scholarly journals Multi-Start Local Search Algorithm for the Minimum Connected Dominating Set Problems

Mathematics ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 1173 ◽  
Author(s):  
Ruizhi Li ◽  
Shuli Hu ◽  
Huan Liu ◽  
Ruiting Li ◽  
Dantong Ouyang ◽  
...  

The minimum connected dominating set (MCDS) problem is a very significant NP-hard combinatorial optimization problem, and it has been used in many fields such as wireless sensor networks and ad hoc networks. In this paper, we propose a novel multi-start local search algorithm (MSLS) to tackle the minimum connected dominating set problem. Firstly, we present the fitness mechanism to design the vertex score mechanism so that our algorithm can jump out of the local optimum. Secondly, we use the configuration checking (CC) mechanism to avoid the cycling problem. Then, we propose the vertex flipping mechanism to change the vertex state by combing the CC mechanism with the vertex score mechanism. Finally, we propose a multi-start local search framework based on these mechanisms. We compare the algorithm MSLS with other compared algorithms on extensive instances. The results of experiment show that MSLS is superior to other algorithms in solution quality and time efficiency on most instances.

Author(s):  
Bohan Li ◽  
Xindi Zhang ◽  
Shaowei Cai ◽  
Jinkun Lin ◽  
Yiyuan Wang ◽  
...  

The minimum connected dominating set (MCDS) problem is an important extension of the minimum dominating set problem, with wide applications, especially in wireless networks. Despite its practical importance, there are few works on solving MCDS for massive graphs, mainly due to the complexity of maintaining connectivity. In this paper, we propose two novel ideas, and develop a new local search algorithm for MCDS called NuCDS. First, a hybrid dynamic connectivity maintenance method is designed to switch alternately between a novel fast connectivity maintenance method based on spanning tree and its previous counterpart. Second, we define a new vertex property called \emph{safety} to make the algorithm more considerate when selecting vertices. Experiments show that NuCDS significantly outperforms the state-of-the-art MCDS algorithms on both massive graphs and classic benchmarks.


2010 ◽  
Vol 21 (03) ◽  
pp. 459-476 ◽  
Author(s):  
SAYAKA KAMEI ◽  
HIROTSUGU KAKUGAWA

Self-stabilization is a theoretical framework of non-masking fault-tolerant distributed algorithms. A self-stabilizing system tolerates any kind and any finite number of transient faults, such as message loss, memory corruption, and topology change. Because such transient faults occur so frequently in mobile ad hoc networks, distributed algorithms on them should tolerate such events. In this paper, we propose a self-stabilizing distributed approximation algorithm for the minimum connected dominating set, which can be used, for example, as a virtual backbone or routing in mobile ad hoc networks. The size of the solution by our algorithm is at most 7.6|Dopt|+1.4, where Dopt is the minimum connected dominating set. The time complexity is O(k) rounds, where k is the depth of input BFS tree.


2021 ◽  
Vol 71 ◽  
pp. 89-119
Author(s):  
Xindi Zhang ◽  
Bohan Li ◽  
Shaowei Cai ◽  
Yiyuan Wang

The minimum connected dominating set (MCDS) problem is an important extension of the minimum dominating set problem, with wide applications, especially in wireless networks. Most previous works focused on solving MCDS problem in graphs with relatively small size, mainly due to the complexity of maintaining connectivity. This paper explores techniques for solving MCDS problem in massive real-world graphs with wide practical importance. Firstly, we propose a local greedy construction method with reasoning rule called 1hopReason. Secondly and most importantly, a hybrid dynamic connectivity maintenance method (HDC+) is designed to switch alternately between a novel fast connectivity maintenance method based on spanning tree and its previous counterpart. Thirdly, we adopt a two-level vertex selection heuristic with a newly proposed scoring function called chronosafety to make the algorithm more considerate when selecting vertices. We design a new local search algorithm called FastCDS based on the three ideas. Experiments show that FastCDS significantly outperforms five state-of-the-art MCDS algorithms on both massive graphs and classic benchmarks.


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