On topology and time: efficient evaluation for temporal-clique subgraph queries

Overview

This research addresses temporal-clique subgraph pattern matching, a query processing problem requiring simultaneous evaluation of topological structure and temporal overlap constraints. The work targets applications across social networks, life sciences, smart cities, and telecommunications domains where subgraph patterns must satisfy both structural specificity and temporal window requirements. Existing subgraph matching techniques prove inefficient when processing combined temporal and structural constraints, motivating development of specialized query evaluation methods.

Methods and approach

The proposed approach systematically exploits both topological and temporal selectivities to optimize query processing performance. Key innovations include a specialized multi-way join operator designed to handle simultaneous structural and temporal constraints, an optimized query planner that determines efficient processing strategies, and an accurate cardinality estimator to predict intermediate result sizes. Additional optimization techniques further enhance processing efficiency. The methodology integrates these components across the complete query processing pipeline rather than treating temporal and structural aspects independently.

Key Findings

Experimental evaluation demonstrates substantial performance improvements over state-of-the-art baseline techniques across comprehensive test scenarios. The proposed method achieves these improvements while maintaining minimal additional storage overhead, indicating efficient resource utilization. The cardinality estimator demonstrates accuracy in predicting intermediate result magnitudes, supporting effective query planning decisions. Performance gains suggest the approach scales effectively relative to existing methods.

Implications

The research provides a practical framework for evaluating temporal-clique patterns in real-world applications where both structural and temporal constraints are fundamental to pattern semantics. The specialized multi-way join operator and cardinality estimation techniques represent transferable components for temporal graph query processing beyond the specific clique-matching problem. The minimal storage overhead indicates feasibility for deployment in resource-constrained environments.