This paper attempts a comprehensive study of deadlock detection in distributed database systems. First, the two predominant deadlock models in these systems and the four different distributed deadlock detection approaches are discussed. Afterwards, a new deadlock detection algorithm is presented. The algorithm is based on dynamically creating deadlock detection agents (DDAs), each being responsible for detecting deadlocks in one connected component of the global wait-for-graph (WFG). The DDA scheme is a “self-tuning” system: after an initial warm-up phase, dedicated DDAs will be formed for “centers of locality”, i.e., parts of the system where many conflicts occur. A dynamic shift in locality of the distributed system will be responded to by automatically creating new DDAs while the obsolete ones terminate. In this paper, we also compare the most competitive representative of each class of algorithms suitable for distributed database systems based on a simulation model, and point out their relative strengths and weaknesses. The extensive experiments we carried out indicate that our newly proposed deadlock detection algorithm outperforms the other algorithms in the vast majority of configurations and workloads and, in contrast to all other algorithms, is very robust with respect to differing load and access profiles.
