Paper Info
Title
Non-Concave Network Utility Maximization In Connectionless Networks: A Fully Distributed Traffic Allocation Algorithm
Abstract
This paper considers the optimization-based traffic allocation problem among multiple end points in connectionless networks. The network utility function is modeled as a non-concave function, since it is the best description of the quality of service perceived by users with inelastic applications, such as video and audio streaming. However, the resulting non-convex optimization problem, is challenging and requires new analysis and solution techniques. To overcome these challenges, we first propose a hierarchy of problems whose optimal value converges to the optimal value of the non-convex optimization problem as the number of moments tends to infinity. From this hierarchy of problems, we obtain a convex relaxation of the original non-convex optimization problem by considering truncated moment sequences. For solving the convex relaxation, we propose a fully distributed iterative algorithm, which enables each node to adjust its date allocation/rate adaption among any given set of next hops solely based on information from the neighboring nodes. Moreover, the proposed traffic allocation algorithm converges to the optimal value of the convex relaxation at a O(1/K) rate, where K is the iteration counter, with a bounded optimality. At the end of this paper, we perform numerical simulations to demonstrate the soundness of the developed algorithm.
Year
DOI
Venue
2017
10.23919/ACC.2017.7963565
2017 AMERICAN CONTROL CONFERENCE (ACC)
Field
DocType
ISSN
Mathematical optimization,Iterative method,Computer science,Connectionless communication,Quality of service,Network utility,Soundness,Hierarchy,Optimization problem,Bounded function
Conference
0743-1619
Citations 
PageRank 
References 
0
0.34
8
Authors
6
Name
Order
Citations
PageRank
Jingyao Wang1457.10
Mahmoud Ashour220.70
Constantino M. Lagoa316425.38
N. S. Aybat48910.49
Hao Che5314.70
Zhisheng Duan62104114.46