Yue Jin, M. Bouzid, Dimitre Kostadinov, A. Aghasaryan
{"title":"Model-free resource management of cloud-based applications using reinforcement learning","authors":"Yue Jin, M. Bouzid, Dimitre Kostadinov, A. Aghasaryan","doi":"10.1109/ICIN.2018.8401615","DOIUrl":"https://doi.org/10.1109/ICIN.2018.8401615","url":null,"abstract":"The digital system of the future will face the growing challenge of controlling the system behavior in complex dynamically evolving environments. In this paper, we examine the applicability of a new management paradigm based on Reinforcement Learning approach, where no preliminary specification of the system model is required. In contrast, the learning agent identifies the most adequate control policies in live interaction with a partially observed system and provides it with autonomous management capabilities. We present the results of experimentation with Cloud- based applications and discuss the technical challenges that need to be addressed in this field.","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132889227","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}
{"title":"Design of C-RAN fronthaul for LTE networks","authors":"H. Silva, L. Correia, Pompeu Costa","doi":"10.1109/ICIN.2018.8401583","DOIUrl":"https://doi.org/10.1109/ICIN.2018.8401583","url":null,"abstract":"C-RAN is a mobile network architecture that enables the share of network resources in a centralised data centre, being cost- effective to the operators. This work consists of a study on the impact of C-RAN in an operator's network, addressing models for the latency and the capacity needed per data centre. The costs associated with the implementation of C-RAN are also modelled, and a comparison with the corresponding decentralised network is shown. The model was implemented taking as an input the positioning of RRHs and possible available BBU Pools, as well as the costs associated with each component, with four types of connection algorithms. The real scenario of a northern region in Portugal is taken for the analysis of results. Concerning fronthaul connections, a microwave link is not cost effective comparing with a fibre one. Cost savings, comparing a decentralised with a C-RAN architecture, is around 13%, and fronthaul costs are the most expensive component.","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133974439","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}
Yue Jin, M. Bouzid, Dimitre Kostadinov, A. Aghasaryan
{"title":"Testing a Q-learning approach for derivation of scaling policies in cloud-based applications","authors":"Yue Jin, M. Bouzid, Dimitre Kostadinov, A. Aghasaryan","doi":"10.1109/ICIN.2018.8401621","DOIUrl":"https://doi.org/10.1109/ICIN.2018.8401621","url":null,"abstract":"In this demonstration, we show the applicability of a new management paradigm based on Reinforcement Learning approach for the control of systems' behavior in complex dynamically evolving environments, without requiring preliminary specifications of the system models. The learning agent identifies the most adequate control policies in live interaction with a partially observed system and provides it with autonomous management capabilities. We present an experimentation with a simulated and a real Cloud-based application, and compare the results with other approaches.","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117051850","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}
{"title":"Anticipating minimum resources needed to avoid service disruption of emergency support systems","authors":"P. Martinez-Julia, Ved P. Kafle, H. Harai","doi":"10.1109/ICIN.2018.8401614","DOIUrl":"https://doi.org/10.1109/ICIN.2018.8401614","url":null,"abstract":"Advancement in the optimization of resources motivates us to study new mechanisms for the automated and elastic adaptation of virtual computer and network systems. Thus we designed the Autonomic Resource Control Architecture (ARCA), which considers the workload of the controlled system together with events notified by external detectors to perform its work. However, there is a delay between the occurrence of an event and the adaptation of the system. In this paper we propose a mechanism to enable ARCA to anticipate the minimum resource amount required by the controlled system under different situations by using a Machine Learning (ML) mechanism. Related solutions only consider the monitoring data provided by the controlled system, require a long learning period, are fragile to topology changes, and are unfeasible for real time operations. We propose to resolve such problems by using a threshold-based method to self-assess and self-correct the knowledge of our ML-based method, thus achieving self-learning qualities and ensuring that correct decisions are issued. Moreover, we set computational boundaries to the algorithm, so it runs within acceptable performance limits. Finally, we demonstrate its qualities by executing a simulation on a generated dataset following a demonstrated behavior, showing that the anticipation method results in no drop of client requests, using just 15% more resources than a threshold-based method.","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129559116","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}
{"title":"Copyright page","authors":"","doi":"10.23919/chicc.2018.8483486","DOIUrl":"https://doi.org/10.23919/chicc.2018.8483486","url":null,"abstract":"","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121128457","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}
{"title":"Foreword NI 2018","authors":"","doi":"10.1109/icin.2018.8401575","DOIUrl":"https://doi.org/10.1109/icin.2018.8401575","url":null,"abstract":"","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126651813","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}
{"title":"Density-aware cell zooming","authors":"Okan Yaman, Alperen Eroğlu, E. Onur","doi":"10.1109/ICIN.2018.8401612","DOIUrl":"https://doi.org/10.1109/ICIN.2018.8401612","url":null,"abstract":"Ultra-dense deployments and mobile cells significantly change cellular networking paradigm. Infrastructure and topology of cellular networks become dynamic as opposed to legacy systems where the infrastructure is assumed to be stationary. As topology morphs, base station or user density of networks also change impacting the performance in terms of resource utilization and quality of service. To increase network capacity, preserve coverage and conserve energy, network density should be considered in communication stacks to make the network density-aware and -adaptive. In this work, we analyze the impact of density on network outage in cellular networks. We propose a novel cell zooming technique at run-time considering network outage and density jointly with a three-dimensional base station density estimator.","PeriodicalId":103076,"journal":{"name":"2018 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)","volume":"36 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132915688","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}