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The trend towards many-core systems comes with various issues, among them their highly dynamic and non-predictable workloads. Hence, new paradigms for managing resources of many-core systems are of paramount importance. The problem of resource management, e.g. mapping applications to processor cores, is NP-hard though, requiring heuristics especially when performed online. In this paper, we therefore present a novel resource-management scheme that supports so-called malleable applications. These applications can adopt their level of parallelism to the assigned resources. By design, our (decentralized) scheme is scalable and it copes with the computational complexity by focusing on local decision-making. Our simulations show that the quality of the mapping decisions of our approach is able to stay near the mapping quality of state-of-the-art (i.e. centralized) online schemes for malleable applications but at a reduced overall communication overhead (only about 12,75% on a 1024 core system with a total workload of 32 multi-threaded applications). In addition, our approach is scalable as opposed to a centralized scheme and therefore it is practically useful for employment in large many-core systems as our extensive studies and experiments show.