Stackelberg Game-Based Models In Energy-Aware Cloud Scheduling

Abstract

Energy-awareness remians the important problem in today's cloud computing (CC). Optimization of the energy consumed in cloud data centers and computing servers is usually related to the scheduling problems. It is very difficult to define an optimal scheduling policy without negoative influence into the system performance and task completion time. In this work, we define a general cloud scheduling model based on a Stackelberg game with the workload scheduler and energy-efficiency agent as the main players. In this game, the aim of the scheduler is the minimization of the makespan of the workload, which is achieved by the employ of a genetic scheduling algorithm that maps the workload tasks into the computational nodes. The energy-efficiency agent selects the energy-optimization techniques based on the idea of switchin-off of the idle machines, in response to the scheduler decisions. The efficiency of the proposed model has been tested using a SCORE cloud simmulator. Obtained results show that the proposed model performs better than static energy-optimization strategies, achieving a fair balance between low energy consumption and short queue times and makespan.

DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres

“…Previous work demonstrates that the Batch workload can achieve good performance levels in terms of scheduling even if we rely on the expected task-processing time according to the computational resources on which it is deployed (see [21][22][23]). Due to the difficulty of performing the computation needed to solve Eq.…”

Game theoretical approach for load balancing using SGMLB model in cloud environment

“…There are different game-theoretical approaches available like cooperative and non-cooperative games [21,22], symmetric and non-symmetric, simultaneous and sequential move games, constant sum, zerosum and non-zero-sum games. Stackelberg model is one of the strategic game models in which the leader firm makes its first move, and then the follower firm makes its next move sequentially [23]. This model is framed based on the game theory, where a group of players follows a leader to compete for a quantity or resource.…”

“…It is taken care that the interference of the macro base station does not exceed an interference constraint, and the existence of Nash Equilibrium was also examined using backward induction. Tran et al [29], used a two-stage Stackelberg game and modeled in the geo-distributed data center to distribute their substantial energy demands based on the real-time pricing scheme of demand response programs [30,23].…”

Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

“…One of the most popular approaches to increase efficiency is to switch off idle servers [75,78], which is usually tested in dedicated simulation tools [74]. Several models, including games theory models [72,73], are used to balance opposite requirements in data centers, such as performance and energy consumption. Even models utilized for economic environments, such as Data Envelopment Analysis, are employed to analyze the efficiency in various realistic large-scale data centers and propose corrections to improve data-center efficiency [76].…”