Task graph pre-scheduling, using Nash equilibrium in game theory

Abdeyazdan, Marjan; Parsa, Saeed; Rahmani, Amir Masoud

doi:10.1007/s11227-012-0845-z

Cited by 13 publications

(5 citation statements)

References 25 publications

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“…Simulations results showed that the proposed game could reduce the temperature difference between different groups of cores, which effectively avoids the local hotspot of a processor. (Abdeyazdan et al, 2013) applied the idea of Nash equilibrium in game theory for static tasks graph pre-scheduling on homogeneous multiprocessor architecture. Given a game with strategy sets for players, a pure Nash equilibrium is a strategy profile in which each player deterministically plays her chosen strategy and no one has an incentive to unilaterally change her strategy.…”

Section: Game Theorymentioning

confidence: 99%

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Boutekkouk

2022

International Journal of Cognitive Informatics and Natural Intelligence

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Artificial Intelligence is becoming more attractive to resolve nontrivial problems including the well known real time scheduling (RTS) problem for Embedded Systems (ES). The latter is considered as a hard multi-objective optimization problem because it must optimize at the same time three key conflictual objectives that are tasks deadlines guarantee, energy consumption reduction and reliability enhancement. In this paper, we firstly present the necessary background to well understand the problematic of RTS in the context of ES, then we present our enriched taxonomies for real time, energy and faults tolerance aware scheduling algorithms for ES. After that, we survey the most pertinent existing works of literature targeting the application of AI methods to resolve the RTS problem for ES notably Constraint Programming, Game theory, Machine learning, Fuzzy logic, Artificial Immune Systems, Cellular Automata, Evolutionary algorithms, Multi-agent Systems and Swarm Intelligence. We end this survey by a discussion putting the light on the main challenges and the future directions.

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Section: Game Theorymentioning

confidence: 99%

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Boutekkouk

2022

International Journal of Cognitive Informatics and Natural Intelligence

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“…Chen et al employing Primary/Backup technique and propose a game theoretical fault-tolerant task allocation algorithm for heterogeneous WSNs, which can balance the network energy under the restraint of task deadline [28]. In [29], M. Abdeyazdan et al consider each task as a player attempting to reduce its earliest time as much as possible, and applied the idea of Nash equilibrium in game theory to determine the most appropriate merging. Gao et al present a hybrid game approach which contains both cooperative behavior and competitive behavior for multi-hop wireless networks [30].…”

Section: Related Workmentioning

confidence: 99%

An Energy-efficiency Node Scheduling Game Based on Task Prediction in WSNs

Lin

Hassan

et al. 2015

Mobile Netw Appl

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For wireless sensor networks, unbalanced task load will decrease the lifetime of network. In this paper, we investigate how to schedule the sensor nodes to sleep or wakeup according to the dynamically changing task load. We first demonstrate that for a sensor network with uniform node distribution and constant data reporting, balancing the task load of the whole network cannot be realized. Then we define the concept of state transition and design a state transition model for sensor nodes. By introducing Markov chain, we further propose a task prediction method to predict the local task load in the next time period. Finally, we propose an energy-efficiency node scheduling algorithm based on game theory (ENSG) for WSNs. To obtain better performance, the residual energy of sensor nodes and local task load are both considered into the payoff function of our game. Our simulation results show that ENSG can guarantee the real-time task completion and prolong the lifetime of network.

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“…There are many energy efficient scheduling approaches [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] that have been studied from different scheduling perspectives. Energy efficient task scheduling is a scheduling algorithm that dynamically allocates jobs into processor to achieve better performance and to minimize energy consumption.…”

Section: Energy Efficient Schedulingmentioning

confidence: 99%

“…Equilibrium is a key concept in game theory and it aims to provide optimal solutions against several choices [14]. Nash equilibrium is a non-cooperative strategy where each player has its own game with its own way without bothering the other players.…”

Section: Game Theory Strategy For Energy Efficient Schedulingmentioning

confidence: 99%

“…There are also cooperative game theories such as Nash axiomatic which finds bargain point and settle down [18]. Pre-scheduling and Scheduling using Game Theory (PSGT) by Abdeyazdan et al [14] proposed energy efficient task scheduling with initial pre-scheduling process. PSGT aims for the best trade-off between makespan and energy consumption by discovering the equilibrium number of processors.…”

Section: Game Theory Strategy For Energy Efficient Schedulingmentioning

confidence: 99%

See 1 more Smart Citation

Energy Management for Cloud Computing: A Survey from Scheduling Perspective of Heuristic, Game Theory and Learning Strategy

Nor¹,

Hussin²,

Selamat³

2014

JCSCM

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Cloud computing has been a champion in Information Technology (IT) world for supporting flexibility on-demand services. It is leveraged to instantly fulfill dynamic demands from heterogeneous environment. However, the massive demand for the Cloud computing services contributed to high energy consumption, thus affecting cost of service and processing components lifetime. Quite a portion of the energy consumed is dissipated for ensuring processing components (i.e., processor) running but idle. An effective task scheduling is the solution for better processing performance while reducing energy consumption. In this paper we compared several energy efficient scheduling from three (3) different perspectives (i.e., heuristic, economic and intelligent points of view). These different perspectives are chosen particularly for exemplifying essential principles and features of energy management in task scheduling. Novel knowledge on the energy management are identified through similarities, differences and energy models. We believed that better trade-off between energy consumption and system performance is the solution to green Cloud computing.

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Task graph pre-scheduling, using Nash equilibrium in game theory

Cited by 13 publications

References 25 publications

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

An Energy-efficiency Node Scheduling Game Based on Task Prediction in WSNs

Energy Management for Cloud Computing: A Survey from Scheduling Perspective of Heuristic, Game Theory and Learning Strategy

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