Game theoretic approaches for job scheduling in cloud computing: A survey

Ananth, Alaka; Sekaran, K. Chandra

doi:10.1109/iccct.2014.7001473

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…Unlike traditional grid schedulers, CRB solves a wide range of application scheduling issues, including the lack of adequate computing nodes in a cluster and the lack of a software execution environment in any grid resources. In this chain, the authors also presented a game-theoretic paradigm for real-time cloud job scheduling (Ananth and Sekaran, 2014). In this approach, the job takes on a player's role, while the VM takes on the part of a strategy.…”

Section: Related Workmentioning

confidence: 99%

A load-balanced hybrid heuristic for allocation of batch of tasks in cloud computing environment

Shiekh

Shahid

Sambare

et al. 2022

IJPCC

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Purpose Cloud computing gives several on-demand infrastructural services by dynamically pooling heterogeneous resources to cater to users’ applications. The task scheduling needs to be done optimally to achieve proficient results in a cloud computing environment. While satisfying the user’s requirements in a cloud environment, scheduling has been proven an NP-hard problem. Therefore, it leaves scope to develop new allocation models for the problem. The aim of the study is to develop load balancing method to maximize the resource utilization in cloud environment. Design/methodology/approach In this paper, the parallelized task allocation with load balancing (PTAL) hybrid heuristic is proposed for jobs coming from various users. These jobs are allocated on the resources one by one in a parallelized manner as they arrive in the cloud system. The novel algorithm works in three phases: parallelization, task allocation and task reallocation. The proposed model is designed for efficient task allocation, reallocation of resources and adequate load balancing to achieve better quality of service (QoS) results. Findings The acquired empirical results show that PTAL performs better than other scheduling strategies under various cases for different QoS parameters under study. Originality/value The outcome has been examined for the real data set to evaluate it with different state-of-the-art heuristics having comparable objective parameters.

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Section: Related Workmentioning

confidence: 99%

A load-balanced hybrid heuristic for allocation of batch of tasks in cloud computing environment

Shiekh

Shahid

Sambare

et al. 2022

IJPCC

View full text Add to dashboard Cite

show abstract

“…. , 1 3 ], means that user of the resource number 1 should declare the lowest possible computing capacity with probability 1 4 , next consecutive computing capacity with probability 1 6 , and so on, and maximum computing capacity with probability 1 3 .…”

Section: Main Game Modelmentioning

confidence: 99%

“…Task scheduling in the dynamic cloud environments is a complex process of contains multiple stages. Tasks may be scheduled as batch with (dependent) or without (independent) correlations among them [1]. In the scheduling process, the following special security-related users' requirements may be taken into account: selection of an appropriate amount of resources for utilization, safety, security, and intrusion detection.…”

Section: Introductionmentioning

confidence: 99%

Using Polymatrix Extensive Stackelberg Games in Security – Aware Resource Allocation and Task Scheduling in Computational Clouds

Wilczyński,

Jakóbik

2017

JTIT

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In this paper, the Stackelberg game models are used for supporting the decisions on task scheduling and resource utilization in computational clouds. Stackelberg games are asymmetric games, where a specific group of players’ acts first as leaders, and the rest of the players follow the leaders’ decisions and make their decisions based on the leader’s actions. In the proposed model, the optimal schedules are generated under the security criteria along with the generation of the optimal virtual machines set for the scheduled batch of tasks. The security criteria are defined as security requirements for mapping tasks onto virtual machines with specified trust level. The effectiveness of the proposed method has been verified in the realistic use cases with in the cloud environment with OpenStack and Amazon Cloud standards.

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“…However, unlike [12], we do not consider the realized priority as a given and fixed function of the priority of the principal and interests of the agent, but as a design parameter for the agent to maximize his own utility. Although there is a vast literature on multi-agent task scheduling literature (see, e.g., [13]- [15]), prior work does not consider either information asymmetry between the agents and the principal or the design of incentives. To the best of our knowledge, this paper is the first work to adopt a game-theoretic approach to analyzing priority misalignments between task senders and task receivers.…”

Section: Introductionmentioning

confidence: 99%

A game-theoretic approach to a task delegation problem

Dobakhshari

Varshney

Gupta

2017

2017 51st Asilomar Conference on Signals, Systems, and Computers

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We study a setting in which a principal selects an agent to execute a collection of tasks according to a specified priority sequence. Agents, however, have their own individual priority sequences according to which they wish to execute the tasks. There is information asymmetry since each priority sequence is private knowledge for the individual agent. We design a mechanism for selecting the agent and incentivizing the selected agent to realize a priority sequence for executing the tasks that achieves socially optimal performance. Our proposed mechanism consists of two parts. First, the principal runs an auction to select an agent to allocate tasks to with minimum declared priority sequence misalignment. Then, the principal rewards the agent according to the realized priority sequence with which the tasks were performed. We show that the proposed mechanism is individually rational and incentive compatible. Further, it is also socially optimal for the case of linear cost of priority sequence modification for the agents.

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Game theoretic approaches for job scheduling in cloud computing: A survey

Cited by 4 publications

References 19 publications

A load-balanced hybrid heuristic for allocation of batch of tasks in cloud computing environment

A load-balanced hybrid heuristic for allocation of batch of tasks in cloud computing environment

Using Polymatrix Extensive Stackelberg Games in Security – Aware Resource Allocation and Task Scheduling in Computational Clouds

A game-theoretic approach to a task delegation problem

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