.png){kind=icon}
返回
Optimization of Workload Balancing and Power Allocation for Wireless Distributed Computing
.png){kind=icon}
PRE
AI
DOI：10.1109/TWC.2022.3160493.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Distributed computing systems, such as Hadoop, have been widely studied and used for executing and analyzing large data. In this paper, we investigate an emerging resource allocation problem for wireless distributed computing systems consisting of multifunctional nodes in charge of both numerical computation and wireless communication with master nodes. We focus on a computation power consumption model based on CMOS devices and a communication power consumption model involving multiple antenna transceivers against mutual interference. We present a joint optimization problem for workload scheduling and power allocation for achieving maximum computational speed under total power constraint. We simplify the joint optimization into two sub-problems. For workload scheduling as an integer programming sub-problem, we relax the integer constraint and establish the equivalence between relaxed and original problems. For the power allocation sub-problem, we maximize a difference of convex functions by utilizing the concave-convex procedure. We prove our proposed algorithm to converge to a stationary point of the original program. Simulation results confirm the efficiency and near-optimal performance of our proposed algorithms.
Keyword:
Resource management
Wireless communication
Task analysis
Power demand
Processor scheduling
Optimization
Distributed computing
Difference of convex functions
power allocation
wireless distributed computing
workload scheduling
Hadoop
期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
机构
引用论文
Suppressed Mobility of Negative Charges in Polymer Electrolytes with an Ether‐Functionalized Anion
OAAI
.png){kind=icon}
OAAI分享收藏分享收藏
查看更多内容