An Asynchronous Gradient Descent Based Method for Distributed Resource Allocation with Bounded Variables

2021 ◽  
pp. 1-1
Author(s):  
Yifan Wang ◽  
Qianchuan Zhao ◽  
Xuetao Wang
Keyword(s):  
Resource Allocation ◽  
Gradient Descent ◽  
Distributed Resource Allocation ◽  
Bounded Variables

Quantized Gradient-Descent Algorithm for Distributed Resource Allocation

2019 ◽  
Vol 07 (02) ◽  
pp. 119-136
Author(s):  
Hongbing Zhou ◽  
Weiyong Yu ◽  
Peng Yi ◽  
Yiguang Hong
Keyword(s):  
Resource Allocation ◽  
Communication Networks ◽  
Gradient Descent ◽  
Allocation Problem ◽  
Resource Allocation Problem ◽  
Distributed Resource Allocation ◽  
Descent Algorithm ◽  
Gradient Descent Algorithm ◽  
Optimal Value ◽  
Fixed Topology

In this paper, we consider a distributed resource allocation problem with communication limitation. We propose a gradient-descent algorithm to solve the distributed resource allocation problem with quantization mechanism due to the communication limitations or in order to reduce the communication cost in the network. With carefully selected parameters, the convergence and correctness of the quantized algorithm can be obtained for fixed communication topologies and moreover, extended to switching jointly connected topologies. The exact optimal value can be obtained, which is different from some existing works, whose convergence accuracies were limited by the quantization bandwidth. In addition, the data rate of the proposed algorithm is also analyzed for both fixed and switching communication networks. Particularly, in the fixed topology case, we obtain that 1 bit is sufficient to solve the distributed problem with the proposed algorithm.

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