed services in need of efficient resource sharing in the vicinity of regions.