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MapReduce based location selection algorithm for utility maximization with capacity constraints

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Abstract

Given a set of facility objects and a set of client objects, where each client is served by her nearest facility and each facility is constrained by a service capacity, we study how to find all the locations on which if a new facility with a given capacity is established, the number of served clients is maximized (in other words, the utility of the facilities is maximized). This problem is intrinsically difficult. An existing algorithm with an exponential complexity is not scalable and cannot handle this problem on large data sets. Therefore, we propose to solve the problem through parallel computing, in particular using MapReduce. We propose an arc-based method to divide the search space into disjoint partitions. For load balancing, we propose a dynamic strategy to assign partitions to reducers so that the estimated load difference is within a threshold. We conduct extensive experiments using both real and synthetic data sets of large sizes. The results demonstrate the efficiency and scalability of the algorithm.

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Acknowledgments

This work is supported by the Australian Research Council (ARC) Discovery Project DP130104587. Dr. Rui Zhang is supported by the ARC Future Fellowships Project FT120100832. Dr. Yueguo Chen is partially supported by the National Science Foundation of China under Grant No. 61003085. Dr. Xiaoyong Du is partially supported by the National Science Foundation of China under Grant No. 61170010.

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Authors and Affiliations

  1. Department of Computing and Information Systems, University of Melbourne, Melbourne, Australia

    Yu Sun, Jianzhong Qi & Rui Zhang

  2. Key Laboratory of Data Engineering and Knowledge Engineering, Renmin University of China, Beijing, China

    Yueguo Chen & Xiaoyong Du

Authors
  1. Yu Sun
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  2. Jianzhong Qi
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  3. Rui Zhang
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  4. Yueguo Chen
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  5. Xiaoyong Du
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Correspondence to Yu Sun.

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Sun, Y., Qi, J., Zhang, R. et al. MapReduce based location selection algorithm for utility maximization with capacity constraints. Computing 97, 403–423 (2015). https://doi.org/10.1007/s00607-013-0382-5

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