Online Inter-Datacenter Service Migrations

Online Inter-Datacenter Service Migrations

Online Inter-Datacenter Service Migrations


Service migration between datacenters can reduce overhead network within a cloud infrastructure, thereby also improving customer service quality. Online Inter-Datacenter Service Migrations Most of the algorithms in the literature assume that the pattern of client access remains stable for a sufficiently long period of time to amortize such migrations. If such an assumption does not hold, however, these algorithms can make arbitrarily poor migration decisions that can substantially degrade system performance.
In this Online Inter-Datacenter Service Migrations paper, for an unknown and dynamically changing client access pattern, we approach the issue of performing service migrations. We propose an online algorithm that minimizes the inter-datacenter network, taking into account the network load of migrating a service between two datacenters, as well as the fact that the pattern of the client request may change “quickly” before such migration is amortized. 

System Configuration

H/W System Configuration
Speed                   : 1.1 GHz
RAM                      : 256 MB(min)
Hard Disk              : 20 GB
Floppy Drive          : 1.44 MB
Key Board             : Standard Windows Keyboard
Mouse                  : Two or Three Button Mouse
Monitor                : SVGA
S/W System Configuration
Platform                     :  cloud computing

Operating system       : Windows Xp,7,
Server                       : WAMP/Apache
Working on                : Browser Like Firefox, IE


In this work, we introduced the problem of deciding at what point in time a service must be migrated to reduce overhead network. As a solution to the above problem, we proposed the network overhead migration algorithm (called NOM). We gave an analytical proof that NOM is 3.8 competitive when the underlying network is structured as a tree. In the current literature (called MIG) we conducted experimental evaluation to compare NOM and the best known online algorithm to a static offline optimal algorithm (SOPT).