Solving task scheduling problem For distributed sensor network With discrete particle swarm optimization - Details

author：

Guo, Wenzhong (Guo, Wenzhong.) ^[1] (Scholars：郭文忠) | Huang, Qiaoyun (Huang, Qiaoyun.) ^[2] | Chen, Guolong (Chen, Guolong.) ^[3] (Scholars：陈国龙) | Yu, Lun (Yu, Lun.) ^[4] (Scholars：余轮)

Indexed by：

EI Scopus

Abstract：

From　the　computation　point　of　view,　task　scheduling　for　distributed　sensor　network　is　an　NPhard　combinatorial　optimization　problem.　The　Particle　Swarm　Optimization　(PSO)　has　been　proved　to　be　a　good　optimization　algorithm　with　outstanding　global　performance.　However,　PSO　cannot　be　directly　used　in　the　combinatorial　optimization　problem　mentioned　above　due　to　its　continuity.　In　this　paper,　a　heuristic　discrete　PSO　(HDPSO)　with　a　well-designed　particle　position　code　is　proposed,　in　which　effective　fitness　function　based　on　approximate　optimal　waiting　approach　is　adopted.　Experiments　show　that　the　performance　of　the　proposed　algorithm　is　better　than　genetic　algorithm.　©　2009　IEEE.

Keyword：

Combinatorial optimization Distributed computer systems Genetic algorithms Multitasking Optimal systems Particle swarm optimization (PSO) Scheduling algorithms Sensor networks

Community：

[ 1 ] [Guo, Wenzhong]College of Physics and Information Engineering, Fuzhou University, Fuzhou 350002, China
[ 2 ] [Guo, Wenzhong]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
[ 3 ] [Huang, Qiaoyun]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
[ 4 ] [Chen, Guolong]College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350002, China
[ 5 ] [Yu, Lun]College of Physics and Information Engineering, Fuzhou University, Fuzhou 350002, China