Energy-Aware Load Balancing and Application Scaling for the Cloud Eco System
Abstract
To introduce an energy-aware operating model used for load balancing and cloud application scaling. Energy-aware Load Balancing and Application Scaling for the Cloud Ecosystem The basic philosophy of our approach is to define an energy-optimal operating regime and to try to maximize the number of servers operating in this regime. Idle and lightly loaded servers are switched to one of the sleep states to save energy.
Energy-aware Load Balancing and Application Scaling for the Cloud Ecosystem The load balancing and scaling algorithms also use some of the most desirable features of server consolidation mechanisms. The results of measurements reported in the literature are difficult to relate to each other. For example, for the AutoScale system, the wake-up time of servers in sleep state and the number of servers in sleep state are reported; yet these figures would be different for another processor, system configuration, and application.
System Configuration
Platform : cloud computing
Conclusion
Low average server usage and its impact on the environment make it imperative to devise new energy-aware policies that identify optimal regimes for cloud servers while preventing SLA violations. The results show different numerical results in each benchmark for the individual applications. Similarly, the effects of an energy-aware algorithm depend on the configuration of the system and the application and can not be expressed by a single numerical value.
