The paper "pMapper: Power and Migration Cost-Aware Application Placement in Virtualized Systems" by Akshat Verma, Puneet Ahuja, and Anindya Neogi explores the design, implementation, and evaluation of a power-aware application placement controller for virtualized server clusters. The primary goal is to minimize power consumption while meeting performance requirements, addressing the limitations of traditional workload placement methods that focus solely on performance. The authors present multiple formulations of the problem, including cost-performance tradeoff, cost minimization with performance constraints, and performance benefit maximization with power constraints. They validate these formulations through experimental setups and model assumptions, demonstrating the feasibility of estimating power costs and migration costs. The paper introduces pMapper, a framework that leverages virtualization capabilities to dynamically place applications on physical servers. pMapper includes three main components: Performance Manager, Power Manager, and Migration Manager, each responsible for different aspects of resource management. The framework uses a central arbitrator to coordinate these components and make optimal placement decisions. The authors propose several algorithms for power-aware application placement, including min Power Parity (mPP), incremental FFD (iFFD), and min Power Placement with History (mPPH). These algorithms aim to minimize power consumption while considering migration costs. The experimental results show that pMapper's algorithms outperform static and load-balancing placement strategies, particularly in scenarios with high utilization and varying workloads. The paper also discusses the scalability and handling of heterogeneity in server platforms, showing that pMapper can effectively manage diverse power models and server types. Overall, the paper provides a comprehensive approach to power-aware application placement, offering practical solutions for optimizing energy efficiency in virtualized environments.The paper "pMapper: Power and Migration Cost-Aware Application Placement in Virtualized Systems" by Akshat Verma, Puneet Ahuja, and Anindya Neogi explores the design, implementation, and evaluation of a power-aware application placement controller for virtualized server clusters. The primary goal is to minimize power consumption while meeting performance requirements, addressing the limitations of traditional workload placement methods that focus solely on performance. The authors present multiple formulations of the problem, including cost-performance tradeoff, cost minimization with performance constraints, and performance benefit maximization with power constraints. They validate these formulations through experimental setups and model assumptions, demonstrating the feasibility of estimating power costs and migration costs. The paper introduces pMapper, a framework that leverages virtualization capabilities to dynamically place applications on physical servers. pMapper includes three main components: Performance Manager, Power Manager, and Migration Manager, each responsible for different aspects of resource management. The framework uses a central arbitrator to coordinate these components and make optimal placement decisions. The authors propose several algorithms for power-aware application placement, including min Power Parity (mPP), incremental FFD (iFFD), and min Power Placement with History (mPPH). These algorithms aim to minimize power consumption while considering migration costs. The experimental results show that pMapper's algorithms outperform static and load-balancing placement strategies, particularly in scenarios with high utilization and varying workloads. The paper also discusses the scalability and handling of heterogeneity in server platforms, showing that pMapper can effectively manage diverse power models and server types. Overall, the paper provides a comprehensive approach to power-aware application placement, offering practical solutions for optimizing energy efficiency in virtualized environments.