Pub Date : 2017-05-01DOI: 10.23919/INM.2017.7987456
Ruijian An, Zhi Liu, Yusheng Ji
In this paper, we target the resource allocation and layer selection problem for the realtime video streaming over highway scenario, by employing Scalable Video Coding (SVC) for the video contents. Especially, we take the freeze-free playback as one of the constraint as well. Since the formulated resource allocation and SVC layer selection problem is NP-hard, we propose the Resource Allocation and Layer Selection with Base layer guarantee (RALSB) algorithm to solve this problem in two phases: the Base layer Guarantee (BG) phase, and the Resource allocation and SVC layer selection (RS) phase. Simulation results show that the proposed RALSB can prevent/reduce the playback freeze in typical scenarios.
{"title":"SVC-based video streaming over highway vehicular networks with base layer guarantee","authors":"Ruijian An, Zhi Liu, Yusheng Ji","doi":"10.23919/INM.2017.7987456","DOIUrl":"https://doi.org/10.23919/INM.2017.7987456","url":null,"abstract":"In this paper, we target the resource allocation and layer selection problem for the realtime video streaming over highway scenario, by employing Scalable Video Coding (SVC) for the video contents. Especially, we take the freeze-free playback as one of the constraint as well. Since the formulated resource allocation and SVC layer selection problem is NP-hard, we propose the Resource Allocation and Layer Selection with Base layer guarantee (RALSB) algorithm to solve this problem in two phases: the Base layer Guarantee (BG) phase, and the Resource allocation and SVC layer selection (RS) phase. Simulation results show that the proposed RALSB can prevent/reduce the playback freeze in typical scenarios.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133553145","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 : 2017-05-01DOI: 10.23919/INM.2017.7987302
Nasim Beigi Mohammadi, Hamzeh Khazaei, Mark Shtern, C. Barna, Marin Litoiu
This paper presents an adaptive service management mechanism that maintains service level agreement through use of overlay networks that are deployed over the cloud provider network. The application autonomic manager strives to maintain the SLA without provisioning new resources for as long as possible. Through continuous monitoring and analysis, autonomic manager uses software defined networking (SDN) to dynamically apply policies to the flows of requests that travel through the application components. We implement and evaluate the proposed method on a hybrid cloud environment. Through extensive experiments, we show that the management mechanism can successfully maintain the SLA of services while it avoids provisioning extra resources which is the common approach in cloud.
{"title":"Adaptive service management for cloud applications using overlay networks","authors":"Nasim Beigi Mohammadi, Hamzeh Khazaei, Mark Shtern, C. Barna, Marin Litoiu","doi":"10.23919/INM.2017.7987302","DOIUrl":"https://doi.org/10.23919/INM.2017.7987302","url":null,"abstract":"This paper presents an adaptive service management mechanism that maintains service level agreement through use of overlay networks that are deployed over the cloud provider network. The application autonomic manager strives to maintain the SLA without provisioning new resources for as long as possible. Through continuous monitoring and analysis, autonomic manager uses software defined networking (SDN) to dynamically apply policies to the flows of requests that travel through the application components. We implement and evaluate the proposed method on a hybrid cloud environment. Through extensive experiments, we show that the management mechanism can successfully maintain the SLA of services while it avoids provisioning extra resources which is the common approach in cloud.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133575126","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 : 2017-05-01DOI: 10.23919/INM.2017.7987448
Eric Falk, R. Camino, R. State, V. Gurbani
The wireless/cellular communications network is composed of a complex set of interconnected computation units that form the mobile core network. The mobile core network is engineered to be fault tolerant and redundant; small errors that manifest themselves in the network are usually resolved automatically. However, some errors remain latent, and if discovered early enough can provide warnings to the network operator about a pending service outage. For mobile network operators, it is of high interest to detect these minor anomalies near real-time. In this work we use performance data from a 4G-LTE network carrier to train two parameter-free models. A first model relies on isolation forests, and the second is histogram based. The trained models represent the data characteristics for normal periods; new data is matched against the trained models to classify the new time period as being normal or abnormal. We show that the proposed methods can gauge the mobile network state with more subtlety than standard success/failure thresholds used in real-world networks today.
{"title":"On non-parametric models for detecting outages in the mobile network","authors":"Eric Falk, R. Camino, R. State, V. Gurbani","doi":"10.23919/INM.2017.7987448","DOIUrl":"https://doi.org/10.23919/INM.2017.7987448","url":null,"abstract":"The wireless/cellular communications network is composed of a complex set of interconnected computation units that form the mobile core network. The mobile core network is engineered to be fault tolerant and redundant; small errors that manifest themselves in the network are usually resolved automatically. However, some errors remain latent, and if discovered early enough can provide warnings to the network operator about a pending service outage. For mobile network operators, it is of high interest to detect these minor anomalies near real-time. In this work we use performance data from a 4G-LTE network carrier to train two parameter-free models. A first model relies on isolation forests, and the second is histogram based. The trained models represent the data characteristics for normal periods; new data is matched against the trained models to classify the new time period as being normal or abnormal. We show that the proposed methods can gauge the mobile network state with more subtlety than standard success/failure thresholds used in real-world networks today.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130808630","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 : 2017-05-01DOI: 10.23919/INM.2017.7987295
Mouhamad Dieye, M. Zhani, H. Elbiaze
In the era of Big data, cloud storage services have become the option of choice to store and share data thanks to their cost-effectiveness and seemingly limitless capacity. The increasing success of these services is driving cloud providers to further improve their storage management systems in order to offer more stringent guarantees on data availability and access time. However, despite recent efforts towards this goal, existing solutions have largely overlooked the heterogeneity of the workloads and the underlying storage components in terms of failure rates, capacity and I/O speed. To fill this gap, we present in this paper a heterogeneity-aware data management scheme (dubbed Heron) based on a genetic algorithm that takes into consideration disk heterogeneity to satisfy SLA requirements in terms of access time and availability and minimizes costs in terms of data migration, storage and energy consumption. Through realistic simulations, we show that Heron significantly improves data availability and access time and ensures minimal storage costs and data migration overhead compared to heterogeneity-oblivious solutions.
{"title":"On achieving high data availability in heterogeneous cloud storage systems","authors":"Mouhamad Dieye, M. Zhani, H. Elbiaze","doi":"10.23919/INM.2017.7987295","DOIUrl":"https://doi.org/10.23919/INM.2017.7987295","url":null,"abstract":"In the era of Big data, cloud storage services have become the option of choice to store and share data thanks to their cost-effectiveness and seemingly limitless capacity. The increasing success of these services is driving cloud providers to further improve their storage management systems in order to offer more stringent guarantees on data availability and access time. However, despite recent efforts towards this goal, existing solutions have largely overlooked the heterogeneity of the workloads and the underlying storage components in terms of failure rates, capacity and I/O speed. To fill this gap, we present in this paper a heterogeneity-aware data management scheme (dubbed Heron) based on a genetic algorithm that takes into consideration disk heterogeneity to satisfy SLA requirements in terms of access time and availability and minimizes costs in terms of data migration, storage and energy consumption. Through realistic simulations, we show that Heron significantly improves data availability and access time and ensures minimal storage costs and data migration overhead compared to heterogeneity-oblivious solutions.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134034530","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 : 2017-05-01DOI: 10.23919/INM.2017.7987271
S. R. Chowdhury, Reaz Ahmed, Nashid Shahriar, Aimal Khan, R. Boutaba, J. Mitra, L. Liu
Perceived as a key enabling technology for the future Internet, Network Virtualization (NV) allows an Infrastructure Provider (InP) to better utilize their Substrate Network (SN) by provisioning multiple Virtual Networks (VNs) from different Service Providers (SPs). A key challenge in NV is to efficiently map the VN requests from SPs on an SN, known as the Virtual Network Embedding (VNE) problem. VNE algorithms are typically online in nature. A VN embedding can become suboptimal over time due to the arrival and departure of other VNs as well as due to changes in SN such as failures. One way to mitigate the impact of such dynamism is to periodically reallocate resources for the existing VNs. VNE reallocation can increase an InP's revenue by decreasing bandwidth consumption and by increasing the possibility of accepting future VNs. In this paper, we study Reallocation of Virtual Network Embedding (ReViNE) problem to minimize the number of over utilized substrate links and total bandwidth cost on the SN. We propose an Integer Linear Programming formulation for the optimal solution (ReViNE-OPT) and a simulated annealing based heuristic (ReViNE-FAST) to solve larger problem instances. Simulation results show that on average our proposed heuristic performs within ∼19% of the optimal solution. Moreover, ReViNE-FAST generates more than 2.5× better solutions compared to the state-of-the-art simulated annealing based heuristic for VNE reallocation.
{"title":"ReViNE: Reallocation of Virtual Network Embedding to eliminate substrate bottlenecks","authors":"S. R. Chowdhury, Reaz Ahmed, Nashid Shahriar, Aimal Khan, R. Boutaba, J. Mitra, L. Liu","doi":"10.23919/INM.2017.7987271","DOIUrl":"https://doi.org/10.23919/INM.2017.7987271","url":null,"abstract":"Perceived as a key enabling technology for the future Internet, Network Virtualization (NV) allows an Infrastructure Provider (InP) to better utilize their Substrate Network (SN) by provisioning multiple Virtual Networks (VNs) from different Service Providers (SPs). A key challenge in NV is to efficiently map the VN requests from SPs on an SN, known as the Virtual Network Embedding (VNE) problem. VNE algorithms are typically online in nature. A VN embedding can become suboptimal over time due to the arrival and departure of other VNs as well as due to changes in SN such as failures. One way to mitigate the impact of such dynamism is to periodically reallocate resources for the existing VNs. VNE reallocation can increase an InP's revenue by decreasing bandwidth consumption and by increasing the possibility of accepting future VNs. In this paper, we study Reallocation of Virtual Network Embedding (ReViNE) problem to minimize the number of over utilized substrate links and total bandwidth cost on the SN. We propose an Integer Linear Programming formulation for the optimal solution (ReViNE-OPT) and a simulated annealing based heuristic (ReViNE-FAST) to solve larger problem instances. Simulation results show that on average our proposed heuristic performs within ∼19% of the optimal solution. Moreover, ReViNE-FAST generates more than 2.5× better solutions compared to the state-of-the-art simulated annealing based heuristic for VNE reallocation.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132285051","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 : 2017-05-01DOI: 10.23919/INM.2017.7987258
Song Yang, P. Wieder, M. Aziz, R. Yahyapour, Xiaoming Fu
Customers often suffer from the variability of data access time in cloud storage service, caused by network congestion, load dynamics, etc. One solution to guarantee a reliable latency-sensitive service is to issue requests with multiple download/upload sessions, accessing the required data (replicas) stored in one or more servers. In order to minimize storage costs, how to optimally allocate data in a minimum number of servers without violating latency guarantees remains to be a crucial issue for the cloud provider to tackle. In this paper, we study the latency-sensitive data allocation problem for cloud storage. We model the data access time as a given distribution whose Cumulative Density Function (CDF) is known, and prove that this problem is NP-hard. To solve it, we propose both exact Integer Nonlinear Program (INLP) and Tabu Search-based heuristic. The proposed algorithms are evaluated in terms of the number of used servers, storage utilization and throughput utilization.
{"title":"Latency-Sensitive Data Allocation for cloud storage","authors":"Song Yang, P. Wieder, M. Aziz, R. Yahyapour, Xiaoming Fu","doi":"10.23919/INM.2017.7987258","DOIUrl":"https://doi.org/10.23919/INM.2017.7987258","url":null,"abstract":"Customers often suffer from the variability of data access time in cloud storage service, caused by network congestion, load dynamics, etc. One solution to guarantee a reliable latency-sensitive service is to issue requests with multiple download/upload sessions, accessing the required data (replicas) stored in one or more servers. In order to minimize storage costs, how to optimally allocate data in a minimum number of servers without violating latency guarantees remains to be a crucial issue for the cloud provider to tackle. In this paper, we study the latency-sensitive data allocation problem for cloud storage. We model the data access time as a given distribution whose Cumulative Density Function (CDF) is known, and prove that this problem is NP-hard. To solve it, we propose both exact Integer Nonlinear Program (INLP) and Tabu Search-based heuristic. The proposed algorithms are evaluated in terms of the number of used servers, storage utilization and throughput utilization.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122871271","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 : 2017-05-01DOI: 10.23919/INM.2017.7987402
Antonio Marsico, R. D. Corin, D. Siracusa
In extremely connected and dynamic environments, such as data centers, SDN network devices can be exploited to simplify the management of network provisioning. However, they leverage on TCAMs to implement the flow tables, i.e., on size-limited memories that can be quickly filled up when fine-grained traffic control is required, eventually preventing the installation of new forwarding rules. In this work, we demonstrate how this issue can be mitigated by means of a novel flow rule swapping mechanism. Specifically, we first show the negative effects of a full TCAM on a video streaming service provided by an SDN-enabled data center. Then, we show that our swapping mechanism helps in overcoming the inability to properly access a media content available in the data center, by temporarily moving the least matched flow rules from the TCAM to a larger memory outside the SDN device.
{"title":"Overcoming the memory limits of network devices in SDN-enabled data centers","authors":"Antonio Marsico, R. D. Corin, D. Siracusa","doi":"10.23919/INM.2017.7987402","DOIUrl":"https://doi.org/10.23919/INM.2017.7987402","url":null,"abstract":"In extremely connected and dynamic environments, such as data centers, SDN network devices can be exploited to simplify the management of network provisioning. However, they leverage on TCAMs to implement the flow tables, i.e., on size-limited memories that can be quickly filled up when fine-grained traffic control is required, eventually preventing the installation of new forwarding rules. In this work, we demonstrate how this issue can be mitigated by means of a novel flow rule swapping mechanism. Specifically, we first show the negative effects of a full TCAM on a video streaming service provided by an SDN-enabled data center. Then, we show that our swapping mechanism helps in overcoming the inability to properly access a media content available in the data center, by temporarily moving the least matched flow rules from the TCAM to a larger memory outside the SDN device.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123958979","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 : 2017-05-01DOI: 10.23919/INM.2017.7987465
Radhika Loomba, Lei Shi, B. Jennings
The myriad of sensor information that can be collected using smartphones, wearables and other IoT devices greatly benefits context-aware applications. These applications rely heavily on mobile devices, present in locations of interest, to offload raw or processed sensor data in order to accurately capture, recognize and classify the surrounding real-time context. However, continuous sensing and offloading of large volumes of mainly redundant sensor data significantly impacts energy-constrained mobile devices. This results in a trade-off between sensing accuracy and the energy consumed by these devices. We propose the use of application-specific state machines that encode the context of interest to determine when sensed data should be offloaded to the cloud. Our control algorithm, ‘Assisted-Aggregation’ applies frequent pattern mining to reduce the number of active devices by sharing sensed data between multiple applications. Our evaluation shows an improvement in terms of the residual energy of the mobile devices, the number of devices actively offloading and the volume of the offloaded data.
{"title":"State-machine driven collaborative mobile sensing serving multiple Internet-of-Things applications","authors":"Radhika Loomba, Lei Shi, B. Jennings","doi":"10.23919/INM.2017.7987465","DOIUrl":"https://doi.org/10.23919/INM.2017.7987465","url":null,"abstract":"The myriad of sensor information that can be collected using smartphones, wearables and other IoT devices greatly benefits context-aware applications. These applications rely heavily on mobile devices, present in locations of interest, to offload raw or processed sensor data in order to accurately capture, recognize and classify the surrounding real-time context. However, continuous sensing and offloading of large volumes of mainly redundant sensor data significantly impacts energy-constrained mobile devices. This results in a trade-off between sensing accuracy and the energy consumed by these devices. We propose the use of application-specific state machines that encode the context of interest to determine when sensed data should be offloaded to the cloud. Our control algorithm, ‘Assisted-Aggregation’ applies frequent pattern mining to reduce the number of active devices by sharing sensed data between multiple applications. Our evaluation shows an improvement in terms of the residual energy of the mobile devices, the number of devices actively offloading and the volume of the offloaded data.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127841458","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 : 2017-05-01DOI: 10.23919/INM.2017.7987325
Michael Coughlin, Kelly Kaoudis, Eric Keller
Despite the benefits of decentralized applications in terms of resilience and privacy, the overwhelming majority of applications with mainstream adoption are provided in a centralized manner. We argue that this is due to the direct benefits to the developer that centralization provides in terms of performance, monetization, and deployability. In this paper we introduce a new model, untrusted delegation, which joins the simplified deployment model of centralization with the benefits of decentralization. In this model, we decouple administrative ownership from administrative management, and leverage the existence of either a private cloud infrastructure, or a public cloud provider that acts as a neutral third party, that is augmented to support decentralization. Our initial prototype integrates with the Digital Ocean API and as a proof-of-concept, we can deploy Tor relay nodes with users only needing to sign up for a Digital Ocean account.
{"title":"Augmenting cloud architectures to support decentralized applications","authors":"Michael Coughlin, Kelly Kaoudis, Eric Keller","doi":"10.23919/INM.2017.7987325","DOIUrl":"https://doi.org/10.23919/INM.2017.7987325","url":null,"abstract":"Despite the benefits of decentralized applications in terms of resilience and privacy, the overwhelming majority of applications with mainstream adoption are provided in a centralized manner. We argue that this is due to the direct benefits to the developer that centralization provides in terms of performance, monetization, and deployability. In this paper we introduce a new model, untrusted delegation, which joins the simplified deployment model of centralization with the benefits of decentralization. In this model, we decouple administrative ownership from administrative management, and leverage the existence of either a private cloud infrastructure, or a public cloud provider that acts as a neutral third party, that is augmented to support decentralization. Our initial prototype integrates with the Digital Ocean API and as a proof-of-concept, we can deploy Tor relay nodes with users only needing to sign up for a Digital Ocean account.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121435650","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 : 2017-05-01DOI: 10.23919/INM.2017.7987283
Yona Lopes, N. Fernandes, D. Muchaluat-Saade, K. Obraczka
In smart grids, the broad use of Distributed Energy Resources (DERs) in distribution networks introduces the need for protective relaying schemes similar to those used in high-voltage networks. The introduction of intermittent DERs, as solar panels, also requires more autonomic and dynamic SCADA networks. Hence, power systems experience an increased demand for resilience in the distribution communication network. However, resilience methods currently in use still cannot meet those protection requirements. This work proposes ARES, a framework for autonomic and resilient communication for smart grids. ARES provides resilient, robust, and flexible communication for smart grids with Software Defined Network (SDN). Our proposal also provides autonomic services for SCADA that can improve smart grid application performance and efficiency. ARES fault resilience module is implemented and tested using Mininet 2.2.1 and RYU controller and presents maximum recovery time of 610 microseconds, which is an important advance compared to other proposals. In addition, ARES is transparent to end devices, keeping compatibility with legacy measurement and actuation devices.
{"title":"ARES: An autonomic and resilient framework for smart grids","authors":"Yona Lopes, N. Fernandes, D. Muchaluat-Saade, K. Obraczka","doi":"10.23919/INM.2017.7987283","DOIUrl":"https://doi.org/10.23919/INM.2017.7987283","url":null,"abstract":"In smart grids, the broad use of Distributed Energy Resources (DERs) in distribution networks introduces the need for protective relaying schemes similar to those used in high-voltage networks. The introduction of intermittent DERs, as solar panels, also requires more autonomic and dynamic SCADA networks. Hence, power systems experience an increased demand for resilience in the distribution communication network. However, resilience methods currently in use still cannot meet those protection requirements. This work proposes ARES, a framework for autonomic and resilient communication for smart grids. ARES provides resilient, robust, and flexible communication for smart grids with Software Defined Network (SDN). Our proposal also provides autonomic services for SCADA that can improve smart grid application performance and efficiency. ARES fault resilience module is implemented and tested using Mininet 2.2.1 and RYU controller and presents maximum recovery time of 610 microseconds, which is an important advance compared to other proposals. In addition, ARES is transparent to end devices, keeping compatibility with legacy measurement and actuation devices.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"24 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115954156","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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