Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs

Authors Jie Wang, Dingding Chen, Ziyu Chen, Xiangshuang Liu, Junsong Gao

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Jie Wang
  • College of Computer Science, Chongqing University, China
Dingding Chen
  • College of Computer Science, Chongqing University, China
Ziyu Chen
  • College of Computer Science, Chongqing University, China
Xiangshuang Liu
  • College of Computer Science, Chongqing University, China
Junsong Gao
  • College of Computer Science, Chongqing University, China

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Jie Wang, Dingding Chen, Ziyu Chen, Xiangshuang Liu, and Junsong Gao. Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 39:1-39:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


Tree-based backtracking search is an important technique to solve Distributed Constraint optimization Problems (DCOPs), where agents cooperatively exhaust the search space by branching on each variable to divide subproblems and reporting the results to their parent after solving each subproblem. Therefore, effectively reusing the historical search results can avoid unnecessary resolutions and substantially reduce the overall overhead. However, the existing caching schemes for asynchronous algorithms cannot be applied directly to synchronous ones, in the sense that child agent reports the lower and upper bound rather than the precise cost of exploration. In addition, the existing caching scheme for synchronous algorithms has the shortcomings of incompleteness and low cache utilization. Therefore, we propose a new caching scheme for tree-based synchronous backtracking search, named Retention Scheme (RS). It utilizes the upper bounds of subproblems which avoid the reuse of suboptimal solutions to ensure the completeness, and deploys a fine-grained cache information unit targeted at each child agent to improve the cache-hit rate. Furthermore, we introduce two new cache replacement schemes to further improve performance when the memory is limited. Finally, we theoretically prove the completeness of our method and empirically show its superiority.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Cooperation and coordination
  • DCOP
  • Cache
  • Any-space Algorithms
  • Complete Search Algorithms


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