Allocating Limited Resources to Protect a Massive Number of Targets using a Game Theoretic Model

Resource allocation is the process of optimizing the rare resources. In the area of security, how to allocate limited resources to protect a massive number of targets is especially challenging. This paper addresses this resource allocation issue by constructing a game theoretic model. A defender and an attacker are players and the interaction is formulated as a trade-off between protecting targets and consuming resources. The action cost which is a necessary role of consuming resource, is considered in the proposed model. Additionally, a bounded rational behavior model (Quantal Response, QR), which simulates a human attacker of the adversarial nature, is introduced to improve the proposed model. To validate the proposed model, we compare the different utility functions and resource allocation strategies. The comparison results suggest that the proposed resource allocation strategy performs better than others in the perspective of utility and resource effectiveness.Comment: 14 pages, 12 figures, 41 reference

클라우드 서비스 연합 장려 모델

학위논문 (석사)-- 서울대학교 대학원 공과대학 협동과정 기술경영·경제·정책전공, 2017. 8. Jorn Altmann.In cloud computing, big service providers rule the market due to the economies of scale. A cloud federation presents a possible solution that allows small cloud providers to increase their competitiveness by making alliances with one another, thus forming a network with shared resources. Previous research suggests several different variables that may incentivize the participation of a selfish cloud provider, such as cost disparity, big competitors, and an efficient revenue sharing mechanism. It can be assumed that each individual cloud provider aims to maximize its profits and will choose to make alliances that provide it a constant benefit. For deciding on whether to federate or not, cloud providers take into consideration whether the federation-underlying revenue sharing will yield them an increase in profits. The proposed study models the interactions between selfish heterogeneous agents in a repeated game that aims to maximize individual profits. Each agent starts off as an individual and is allowed to change its strategies and federate with other providers in order to improve its own performance. By looking at the speed of collaboration and overall profit of individuals, we can determine which specific incentives encourage the creation of cloud federations.Chapter 1 Introduction 1 1.1 Cloud Computing 1 1.2 Problem Description 2 1.3 Research Objective 3 Chapter 2 Related Work.. 4 Chapter 3 Experiment Formulation 8 3.1 Model 8 3.2 Experiment Setup 10 3.2.1 Revenue Sharing. 11 3.2.2 Capacity Disparity 14 3.2.3 Cost Disparity. 15 3.2.4 Big Competitor. 16 3.2.5 Volatile Demand. 17 Chapter 4 Results 17 4.1 Revenue Sharing Scenario 18 4.2 Capacity Disparity Scenario 19 4.3 Cost Disparity Scenario. 21 4.4 Big Competitor Scenario 22 4.5 Federation Behavior in Demand Peaks. 23 Chapter 5 Conclusions.. 24 5.1 Summary. 24 5.2 Discussion and Implications. 25 5.3 Limitations and Future Work 26 Bibliography. 27 Abstract. 29Maste