Continuous Monitoring of Maximum Clique Over Dynamic Graphs

The maximum clique problem ( MCP ) has various applications to reveal the structure and function of graphs. Graphs are constantly updated in the real life. However, no algorithm is specifically designed for dynamic graph. Although MCP in dynamic graphs can be solved by simply invoking a state-of-the-art static approach, such as PMC , when the graph is updated, such an approach of simply re-calculating from scratch is inefficient. The key issue with MCP algorithm is to find a large clique, namely a seed , as fast as possible. Thus, search space can be pruned based on the seed. Size of the seed greedily found by PMC cannot be guaranteed, as it fluctuates considerably. Moreover, the time required to find a seed under PMC is up to O(| E| \cdot \Delta (G)) O(|E|·Δ(G)) , where \Delta (G) Δ(G) is the highest degree in G . In this article, we intend to find a sizable seed by updating the previous maximum clique with the incident vertices of the inserted/deleted edge. Size of the seed now is guaranteed to be no less than \omega (G^{\prime})\; - \;1 ω(G')-1 , where \omega (G^{\prime}) ω(G') is the size of the maximum clique on the updated graph. Moreover, the seed can be found in a time complexity of O(\Delta (G)^{2})