Simulated versus reduced noise quantum annealing in maximum independent set solution to wireless network scheduling

2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Chi Wang ◽  
Edmond Jonckheere
Keyword(s):  
Wireless Network ◽  
Independent Set ◽  
Maximum Independent Set ◽  
Quantum Annealing ◽  
Network Scheduling

scholarly journals WiFi-Based Virtual Access Network Scheduling for Downlink Traffic Dominated Smart Spaces

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Pin Lv ◽  
Siyu Pan ◽  
Jia Xu
Keyword(s):  
Scheduling Algorithm ◽  
Access Network ◽  
Independent Set ◽  
Scheduling Algorithms ◽  
Conflict Graph ◽  
Maximum Independent Set ◽  
Smart Spaces ◽  
Network Scheduling ◽  
Wifi Networks ◽  
Network Utilization

WiFi networks are widely and densely deployed as infrastructure in smart spaces. However, differentiated services with guaranteed access bandwidths are not supported in traditional WiFi networks. In this paper, wireless virtual access networks are established to provide guaranteed downlink bandwidths for primary users. For each primary user with a demanded access bandwidth, a group of APs are coordinated to serve it. In order to maximize network utilization, two wireless virtual access network scheduling algorithms are designed. One scheduling algorithm is designed based on the maximum independent set in the conflict graph, which has an exponential computation complexity. The other scheduling solution is based on a greedy strategy with linear complexity. Simulation results prove that both scheduling algorithms improve network utilization effectively, and the greedy algorithm is more suitable for practical use.

scholarly journals Gumbel-softmax-based optimization: a simple general framework for optimization problems on graphs

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yaoxin Li ◽  
Jing Liu ◽  
Guozheng Lin ◽  
Yueyuan Hou ◽  
Muyun Mou ◽  
...  
Keyword(s):  
Objective Function ◽  
Statistical Physics ◽  
Automatic Differentiation ◽  
Optimization Problems ◽  
Vertex Cover ◽  
Independent Set ◽  
Computational Social Science ◽  
Maximization Problem ◽  
Maximum Independent Set ◽  
Gradient Descent Algorithm

AbstractIn computer science, there exist a large number of optimization problems defined on graphs, that is to find a best node state configuration or a network structure, such that the designed objective function is optimized under some constraints. However, these problems are notorious for their hardness to solve, because most of them are NP-hard or NP-complete. Although traditional general methods such as simulated annealing (SA), genetic algorithms (GA), and so forth have been devised to these hard problems, their accuracy and time consumption are not satisfying in practice. In this work, we proposed a simple, fast, and general algorithm framework based on advanced automatic differentiation technique empowered by deep learning frameworks. By introducing Gumbel-softmax technique, we can optimize the objective function directly by gradient descent algorithm regardless of the discrete nature of variables. We also introduce evolution strategy to parallel version of our algorithm. We test our algorithm on four representative optimization problems on graph including modularity optimization from network science, Sherrington–Kirkpatrick (SK) model from statistical physics, maximum independent set (MIS) and minimum vertex cover (MVC) problem from combinatorial optimization on graph, and Influence Maximization problem from computational social science. High-quality solutions can be obtained with much less time-consuming compared to the traditional approaches.

Finding a Maximum Independent Set

1977 ◽  
Vol 6 (3) ◽  
pp. 537-546 ◽  
Author(s):  
Robert Endre Tarjan ◽  
Anthony E. Trojanowski
Keyword(s):  
Independent Set ◽  
Maximum Independent Set

Advice Complexity of Maximum Independent set in Sparse and Bipartite Graphs

2014 ◽  
Vol 56 (1) ◽  
pp. 197-219 ◽  
Author(s):  
Stefan Dobrev ◽  
Rastislav Královič ◽  
Richard Královič
Keyword(s):  
Independent Set ◽  
Bipartite Graphs ◽  
Maximum Independent Set ◽  
Advice Complexity
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