{"title":"Proactive Guidance for Dynamic and Cooperative Resource Allocation under Uncertainties","authors":"Gerrit Anders, Florian Siefert, M. Mair, W. Reif","doi":"10.1109/SASO.2014.14","DOIUrl":null,"url":null,"abstract":"In many technical systems, such as smart grids, the central issue is to enable multiple devices to solve a resource allocation problem in a cooperative manner. If the devices' ability to change their contribution is subject to inertia, the problem has to be solved proactively. This means that the allocation of resources is scheduled beforehand, based on predictions of the future demand. Because of the scheduling problem's complexity, schedules should be created rather sporadically for a coarse-grained time pattern. However, because the resource allocation problem has to be solved for all time steps and the demand and provision of resources is uncertain, devices have to reactively adapt their contributions according to the current circumstances. In this paper, we present a mechanism that allows the participants to incorporate the information of proactively created schedules in their reactive decisions in order to steer the system in a stable and efficient way. In particular, the decisions are guided by schedules that already include information about possible uncertainties. While this combination avoids inertia based problems, it significantly reduces the computational costs of searching for high quality solutions. Throughout the paper, the problem of maintaining the balance between energy production and consumption in decentralized autonomous power management systems serves to illustrate our algorithm and results.","PeriodicalId":6458,"journal":{"name":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SASO.2014.14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In many technical systems, such as smart grids, the central issue is to enable multiple devices to solve a resource allocation problem in a cooperative manner. If the devices' ability to change their contribution is subject to inertia, the problem has to be solved proactively. This means that the allocation of resources is scheduled beforehand, based on predictions of the future demand. Because of the scheduling problem's complexity, schedules should be created rather sporadically for a coarse-grained time pattern. However, because the resource allocation problem has to be solved for all time steps and the demand and provision of resources is uncertain, devices have to reactively adapt their contributions according to the current circumstances. In this paper, we present a mechanism that allows the participants to incorporate the information of proactively created schedules in their reactive decisions in order to steer the system in a stable and efficient way. In particular, the decisions are guided by schedules that already include information about possible uncertainties. While this combination avoids inertia based problems, it significantly reduces the computational costs of searching for high quality solutions. Throughout the paper, the problem of maintaining the balance between energy production and consumption in decentralized autonomous power management systems serves to illustrate our algorithm and results.