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This paper proposes an efficient heuristic for solving the minimum-intracommunication clustering problem in energy- and resource-constrained ad hoc networks. The heuristic organizes the network in clusters aiming to minimize a given cost function. The function used measures the total communication cost between all nodes within the cluster, keeping a minimum amount of resources per cluster. The clusterhead selection of the proposed heuristic is based on the division of labor encountered in social insects. The idea is that each node has probabilistic tendencies to assume a determined role in the network. For example, nodes with good connectivity and high energy level are good candidates for being clusterheads. The probability of assuming a determined role is based on a node's fitness for the specific role and the actual necessity (reflected by stimulus) of the role in the current network context. After becoming clusterhead, a node starts recruiting members in order to reach a minimum amount of resources that have to be available in the cluster. The procedure is based on a membership fitness function that evaluates the suitability of a node for the cluster. The realized simulations demonstrate that the proposed heuristic performance was about in average 25% inferior to the global optimum.