Utility Maximized Two-level Game-Theoretic Approach for Bandwidth Allocation in Heterogeneous Radio Access Networks

Author(s):  
Qixun Zhang ◽  
Bin Fu ◽  
Zhiyong Feng ◽  
Wei Li
2016 ◽  
Vol 17 (12) ◽  
pp. 1253-1265 ◽  
Author(s):  
Jun-feng Xie ◽  
Ren-chao Xie ◽  
Tao Huang ◽  
Jiang Liu ◽  
F. Richard Yu ◽  
...  

2017 ◽  
Vol 19 (01) ◽  
pp. 1750001
Author(s):  
Ilya Nikolaevskiy ◽  
Andrey Lukyanenko ◽  
Andrei Gurtov

The Nash Bargaining Solution (NBS) has been broadly suggested as an effective solution for the problem of fair allocation of multiple resources, namely bandwidth allocation in datacenters. In spite of being thoroughly studied, and provably strategy-proof for most scenarios, NBS-based allocation methods lack research on the strategic behavior of tenants in the case of proportionality of resource demands, which is common in datacenter workloads. We found that misbehavior is beneficial: by lying about bandwidth demands tenants can improve their allocations. We show that a sequence of selfish improvements leads to trivial demand vectors for all tenants. It essentially removes sharing incentives which are very important for datacenter networks. In this paper, we analytically prove that tenants can misbehave in 2- and 3- tenants cases. We show that misbehavior is possible in one recently proposed NBS-based allocation system if proportionality of demands is taken into account. Monte Carlo simulations were done for 2–15 tenants to show a misbehavior possibility and its impact on aggregated bandwidth. We propose to use another game-theoretic approach, namely Dominant Resource Fairness (DRF) to allocate bandwidth in the case of proportional demands. We show that this method performs significantly better than NBS after misbehavior.


Sign in / Sign up

Export Citation Format

Share Document