In-Network Distributed Algorithm for Energy Optimal Routing Based on Dual Decomposition of Linear Programming

2012 ◽  
Vol 60 (6) ◽  
pp. 1634-1645 ◽  
Author(s):  
J. Trdlicka ◽  
Z. Hanzalek
Keyword(s):  
Linear Programming ◽  
Distributed Algorithm ◽  
Optimal Routing ◽  
Dual Decomposition

scholarly journals Distributed Algorithm for Real-Time Energy Optimal Routing Based on Dual Decomposition of Linear Programming

2011 ◽  
Vol 8 (1) ◽  
pp. 346163
Author(s):  
Jiří Trdlička ◽  
Zdeněk Hanzálek
Keyword(s):  
Linear Programming ◽  
Real Time ◽  
Network Flow ◽  
Distributed Algorithm ◽  
Cost Functions ◽  
Optimal Routing ◽  
Communication Delays ◽  
Dual Decomposition ◽  
Routing Problem ◽  
Linear Cost

This work proposes a novel in-network distributed algorithm for real-time energy optimal routing in ad hoc and sensor networks for systems with linear cost functions and constant communication delays. The routing problem is described as a minimum-cost multicommodity network flow problem by linear programming and modified by network replication to a real-time aware form. Based on the convex programming theory we use dual decomposition to derive the distributed algorithm. Thanks to the exact mathematical derivation, the algorithm computes the energy optimal real-time routing. It uses only peer-to-peer communication between neighboring nodes and does not need any central node or knowledge about the whole network structure. Each node knows only the produced and collected data flow and the costs of its outgoing communication links. According to our knowledge, this work is the first, which solves the real-time routing problem with linear cost functions and constant communication delays, using the dual decomposition.

scholarly journals A Primal-Dual Decomposition-Based Interior Point Approach to Two-Stage Stochastic Linear Programming

2002 ◽  
Vol 50 (5) ◽  
pp. 904-915 ◽  
Author(s):  
Arjan Berkelaar ◽  
Cees Dert ◽  
Bart Oldenkamp ◽  
Shuzhong Zhang
Keyword(s):  
Linear Programming ◽  
Interior Point ◽  
Dual Decomposition ◽  
Stochastic Linear Programming ◽  
Two Stage ◽  
Primal Dual

A Distributed Algorithm for Data Collection in Low-Duty-Cycled WSNs

2014 ◽  
Vol 668-669 ◽  
pp. 1355-1358
Author(s):  
Feng Liu ◽  
Yu Fei Wang ◽  
Mu Lin
Keyword(s):  
Data Collection ◽  
Distributed Algorithm ◽  
Routing Algorithms ◽  
Optimal Routing ◽  
Shortest Path Algorithm ◽  
End To End Delay ◽  
Network Utility ◽  
Control Message ◽  
End To End ◽  
Better Than

In order to prolong the lifetime of WSNs, low-duty-cycled scheduling is a widely used strategy. However, there exists high latency with traditional routing algorithms. In this paper, we model the data collection scheme of WSNs to be a delay optimization problem and propose a distributed algorithm based on Network Utility Maximization. The proposed algorithm can distributed find an optimal routing to achieve minimal average end-to-end delay. The simulation results show that our algorithm performs better than the traditional shortest path algorithm on end-to-end delay with less control message.

Network Utility Maximization with Random Link Failures

2014 ◽  
Vol 513-517 ◽  
pp. 1807-1810
Author(s):  
Sheng Bin Liao ◽  
Cui Tao Zhu
Keyword(s):  
Distributed Algorithm ◽  
Utility Maximization ◽  
Numerical Results ◽  
Network Utility Maximization ◽  
Dual Decomposition ◽  
Link Failures ◽  
Network Utility

Network utility maximization model with random link failures was presented in this paper. We provide a distributed algorithm based on the dual decomposition and investigate the impacts of link failures on the network utility. Numerical results validated the convergence of the proposed algorithm and our conclusions.

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