Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963115
Jihene Ben Rejeb, I. Morǎrescu, A. Girard, J. Daafouz
The paper deals with singularly perturbed hybrid systems. It proposes a methodology for building a graph defining all the rules that ensure the origin is a stable equilibrium in presence of a dwell-time of order of the parameter defining the ratio between the two time-scales of the system. In this framework one can also treat the corresponding problem for interesting particular cases such as: singularly perturbed switched linear systems without impulses, one scale hybrid systems or one scale switched systems. A numerical example illustrates the theoretical results completing the paper.
{"title":"Design of O(ε) dwell-time graph for stability of singularly perturbed hybrid linear systems","authors":"Jihene Ben Rejeb, I. Morǎrescu, A. Girard, J. Daafouz","doi":"10.23919/ACC.2017.7963115","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963115","url":null,"abstract":"The paper deals with singularly perturbed hybrid systems. It proposes a methodology for building a graph defining all the rules that ensure the origin is a stable equilibrium in presence of a dwell-time of order of the parameter defining the ratio between the two time-scales of the system. In this framework one can also treat the corresponding problem for interesting particular cases such as: singularly perturbed switched linear systems without impulses, one scale hybrid systems or one scale switched systems. A numerical example illustrates the theoretical results completing the paper.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122414008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963309
Tianyi He, A. K. Al-Jiboory, S. Swei, G. Zhu
This paper presents a new method to design Robust Switching State-Feedback Gain-Scheduling (RSSFGS) controllers for Linear Parameter Varying (LPV) systems with uncertain scheduling parameters. The domain of scheduling parameters are divided into several overlapped subregions to undergo hysteresis switching among a family of simultaneously designed LPV controllers over the corresponding subregion with the guaranteed ℋ∞ performance. The synthesis conditions are given in terms of Parameterized Linear Matrix Inequalities that guarantee both stability and performance at each subregion and associated switching surfaces. The switching stability is ensured by descent parameter-dependent Lyapunov function on switching surfaces. By solving the optimization problem, RSSFGS controller can be obtained for each subregion. A numerical example is given to illustrate the effectiveness of the proposed approach over the non-switching controllers.
{"title":"Switching State-Feedback LPV control with uncertain scheduling parameters","authors":"Tianyi He, A. K. Al-Jiboory, S. Swei, G. Zhu","doi":"10.23919/ACC.2017.7963309","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963309","url":null,"abstract":"This paper presents a new method to design Robust Switching State-Feedback Gain-Scheduling (RSSFGS) controllers for Linear Parameter Varying (LPV) systems with uncertain scheduling parameters. The domain of scheduling parameters are divided into several overlapped subregions to undergo hysteresis switching among a family of simultaneously designed LPV controllers over the corresponding subregion with the guaranteed ℋ∞ performance. The synthesis conditions are given in terms of Parameterized Linear Matrix Inequalities that guarantee both stability and performance at each subregion and associated switching surfaces. The switching stability is ensured by descent parameter-dependent Lyapunov function on switching surfaces. By solving the optimization problem, RSSFGS controller can be obtained for each subregion. A numerical example is given to illustrate the effectiveness of the proposed approach over the non-switching controllers.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128924199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963792
S. Gelmini, S. Sabatini, Mark A. Hoffman, S. Onori
A three way catalytic converter (TWC) is responsible for conversion of engine out hazardous pollutants such as carbon monoxide (CO), nitrogen oxides (NOx) and hydrocarbons (HC) into carbon dioxide (CO2), water (H2O) and (N2) nitrogen. TWC conversion efficiency highly depends on the amount of oxygen stored in the converter, or State of Oxygen (SOX). Estimation of SOX during real time operation is key controlling the TWC behaviour maximizing its efficiency. Moreover, the decrease of TWC conversion efficiency over converter lifetime due to mechanical, chemical and thermal factors, is observed through the decrease of a macroscopic quantity, the Oxygen Storage Capacity (OSC). In this paper, a Dual Extended Kalman Filter (d-EKF) to estimate TWC SOX and OSC is presented. The observer is built upon an experimentally validated, physics-based model of the converter developed by the same authors in a previous work. The nonlinear partial differential equation-based TWC model is properly adapted, through the finite discrete method, for real-time estimation within a vehicle engine-control unit (ECU). Experimental results collected from a TWC instrumented with wide-range oxygen sensors show the ability of the dual observer to robustly estimate both SOX and the catalyst age.
{"title":"Development and experimental validation of a Dual Extended Kalman Filter for three way catalytic converter","authors":"S. Gelmini, S. Sabatini, Mark A. Hoffman, S. Onori","doi":"10.23919/ACC.2017.7963792","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963792","url":null,"abstract":"A three way catalytic converter (TWC) is responsible for conversion of engine out hazardous pollutants such as carbon monoxide (CO), nitrogen oxides (NOx) and hydrocarbons (HC) into carbon dioxide (CO2), water (H2O) and (N2) nitrogen. TWC conversion efficiency highly depends on the amount of oxygen stored in the converter, or State of Oxygen (SOX). Estimation of SOX during real time operation is key controlling the TWC behaviour maximizing its efficiency. Moreover, the decrease of TWC conversion efficiency over converter lifetime due to mechanical, chemical and thermal factors, is observed through the decrease of a macroscopic quantity, the Oxygen Storage Capacity (OSC). In this paper, a Dual Extended Kalman Filter (d-EKF) to estimate TWC SOX and OSC is presented. The observer is built upon an experimentally validated, physics-based model of the converter developed by the same authors in a previous work. The nonlinear partial differential equation-based TWC model is properly adapted, through the finite discrete method, for real-time estimation within a vehicle engine-control unit (ECU). Experimental results collected from a TWC instrumented with wide-range oxygen sensors show the ability of the dual observer to robustly estimate both SOX and the catalyst age.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"406 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128931284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963810
David Umsonst, H. Sandberg, A. Cárdenas
Two anomaly detectors for control systems are analyzed with respect to their sensitivity to malicious data injection attacks. A stateless anomaly detector based on the current residual signal is compared to a cumulative sum detector. The worst-case impact of a stealthy time-limited data injection attack is characterized for both detectors by a non-convex optimization problem and compared to determine which detector limits the impact the most. We prove that the problem can be solved by means of a set of convex optimization problems. Simulations verify that finding the right configuration for the cumulative sum is crucial to limit the worst-case attack impact more than with a stateless anomaly detector.
{"title":"Security analysis of control system anomaly detectors","authors":"David Umsonst, H. Sandberg, A. Cárdenas","doi":"10.23919/ACC.2017.7963810","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963810","url":null,"abstract":"Two anomaly detectors for control systems are analyzed with respect to their sensitivity to malicious data injection attacks. A stateless anomaly detector based on the current residual signal is compared to a cumulative sum detector. The worst-case impact of a stealthy time-limited data injection attack is characterized for both detectors by a non-convex optimization problem and compared to determine which detector limits the impact the most. We prove that the problem can be solved by means of a set of convex optimization problems. Simulations verify that finding the right configuration for the cumulative sum is crucial to limit the worst-case attack impact more than with a stateless anomaly detector.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123320102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963824
Vincent A. Laurense, Jonathan Y. Goh, J. C. Gerdes
The ability to use all of the available tire force is essential to road vehicles for emergency maneuvers and racing. As the front tires of an understeering vehicle saturate while cornering at the limit of tire-road friction, steering is lost as a control input for path-tracking. Experimental data from an autonomous vehicle show that for path-tracking at the limit of friction through steering the value of friction needs to be known to within approximately 2%. This requirement exceeds the capabilities of existing real-time friction estimation algorithms. Data collected with a professional race car driver inspire a novel control framework, with a slip angle-based control strategy of maintaining the front tires at the slip angle for which maximum tire force is attained, and longitudinal speed control for path-tracking. This approach has significantly less demanding requirements on the accuracy of friction estimation. A controller is presented to explore this concept, and experimental results demonstrate successful tracking of a circular path at the friction limit without a priori friction information.
{"title":"Path-tracking for autonomous vehicles at the limit of friction","authors":"Vincent A. Laurense, Jonathan Y. Goh, J. C. Gerdes","doi":"10.23919/ACC.2017.7963824","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963824","url":null,"abstract":"The ability to use all of the available tire force is essential to road vehicles for emergency maneuvers and racing. As the front tires of an understeering vehicle saturate while cornering at the limit of tire-road friction, steering is lost as a control input for path-tracking. Experimental data from an autonomous vehicle show that for path-tracking at the limit of friction through steering the value of friction needs to be known to within approximately 2%. This requirement exceeds the capabilities of existing real-time friction estimation algorithms. Data collected with a professional race car driver inspire a novel control framework, with a slip angle-based control strategy of maintaining the front tires at the slip angle for which maximum tire force is attained, and longitudinal speed control for path-tracking. This approach has significantly less demanding requirements on the accuracy of friction estimation. A controller is presented to explore this concept, and experimental results demonstrate successful tracking of a circular path at the friction limit without a priori friction information.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114689523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7962935
Nima Lotfi, Jie Li, R. Landers, Jonghyun Park
Health-conscious battery management is one of the main facilitators for widespread commercialization of Li-ion batteries as the primary power source in electrified transportation and portable electronics and as the backup source in stationary energy storage systems. The majority of the existing Battery Management Systems (BMSs) define battery State of Health (SOH) in terms of internal resistance increase or battery capacity decay and use various open-loop criteria based on the battery cycle number and/or operating conditions to determine its SOH. However, considering the wide range of operating conditions and current profiles for Li-ion batteries, the use of a closed-loop SOH estimation approach based on the measureable quantities of the battery along with a battery model is of great importance. In this work, the battery internal resistance increase which can be attributed to various chemical and mechanical degradation mechanisms is considered as the measure of the battery SOH. In order to estimate the SOH, a modified reduced-order electrochemical model based on the Single Particle (SP) Li-ion battery model is proposed to improve the traditional SP model accuracy. This model not only incorporates an analytical expression for the electrolyte-phase potential difference, it is also capable of accurately predicting the battery performance over a wide range of operating currents by considering the effects of the unmodeled dynamics. Finally, this model integrated with an adaptive output-injection observer to estimate the SP model states and the output model uncertainties, can be used to estimate the internal resistance increase during the battery lifetime. The modeling and estimation results are validated via a comparison to the full-order electrochemical model simulations.
{"title":"Li-ion Battery State of Health Estimation based on an improved Single Particle model","authors":"Nima Lotfi, Jie Li, R. Landers, Jonghyun Park","doi":"10.23919/ACC.2017.7962935","DOIUrl":"https://doi.org/10.23919/ACC.2017.7962935","url":null,"abstract":"Health-conscious battery management is one of the main facilitators for widespread commercialization of Li-ion batteries as the primary power source in electrified transportation and portable electronics and as the backup source in stationary energy storage systems. The majority of the existing Battery Management Systems (BMSs) define battery State of Health (SOH) in terms of internal resistance increase or battery capacity decay and use various open-loop criteria based on the battery cycle number and/or operating conditions to determine its SOH. However, considering the wide range of operating conditions and current profiles for Li-ion batteries, the use of a closed-loop SOH estimation approach based on the measureable quantities of the battery along with a battery model is of great importance. In this work, the battery internal resistance increase which can be attributed to various chemical and mechanical degradation mechanisms is considered as the measure of the battery SOH. In order to estimate the SOH, a modified reduced-order electrochemical model based on the Single Particle (SP) Li-ion battery model is proposed to improve the traditional SP model accuracy. This model not only incorporates an analytical expression for the electrolyte-phase potential difference, it is also capable of accurately predicting the battery performance over a wide range of operating currents by considering the effects of the unmodeled dynamics. Finally, this model integrated with an adaptive output-injection observer to estimate the SP model states and the output model uncertainties, can be used to estimate the internal resistance increase during the battery lifetime. The modeling and estimation results are validated via a comparison to the full-order electrochemical model simulations.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115846319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963169
Zhanrui Liao, Longsheng Jiang, Yue Wang
Human-robot collaborations (HRC) can be used for object detection in domain search tasks, which integrate human and computer vision to improve accuracy and efficiency. The Bayesian sequential decision-making (BSD) method has been used for task allocation of a robot in search tasks. In this paper, we first provide an explanation to reveal the nature of the BSD approach: it makes decisions based on the expected value criterion, which is proved to be very different from human decision-making behaviors. On the other hand, it has been shown that joint performance of a team will improve if all members share the same decision-making logic. In HRC, since forcing a human to act like a robot is not desired, we propose to modify the BSD approach such that the robot imitates human logic. In particular, regret theory qualitatively models human's rational decision-making behaviors under uncertainty. We propose a holistic framework to measure regret quantitatively, an individual-based parametric model that fits the measurements, and the integration of regret into the BSD method. Furthermore, we design a human-in-the-loop experiment based on the framework to collect enough data points to further elicit requisite functions of regret theory. Our preliminary results match all the properties in regret theory, while the parametric elicited model shows a good fit to the experimental data.
{"title":"A quantitative measure of regret in decision-making for human-robot collaborative search tasks","authors":"Zhanrui Liao, Longsheng Jiang, Yue Wang","doi":"10.23919/ACC.2017.7963169","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963169","url":null,"abstract":"Human-robot collaborations (HRC) can be used for object detection in domain search tasks, which integrate human and computer vision to improve accuracy and efficiency. The Bayesian sequential decision-making (BSD) method has been used for task allocation of a robot in search tasks. In this paper, we first provide an explanation to reveal the nature of the BSD approach: it makes decisions based on the expected value criterion, which is proved to be very different from human decision-making behaviors. On the other hand, it has been shown that joint performance of a team will improve if all members share the same decision-making logic. In HRC, since forcing a human to act like a robot is not desired, we propose to modify the BSD approach such that the robot imitates human logic. In particular, regret theory qualitatively models human's rational decision-making behaviors under uncertainty. We propose a holistic framework to measure regret quantitatively, an individual-based parametric model that fits the measurements, and the integration of regret into the BSD method. Furthermore, we design a human-in-the-loop experiment based on the framework to collect enough data points to further elicit requisite functions of regret theory. Our preliminary results match all the properties in regret theory, while the parametric elicited model shows a good fit to the experimental data.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134074626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963625
Zhanhong Jiang, K. Mukherjee, S. Sarkar
The generalized gossip-based subgradient algorithm has been recently proposed for solving distributed optimization problems associated with multi-agent networks. The algorithm provides a generalization such that the optimization process can operate in the entire spectrum of “complete consensus” to “complete disagreement”. Beyond the existing work of first-order convergence analysis results, this paper presents the second-order convergence results and convergence rate estimates for the proposed algorithm. Moreover, this work also takes into consideration the effect of noise in subgradient estimates as well as measurements on the function value error bounds. A numerical case study based on a building energy system is presented to validate the algorithm.
{"title":"Convergence and noise effect analysis for generalized gossip-based distributed optimization","authors":"Zhanhong Jiang, K. Mukherjee, S. Sarkar","doi":"10.23919/ACC.2017.7963625","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963625","url":null,"abstract":"The generalized gossip-based subgradient algorithm has been recently proposed for solving distributed optimization problems associated with multi-agent networks. The algorithm provides a generalization such that the optimization process can operate in the entire spectrum of “complete consensus” to “complete disagreement”. Beyond the existing work of first-order convergence analysis results, this paper presents the second-order convergence results and convergence rate estimates for the proposed algorithm. Moreover, this work also takes into consideration the effect of noise in subgradient estimates as well as measurements on the function value error bounds. A numerical case study based on a building energy system is presented to validate the algorithm.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134602261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963045
B. Novoselnik, J. Matuško, M. Baotic
Microgrid is a cluster of distributed (renewable) generation sources, storage units and loads, which, when controlled in an optimal fashion, can improve both the quality of the local power supply as well as the performance of the overall power distribution system. In this paper we present a robust control methodology for microgrids that can cope with uncertainties introduced by intermittent renewable energy sources and variable loads. Our control approach is based on a tube scaling model predictive control where new optimization variables - scaling factors - are introduced that optimally balance disturbance compensation by individual controllable microgrid entities. The control actions are determined such that all microgrid constraints are satisfied for all possible realizations of the bounded disturbance. Performance of the proposed control strategy is illustrated with a numerical example.
{"title":"Robust microgrid control using tube scaling approach","authors":"B. Novoselnik, J. Matuško, M. Baotic","doi":"10.23919/ACC.2017.7963045","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963045","url":null,"abstract":"Microgrid is a cluster of distributed (renewable) generation sources, storage units and loads, which, when controlled in an optimal fashion, can improve both the quality of the local power supply as well as the performance of the overall power distribution system. In this paper we present a robust control methodology for microgrids that can cope with uncertainties introduced by intermittent renewable energy sources and variable loads. Our control approach is based on a tube scaling model predictive control where new optimization variables - scaling factors - are introduced that optimally balance disturbance compensation by individual controllable microgrid entities. The control actions are determined such that all microgrid constraints are satisfied for all possible realizations of the bounded disturbance. Performance of the proposed control strategy is illustrated with a numerical example.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133116906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-05-24DOI: 10.23919/ACC.2017.7963667
Kevin Schubert, Neal Master, Zhengyuan Zhou, N. Bambos
Cloud computing refers to a computing paradigm in which a service provider (i.e. server) provides computing resources to service receivers (i.e. clients) who have heterogeneous requirements for completing their computational jobs. In this paper we consider a decentralized auction-based mechanism for studying this resource allocation problem. This model allows for a general class of queueing processes (representing the computational job arrivals) along with a general class of incentive-compatible bidding mechanisms. This gives us insights into the interplay between the economic and queueing considerations of clients in real-world cloud computing systems. Specifically, we show existence and uniqueness of a Nash equilibrium for the induced game and also show that asynchronous best-response dynamics are sufficient for achieving this equilibrium. The distributed and decentralized dynamics require little communication, thus providing a scheme that can be used to guide implementations in practice.
{"title":"Asynchronous best-response dynamics for resource allocation games in cloud computing","authors":"Kevin Schubert, Neal Master, Zhengyuan Zhou, N. Bambos","doi":"10.23919/ACC.2017.7963667","DOIUrl":"https://doi.org/10.23919/ACC.2017.7963667","url":null,"abstract":"Cloud computing refers to a computing paradigm in which a service provider (i.e. server) provides computing resources to service receivers (i.e. clients) who have heterogeneous requirements for completing their computational jobs. In this paper we consider a decentralized auction-based mechanism for studying this resource allocation problem. This model allows for a general class of queueing processes (representing the computational job arrivals) along with a general class of incentive-compatible bidding mechanisms. This gives us insights into the interplay between the economic and queueing considerations of clients in real-world cloud computing systems. Specifically, we show existence and uniqueness of a Nash equilibrium for the induced game and also show that asynchronous best-response dynamics are sufficient for achieving this equilibrium. The distributed and decentralized dynamics require little communication, thus providing a scheme that can be used to guide implementations in practice.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133130479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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