Scheduling Multi-Workflows Over Heterogeneous Virtual Machines With a Multi-Stage Dynamic Game-Theoretic Approach

2018 ◽  
Vol 15 (4) ◽  
pp. 82-96 ◽  
Author(s):  
Lei Wu ◽  
Yuandou Wang

Cloud computing, with dependable, consistent, pervasive, and inexpensive access to geographically distributed computational capabilities, is becoming an increasingly popular platform for the execution of scientific applications such as scientific workflows. Scheduling multiple workflows over cloud infrastructures and resources is well recognized to be NP-hard and thus critical to meeting various types of Quality-of-Service (QoS) requirements. In this work, the authors consider a multi-objective scientific workflow scheduling framework based on the dynamic game-theoretic model. It aims at reducing make-spans, cloud cost, while maximizing system fairness in terms of workload distribution among heterogeneous cloud virtual machines (VMs). The authors consider randomly-generated scientific workflow templates as test cases and carry out extensive real-world tests based on third-party commercial clouds. Experimental results show that their proposed framework outperforms traditional ones by achieving lower make-spans, lower cost, and better system fairness.

2020 ◽  
Vol 117 (19) ◽  
pp. 10210-10217 ◽  
Author(s):  
Adam Lampert

The management of harmful species, including invasive species, pests, parasites, and diseases, is a major global challenge. Harmful species cause severe damage to ecosystems, biodiversity, agriculture, and human health. In particular, managing harmful species often requires cooperation among multiple agents, such as landowners, agencies, and countries. Each agent may have incentives to contribute less to the treatment, leaving more work for other agents, which may result in inefficient treatment. A central question is, therefore, how should a policymaker allocate treatment duties among the agents? Specifically, should the agents work together in the same area, or should each agent work only in a smaller area designated just for her/him? We consider a dynamic game-theoretic model, where a Nash equilibrium corresponds to a possible set of contributions that the agents could adopt over time. In turn, the allocation by the policymaker determines which of the Nash equilibria could be adopted, which allows us to compare the outcome of various allocations. Our results show that fewer agents can abate the harmful species population faster, but more agents can better control the population to keep its density lower. We prove this result in a general theorem and demonstrate it numerically for two case studies. Therefore, following an outbreak, the better policy would be to split and assign one or a few agents to treat the species in a given location, but if controlling the harmful species population at some low density is needed, the agents should work together in all of the locations.


2019 ◽  
Vol 31 (3) ◽  
pp. 286-307 ◽  
Author(s):  
Xinyu Fan ◽  
Feng Yang

While existing studies usually model promotion as a bilateral interaction between promoter and promotee, it is not uncommon that the promoter is under the influence of a third party. For instance, authoritarian rulers may consider how their interactions with local agents change the way that citizens view them. Similarly, a mid-tier officer in a bureaucratic hierarchy often concerns herself with her image in the eyes of her superior when managing her subordinates. In this paper, we construct a game-theoretic model to investigate promotion strategies when promoters have reputation concerns. We show that promoters can use promotion as a signaling tool, where she can deliberately postpone promoting the subordinate to enhance her own reputation. Furthermore, the promoter has extra incentives to shirk, knowing that she can manipulate promotion in the future. Thus, strategic promotions decrease government responsiveness. Counter-intuitively, such a decrease is more severe when intra-bureaucracy information is more transparent. In other words, transparency may do more harm than good. We conduct a case study of the Chinese bureaucracy and provide supportive evidence.


2014 ◽  
Vol 4 (1) ◽  
pp. 40-54 ◽  
Author(s):  
Hesham Osman ◽  
Mazdak Nikbakht

Purpose – The purpose of this paper is to present a socio-technical approach to modeling the behavior of roadway users, asset managers, and politicians toward roadway performance and asset management. This approach models the complex interactions that occur between these agents in a complex system. Most modeling approaches in the domain of infrastructure asset management take a purely asset-centric approach and fail to address these socio-technical interactions. Design/methodology/approach – Interactions among political decision makers, asset management strategy developers, and road users are modeled using a game-theoretic approach. The interactions are modeled as a non-cooperative game in which politicians, asset managers, and road users are the main players. Each player is autonomous and aims to come up with the set of moves to maximize their respective level of satisfaction in response to other players’ moves. Multi-attribute utility theory is used to deal with multitude of players’ goals, and the Nash equilibria of the game are south out to develop appropriate strategies for different players. Findings – An illustrative example for a road network of a Canadian city is used to demonstrate the developed methodology. The developed methodology demonstrates how behaviors of various agents involved in the sphere of asset management impacts their collective decision-making behavior. Originality/value – The developed framework provides asset managers and political decision makers with a valuable tool to evaluate the impact of public policy decisions related to asset managers on road performance and the overall satisfaction of road users.


2016 ◽  
Vol 283 (1842) ◽  
pp. 20161993 ◽  
Author(s):  
Gordon G. McNickle ◽  
Miquel A. Gonzalez-Meler ◽  
Douglas J. Lynch ◽  
Jennifer L. Baltzer ◽  
Joel S. Brown

Plants appear to produce an excess of leaves, stems and roots beyond what would provide the most efficient harvest of available resources. One way to understand this overproduction of tissues is that excess tissue production provides a competitive advantage. Game theoretic models predict overproduction of all tissues compared with non-game theoretic models because they explicitly account for this indirect competitive benefit. Here, we present a simple game theoretic model of plants simultaneously competing to harvest carbon and nitrogen. In the model, a plant's fitness is influenced by its own leaf, stem and root production, and the tissue production of others, which produces a triple tragedy of the commons. Our model predicts (i) absolute net primary production when compared with two independent global datasets; (ii) the allocation relationships to leaf, stem and root tissues in one dataset; (iii) the global distribution of biome types and the plant functional types found within each biome; and (iv) ecosystem responses to nitrogen or carbon fertilization. Our game theoretic approach removes the need to define allocation or vegetation type a priori but instead lets these emerge from the model as evolutionarily stable strategies. We believe this to be the simplest possible model that can describe plant production.


2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Patanjal Kumar ◽  
Dheeraj Sharma ◽  
Peeyush Pandey

PurposeSupply chain network is complicated to manage due to the involvement of a number of agents. Formation of virtual organization using Industry 4.0 (I4.0) is an approach to improve the efficiency and effectiveness and to overcome the complexities of the channel. However, the task of managing the channel further becomes complicated after incorporating sustainability into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of I4.0-based virtual organization to coordinate sustainable supply chain.Design/methodology/approachIn this paper, we model and compare I4.0-based virtual organization models using four other traditional contracts with centralized supply chain. The non-cooperative game theoretic approach has been used for the analysis of models.FindingsOur game-theoretic analysis shows that investment in I4.0 and sustainable innovation are beneficial for the overall supply chain. Our results show that linear two-part tariff contract and I4.0-based virtual organization model can perfectly coordinated with the supply chain.Research limitations/implicationsThis study consider deterministic model settings with full information game. Therefore researchers are encouraged to study I4.0-based coordination models under information asymmetry and uncertain situations.Practical implicationsThe paper includes implications for the development of I4.0-based coordination model to tackle the problems of channel coordination.Originality/valueThis study proposes I4.0-based game-theoretic model for the sustainable supply chain coordination.


2005 ◽  
Vol 5 (2) ◽  
pp. 147-178 ◽  
Author(s):  
PENGCHENG ZHANG ◽  
SRINIVAS PEETA ◽  
TERRY FRIESZ

2020 ◽  
Vol 23 (3) ◽  
pp. 2035-2046 ◽  
Author(s):  
Rajani Singh ◽  
Ashutosh Dhar Dwivedi ◽  
Gautam Srivastava ◽  
Agnieszka Wiszniewska-Matyszkiel ◽  
Xiaochun Cheng

Abstract Blockchain and cryptocurrency are a hot topic in today’s digital world. In this paper, we create a game theoretic model in continuous time. We consider a dynamic game model of the bitcoin market, where miners or players use mining systems to mine bitcoin by investing electricity into the mining system. Although this work is motivated by BTC, the work presented can be applicable to other mining systems similar to BTC. We propose three concepts of dynamic game theoretic solutions to the model: Social optimum, Nash equilibrium and myopic Nash equilibrium. Using the model that a player represents a single “miner” or a “mining pool”, we develop novel and interesting results for the cryptocurrency world.


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