Pub Date : 2019-06-01DOI: 10.1109/FMEC.2019.8795312
M. Rathore, Y. Jararweh, M. Raheel, Anand Paul
The smart city is established through continuous analytics of the city data that is harvested from various smart systems and IoT sensors deployed in the city such as, smart homes, buildings, and parking, smart pollution monitoring, transportation sensors, etc., which generates continuous streams of high-speed data. Lack of security and privacy in the smart city system while communicating with the central analysis building gives the control of the city to the cyber criminals. However, offering privacy and security for such a continuous high-speed communication requires an efficient security model without introducing any delay in the real-time communication of the smart city. Thus, to cater with these challenges, in this paper, we proposed an efficient authentication and key management model among the smart city entities such as, remote smart systems (RSS) (i.e., smart homes, smart parkings, smart health systems, environment control system, etc.), remote users (U), and central city analysis building. First, every remote system and citizen have to be registered with the system through secure registration phase. Later, the session keys are generated and shared among the smart city entities that are used in secure routine communication. Moreover, the protocol is enabled with an efficient secure communication mechanism with the ability of parallel processing that makes it possible to work in a real-time environment. Finally, the security of the proposed model is verified informally through mathematical analysis and formally by implementing it using AVISPA tool (Automated Validation of Internet Security Protocols and Applications). Also, the proposed protocol is evaluated in terms of its efficiency and capability to work in a real-time environment. The results show that the protocol is secure against known cyber-attacks, is efficient, and faster than the existing schemes.
{"title":"Securing High-Velocity Data: Authentication and Key Management Model for Smart City Communication","authors":"M. Rathore, Y. Jararweh, M. Raheel, Anand Paul","doi":"10.1109/FMEC.2019.8795312","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795312","url":null,"abstract":"The smart city is established through continuous analytics of the city data that is harvested from various smart systems and IoT sensors deployed in the city such as, smart homes, buildings, and parking, smart pollution monitoring, transportation sensors, etc., which generates continuous streams of high-speed data. Lack of security and privacy in the smart city system while communicating with the central analysis building gives the control of the city to the cyber criminals. However, offering privacy and security for such a continuous high-speed communication requires an efficient security model without introducing any delay in the real-time communication of the smart city. Thus, to cater with these challenges, in this paper, we proposed an efficient authentication and key management model among the smart city entities such as, remote smart systems (RSS) (i.e., smart homes, smart parkings, smart health systems, environment control system, etc.), remote users (U), and central city analysis building. First, every remote system and citizen have to be registered with the system through secure registration phase. Later, the session keys are generated and shared among the smart city entities that are used in secure routine communication. Moreover, the protocol is enabled with an efficient secure communication mechanism with the ability of parallel processing that makes it possible to work in a real-time environment. Finally, the security of the proposed model is verified informally through mathematical analysis and formally by implementing it using AVISPA tool (Automated Validation of Internet Security Protocols and Applications). Also, the proposed protocol is evaluated in terms of its efficiency and capability to work in a real-time environment. The results show that the protocol is secure against known cyber-attacks, is efficient, and faster than the existing schemes.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124335643","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795339
R. Beraldi, H. Alnuweiri
Fog computing promises to support many emerging classes of applications that can’t be rely on a cloud-only backend. Fog-to-Fog (F2F) cooperation is suggested in the openFog’s Fog computing Reference Architecture, now adopted as an IEEE standard, as a way to improve the computation service provided by this computing delivery model.In this paper, we propose DFR - Distributed Fair Randomized, a distributed F2F cooperation algorithm that allows for sharing computation resources among fog providers that agree on a (reasonable) measure of fairness. We adopt an analytical approach to study the cooperation problem of providers subject to different load conditions. We initially put the cooperation problem in the light of a simple game-theory framework to capture the selfish behavior of providers without any fairness criteria and its consequence in limiting cooperation. Then, we cast the problem as an optimization problem that incorporates fairness. Preliminary simulations results show how DFR converges to the predicted optimal value.
{"title":"Distributed Fair Randomized (DFR): a Resource Sharing Protocol for Fog Providers","authors":"R. Beraldi, H. Alnuweiri","doi":"10.1109/FMEC.2019.8795339","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795339","url":null,"abstract":"Fog computing promises to support many emerging classes of applications that can’t be rely on a cloud-only backend. Fog-to-Fog (F2F) cooperation is suggested in the openFog’s Fog computing Reference Architecture, now adopted as an IEEE standard, as a way to improve the computation service provided by this computing delivery model.In this paper, we propose DFR - Distributed Fair Randomized, a distributed F2F cooperation algorithm that allows for sharing computation resources among fog providers that agree on a (reasonable) measure of fairness. We adopt an analytical approach to study the cooperation problem of providers subject to different load conditions. We initially put the cooperation problem in the light of a simple game-theory framework to capture the selfish behavior of providers without any fairness criteria and its consequence in limiting cooperation. Then, we cast the problem as an optimization problem that incorporates fairness. Preliminary simulations results show how DFR converges to the predicted optimal value.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121183502","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795324
S. Kakakhel, Tomi Westerlund, M. Daneshtalab, Zhuo Zou, J. Plosila, H. Tenhunen
Protocols enable things to connect and communicate, thus making the Internet of Things possible. The performance aspect of the Internet of Things protocols, vital to its widespread utilization, have received much attention. However, one aspect of IoT protocols, essential to its adoption in the real world, is a protocols’ feature set. Comparative analysis based on competing features and properties are rarely if ever, discussed in the literature. In this paper, we define 19 attributes in 5 categories that are essential for IoT stakeholders to consider. These attributes are then used to contrast four IoT protocols, MQTT, HTTP, CoAP and XMPP. Furthermore, we discuss scenarios where an assessment based on comparative strengths and weaknesses would be beneficial. The provided comparison model can be easily extended to include protocols like MQTT-SN, AMQP and DDS.
{"title":"A Qualitative Comparison Model for Application Layer IoT Protocols","authors":"S. Kakakhel, Tomi Westerlund, M. Daneshtalab, Zhuo Zou, J. Plosila, H. Tenhunen","doi":"10.1109/FMEC.2019.8795324","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795324","url":null,"abstract":"Protocols enable things to connect and communicate, thus making the Internet of Things possible. The performance aspect of the Internet of Things protocols, vital to its widespread utilization, have received much attention. However, one aspect of IoT protocols, essential to its adoption in the real world, is a protocols’ feature set. Comparative analysis based on competing features and properties are rarely if ever, discussed in the literature. In this paper, we define 19 attributes in 5 categories that are essential for IoT stakeholders to consider. These attributes are then used to contrast four IoT protocols, MQTT, HTTP, CoAP and XMPP. Furthermore, we discuss scenarios where an assessment based on comparative strengths and weaknesses would be beneficial. The provided comparison model can be easily extended to include protocols like MQTT-SN, AMQP and DDS.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116405602","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795334
Hazem A. Abdelhafez, M. Ripeanu
Nowadays, heterogeneous unified memory architecture platforms are becoming increasingly common. These platforms incorporate several co-processors on a single chip with a shared physical memory. The use cases for such platforms can vary dramatically. On the one hand, they can be used in the context of Edge computing, which cannot tolerate high latency and has strict energy/power constraints. On the other hand, motivated by their growing computing capabilities, and their energy-efficiency, many have considered replacing traditional bulky servers with these platforms to deliver the same computing power but with lower energy budget. This study is an exploratory step to understand the trade-off between power consumption, processing time, and throughput on a low-power heterogeneous platform. We focus on data stream processing workloads by characterizing several common computing kernels found in computer vision algorithms. Our preliminary experiments on NVIDIA Jetson TX1 show that it is possible reduce power consumption by up to 12%.
{"title":"Studying the Impact of CPU and Memory Controller Frequencies on Power Consumption of the Jetson TX1","authors":"Hazem A. Abdelhafez, M. Ripeanu","doi":"10.1109/FMEC.2019.8795334","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795334","url":null,"abstract":"Nowadays, heterogeneous unified memory architecture platforms are becoming increasingly common. These platforms incorporate several co-processors on a single chip with a shared physical memory. The use cases for such platforms can vary dramatically. On the one hand, they can be used in the context of Edge computing, which cannot tolerate high latency and has strict energy/power constraints. On the other hand, motivated by their growing computing capabilities, and their energy-efficiency, many have considered replacing traditional bulky servers with these platforms to deliver the same computing power but with lower energy budget. This study is an exploratory step to understand the trade-off between power consumption, processing time, and throughput on a low-power heterogeneous platform. We focus on data stream processing workloads by characterizing several common computing kernels found in computer vision algorithms. Our preliminary experiments on NVIDIA Jetson TX1 show that it is possible reduce power consumption by up to 12%.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114375452","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 : 2019-06-01DOI: 10.1109/fmec.2019.8795330
{"title":"[Copyright notice]","authors":"","doi":"10.1109/fmec.2019.8795330","DOIUrl":"https://doi.org/10.1109/fmec.2019.8795330","url":null,"abstract":"","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"12 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125988471","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795351
G. Ciccarella, R. Giuliano, F. Mazzenga, F. Vatalaro, Alessandro Vizzarri
The Edge Cloud Computing (ECC) paradigm is rapidly imposing itself in telecommunications networks since when services such as 4K/8K video streaming, 360 degrees augmented/virtual reality, and autonomous driving started appearing on the horizon. This paper provides some case studies on performance improvement and Total Cost of Ownership (TCO) saving which can be achieved with ECC. It discusses the basic rationale for the ECC being the solution to improve KPIs in ultra-broad-band networks, and then it provides examples of performance and cost evaluation based on simulations.
{"title":"Edge Cloud Computing in Telecommunications: Case Studies on Performance Improvement and TCO Saving","authors":"G. Ciccarella, R. Giuliano, F. Mazzenga, F. Vatalaro, Alessandro Vizzarri","doi":"10.1109/FMEC.2019.8795351","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795351","url":null,"abstract":"The Edge Cloud Computing (ECC) paradigm is rapidly imposing itself in telecommunications networks since when services such as 4K/8K video streaming, 360 degrees augmented/virtual reality, and autonomous driving started appearing on the horizon. This paper provides some case studies on performance improvement and Total Cost of Ownership (TCO) saving which can be achieved with ECC. It discusses the basic rationale for the ECC being the solution to improve KPIs in ultra-broad-band networks, and then it provides examples of performance and cost evaluation based on simulations.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124827081","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795348
A. Randazzo, I. Tinnirello
Content delivery is one of the most successful applications in mobile networks. Mobile edge servers are significantly contributing to the improvement of this type of applications, by also performing resolution adaptations as a function of the radio link quality observed by the users. In this paper, we face the problem of dynamically tracking the perceived video resolution by mobile clients in a mobile edge environment to guarantee an agreed Service Level Agreement (SLA). To this purpose, we propose a protocol-agnostic approach, based on monitoring some memory metrics of a running video streaming process at the mobile client, for identifying the time-varying resolution of the video content.
{"title":"Recognizing Video Resolution by Monitoring Memory Metrics in Mobile Clients","authors":"A. Randazzo, I. Tinnirello","doi":"10.1109/FMEC.2019.8795348","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795348","url":null,"abstract":"Content delivery is one of the most successful applications in mobile networks. Mobile edge servers are significantly contributing to the improvement of this type of applications, by also performing resolution adaptations as a function of the radio link quality observed by the users. In this paper, we face the problem of dynamically tracking the perceived video resolution by mobile clients in a mobile edge environment to guarantee an agreed Service Level Agreement (SLA). To this purpose, we propose a protocol-agnostic approach, based on monitoring some memory metrics of a running video streaming process at the mobile client, for identifying the time-varying resolution of the video content.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130980845","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795340
V. Balasubramanian, Kees Kroep, K. Joshi, R. V. Prasad
In recent years, enormous growth has been witnessed in the computational and storage capabilities of mobile devices. However, much of this computational and storage capabilities are not always fully used. On the other hand, popularity of mobile edge computing which aims to replace the traditional centralized powerful cloud with multiple edge servers is rapidly growing. In particular, applications having strict latency requirements can be best served by the mobile edge clouds due to a reduced round-trip delay. In this paper we propose a Multi-Path TCP (MPTCP) enabled mobile device cloud (MDC) as a replacement to the existing TCP based or D2D device cloud techniques, as it effectively makes use of the available bandwidth by providing much higher throughput as well as ensures robust wireless connectivity. We investigate the congestion in mobile-device cloud formation resulting mainly due to the message passing for service providing nodes at the time of discovery, service continuity and formation of cloud composition. We propose a user space agent called congestion handler that enable offloading of packets from one sub-flow to the other under link quality constraints. Further, we discuss the benefits of this design and perform preliminary analysis of the system.
{"title":"Reinforcing Edge Computing with Multipath TCP Enabled Mobile Device Clouds","authors":"V. Balasubramanian, Kees Kroep, K. Joshi, R. V. Prasad","doi":"10.1109/FMEC.2019.8795340","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795340","url":null,"abstract":"In recent years, enormous growth has been witnessed in the computational and storage capabilities of mobile devices. However, much of this computational and storage capabilities are not always fully used. On the other hand, popularity of mobile edge computing which aims to replace the traditional centralized powerful cloud with multiple edge servers is rapidly growing. In particular, applications having strict latency requirements can be best served by the mobile edge clouds due to a reduced round-trip delay. In this paper we propose a Multi-Path TCP (MPTCP) enabled mobile device cloud (MDC) as a replacement to the existing TCP based or D2D device cloud techniques, as it effectively makes use of the available bandwidth by providing much higher throughput as well as ensures robust wireless connectivity. We investigate the congestion in mobile-device cloud formation resulting mainly due to the message passing for service providing nodes at the time of discovery, service continuity and formation of cloud composition. We propose a user space agent called congestion handler that enable offloading of packets from one sub-flow to the other under link quality constraints. Further, we discuss the benefits of this design and perform preliminary analysis of the system.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133513107","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795331
Shoayee Alotaibi, Rashid Mehmood, Iyad A. Katib
Social media including Twitter have transformed our societies and has become an important pulse of smart societies by sensing the information about the people and their experiences across space and time around the living spaces. This has allowed connecting with people, sensing their feelings and behaviors, and measuring the performance of various city systems such as healthcare and transport. The sentiment analysis of social media is a key step in this process. As of January 2019, Saudi Arabia had the fourth highest number of Twitter users in the world, after the US, Japan, and the UK. However, the works done on sentiment analysis in the Arabic language are limited in their scope and depth. Moreover, little is available in the literature on sentiment analysis in the Arabic and Saudi dialects. This paper aims to provide a resource on the sentiment analysis in the Arabic and Saudi dialects. It reviews the relevant tools and techniques considering their accuracy. We hope that this paper will be a useful guide for the researchers who are interested in the sentiment analysis of the Arabic and the Saudi dialects.
{"title":"Sentiment Analysis of Arabic Tweets in Smart Cities: A Review of Saudi Dialect","authors":"Shoayee Alotaibi, Rashid Mehmood, Iyad A. Katib","doi":"10.1109/FMEC.2019.8795331","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795331","url":null,"abstract":"Social media including Twitter have transformed our societies and has become an important pulse of smart societies by sensing the information about the people and their experiences across space and time around the living spaces. This has allowed connecting with people, sensing their feelings and behaviors, and measuring the performance of various city systems such as healthcare and transport. The sentiment analysis of social media is a key step in this process. As of January 2019, Saudi Arabia had the fourth highest number of Twitter users in the world, after the US, Japan, and the UK. However, the works done on sentiment analysis in the Arabic language are limited in their scope and depth. Moreover, little is available in the literature on sentiment analysis in the Arabic and Saudi dialects. This paper aims to provide a resource on the sentiment analysis in the Arabic and Saudi dialects. It reviews the relevant tools and techniques considering their accuracy. We hope that this paper will be a useful guide for the researchers who are interested in the sentiment analysis of the Arabic and the Saudi dialects.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132040737","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 : 2019-06-01DOI: 10.1109/FMEC.2019.8795337
Areeg Samir, C. Pahl
Edge cloud environments are often build as virtualized coordinated clusters of possibly heterogeneous devices. Their problem is that infrastructure metrics are only partially available and observable performance needs to be linked to underlying infrastructure problems in case of observed anomalies in order to remedy problems effectively. This paper presents an anomaly detection and prediction model based on Hidden Markov Model (HMM) that addresses the problem of mapping observations to underlying infrastructure problems. The model aims at detecting anomalies but also predicting them at runtime in order to optimize system availability and performance. The model detects changes in response time based on their resource utilization. We target a cluster architecture for edge computing where applications are deployed in the form of lightweight containers. To evaluate the proposed model, experiments were conducted considering CPU utilization, response time, and throughput as metrics. The results show that our HMM detection and prediction performs well and achieves accurate fault prediction.
{"title":"Detecting and Predicting Anomalies for Edge Cluster Environments using Hidden Markov Models","authors":"Areeg Samir, C. Pahl","doi":"10.1109/FMEC.2019.8795337","DOIUrl":"https://doi.org/10.1109/FMEC.2019.8795337","url":null,"abstract":"Edge cloud environments are often build as virtualized coordinated clusters of possibly heterogeneous devices. Their problem is that infrastructure metrics are only partially available and observable performance needs to be linked to underlying infrastructure problems in case of observed anomalies in order to remedy problems effectively. This paper presents an anomaly detection and prediction model based on Hidden Markov Model (HMM) that addresses the problem of mapping observations to underlying infrastructure problems. The model aims at detecting anomalies but also predicting them at runtime in order to optimize system availability and performance. The model detects changes in response time based on their resource utilization. We target a cluster architecture for edge computing where applications are deployed in the form of lightweight containers. To evaluate the proposed model, experiments were conducted considering CPU utilization, response time, and throughput as metrics. The results show that our HMM detection and prediction performs well and achieves accurate fault prediction.","PeriodicalId":101825,"journal":{"name":"2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132292397","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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