Title
LBMIC: communication-aware load balancing in distributed ASMs with evolving social networks
Abstract
Multi-agent-based simulation for artificial stock market (ASM) is an important method in behavioural finance. The social network in ASM will influence the coordination and decision making of the intelligent agents. To improve the performance of an ASM with evolving social networks in a distributed computing environment, the computational load balancing and inter-nodes communication should be considered jointly. This paper proposes a scheduling algorithm called LBMIC to partition the agents onto different computing nodes while keeping the degree of load imbalance lower than a given threshold with minimized inter-nodes communication between agents. LBMIC models the scheduling into a graph partitioning problem and uses the multi-level graph partitioning algorithm to achieve an efficient scheduling. When the network evolves, LBMIC refines the partitioning by migrating parts of the agents. The experiments indicate that LBMIC can efficiently improve the performance of communication-intensive ASMs by both initial partitioning and refining partitioning.
Year
DOI
Venue
2016
10.1057/jos.2015.12
J. Simulation
Keywords
Field
DocType
discrete event simulation,simulation
Intelligent agent,Social network,Distributed Computing Environment,Computer science,Scheduling (computing),Load balancing (computing),Simulation,Multi-agent system,Graph partition,Discrete event simulation,Distributed computing
Journal
Volume
Issue
ISSN
10
4
1747-7786
Citations 
PageRank 
References 
0
0.34
36
Authors
7
Name
Order
Citations
PageRank
cheng yu100.34
Xiang Chen213930.34
chengxiang wang300.34
yanhui li400.34
julu sun500.34
Hongyi Wu684876.90
xiaoying zhang700.34