A Survey of Game-Theoretic Approach for Resource Management in Cloud Computing

Table 5

A comparative analysis of game-theoretic models for resource provisioning in cloud architecture.

Author(s)	Techniques	Usage	Comments
Zou et al. [56]	Inter-/intraslice bandwidth optimization strategy	This is a challenge to allocate resources efficiently due to heterogeneous QoS requirements of diverse services as well as competition among different network slices	Inter-/intraslice bandwidth optimization strategy.
Pham-Nguyen and Tran-Minh [57]	Multiobjective optimization problem/strategy that is to combine three considered components (application’s response time, network congestion, and server usage) into one objective function	The service deployment is a multiobjective optimization problem	Fog computing is a model in which the system tries to push data processing from cloud servers to “near” IoT devices in order to reduce latency time.
Wu et al. [50]	The resource provisioning strategy that is based on dynamic programming		Due to the clouds providing the pay-as-you-go pricing scheme, executing a workflow in clouds should pay for the provisioned resources. Thus, cost-effective resource provisioning for workflow in clouds is still a critical challenge.
Mashayekhy et al. [58]	Polynomial-time approximation scheme (PTAS)	Address the problem of autonomic VM provisioning and allocation for the auction-based model	Address cloud providers’ ability to allocate and provide these resources such that their profit is maximized and the resources are utilized efficiently.
Nejad et al. [59]	Integer programming	Enable the cloud providers to effectively utilize their available resources and obtain higher profits	Address the problem of VM provisioning and allocation in clouds in the presence of multiple types of resources.