01839nas a2200229   4500008004100000245008100041210006900122260000900191300001400200490000600214520114900220653000701369653001901376653001701395653000801412653002401420653000801444100001201452700001701464700001101481856011701492       2009                        eng d00aGA and PSO-based resource scheduling for orchestrated, distributed computing0 aGA and PSObased resource scheduling for orchestrated distributed  c2009  a343 - 3510 v73 aA new distributed computing architecture, Dynamic Virtual Private Network (DVPN), is introduced. The DVM (Dynamic VPN Manager) works as the Autonomous System (AS) administrator in the DVPN system to perform resource scheduling and liaise with the underlying connection management. The approach combines on-demand reservation of both the communications infrastructure and various higherlevel processing facilities. This enables support of orchestrated computing where a complex job can be considered to be a VPN community. This job may be decomposed into tasks to be located at various distributed processing sites. Data can flow between them rather like a production line, in order to deliver the finished "product" to chosen end hosts. Two variants of a resource-scheduling algorithm are proposed for job scheduling in the DVPN system. Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO) mechanisms are considered for use within the optimization process. Simulation results show that both approaches are feasible. The authors then compare the performance of GA against PSO in this dynamic VPN environment to compare their suitability.10aGA10aGrid computing10aInter-domain10aPSO10aResource scheduling10aVPN1 aGao, Y.1 aPhillips, C.1 aHe, L.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960659450&partnerID=40&md5=d9ea15f86f2d90b8c89711571dc61514