An Enhanced Integrated High Availability Cluster Model Based on Active-Active and Active-Passive Cluster

High availability (HA) refers to systems that are likely to operate continuously without failure for a long time. HA can be achieved by creating a cluster of computers that act like a single system and provide continuous uptime. Several researchers have used different approaches for high availability cluster, basically active-active and active-passive cluster which leads to issues like client request congestion or overload and redundant standby systems respectively. This research creates enhancement in high availability using integrated high availability cluster (iHAC). iHAC addresses overload and redundancy by introducing efficient throughput and low latency. iHAC uses three scenarios, active active-passive, active passive-active, and active passive-passive. Model methodology is used to create an abstraction of the system where experiment is conducted to ascertain results which may have been difficult to get in real systems. The simulation tool used was Riverbed Modeler (Opnet Modeler). Results indicate that in terms of delay, iHAC recorded 0.00008 to 0.00015 whiles active-active and active-passive recorded 0.00018 to 0.00025. Http response is generated in 1 to 2 seconds on all scenarios of iHAC whiles active-active and active-passive response at 3 to 7 seconds. in effect the iHAC model gave better throughput and latency when compared against activea-ctive and active-passive cluster model.