Pub Date : 2017-05-01DOI: 10.23919/INM.2017.7987403
A. Jacobs, R. Santos, M. Franco, E. Scheid, R. Pfitscher, L. Granville
AMNESiA is an affinity measurement platform for NFV-enabled networks, designed to consolidate and interpret existing monitoring data into an affinity metric, aiding operators to identify affinity and anti-affinity relations in the network. AMNESiA uses the latest snapshot of usage data, collected through a generic monitoring solution, from the database to measure affinity between VNFs.
{"title":"AMNESiA: Affinity measurement platform for NFV-enabled networks","authors":"A. Jacobs, R. Santos, M. Franco, E. Scheid, R. Pfitscher, L. Granville","doi":"10.23919/INM.2017.7987403","DOIUrl":"https://doi.org/10.23919/INM.2017.7987403","url":null,"abstract":"AMNESiA is an affinity measurement platform for NFV-enabled networks, designed to consolidate and interpret existing monitoring data into an affinity metric, aiding operators to identify affinity and anti-affinity relations in the network. AMNESiA uses the latest snapshot of usage data, collected through a generic monitoring solution, from the database to measure affinity between VNFs.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"74 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":"127346344","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.2017.7987348
Tareq Hayajna, Miochdel Kaldoching
To increase mobile ad hoc network reliability, virtually decrease the packets loss to zero, and to support multimedia communications multi-route is required. In order to ensure the availability of two routes, node density must be above a certain value. To the best our knowledge, this paper is the first paper that mathematically determines the required node density to ensure the availability of two routes between any randomly chosen source and destination pair in mobile ad hoc networks with random waypoint mobility model. To this end, a complete probabilistic model is provided. The obtained results reveal that the increase in the node density exponentially increases the probability of having two routes. This exponential increase is limited by a certain threshold, after this threshold the increase is negligible. An interesting conclusion from this paper is that the required node densities to ensure two routes connectivity are the same for both mobile nodes moving according to the generalized random waypoint mobility model and static nodes that are uniformly distributed in the network area. This work can be used by mobile ad hoc network designers to study the network reliability and connectivity.
{"title":"Ensuring two routes connectivity in mobile ad hoc networks with Random Waypoint mobility","authors":"Tareq Hayajna, Miochdel Kaldoching","doi":"10.23919/INM.2017.7987348","DOIUrl":"https://doi.org/10.23919/INM.2017.7987348","url":null,"abstract":"To increase mobile ad hoc network reliability, virtually decrease the packets loss to zero, and to support multimedia communications multi-route is required. In order to ensure the availability of two routes, node density must be above a certain value. To the best our knowledge, this paper is the first paper that mathematically determines the required node density to ensure the availability of two routes between any randomly chosen source and destination pair in mobile ad hoc networks with random waypoint mobility model. To this end, a complete probabilistic model is provided. The obtained results reveal that the increase in the node density exponentially increases the probability of having two routes. This exponential increase is limited by a certain threshold, after this threshold the increase is negligible. An interesting conclusion from this paper is that the required node densities to ensure two routes connectivity are the same for both mobile nodes moving according to the generalized random waypoint mobility model and static nodes that are uniformly distributed in the network area. This work can be used by mobile ad hoc network designers to study the network reliability and connectivity.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"39 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":"122858656","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.2017.7987319
Binh Nguyen, Nakjung Choi, M. Thottan, J. Merwe
In future mobile networks, e.g., 5G, emerging IoT services are expected to support billions of IoT devices with unique characteristics and traffic patterns. In this paper we propose an SDN-based IoT Mobile Edge Cloud Architecture (SIMECA1) which can deploy diverse IoT services at the mobile edge by leveraging distributed, lightweight control and data planes optimized for IoT communications. We prototyped our architecture using a pre-commercial mobile networking software stack to demonstrate the feasibility and utility of our approach.
{"title":"SIMECA: SDN-based IoT Mobile Edge Cloud Architecture","authors":"Binh Nguyen, Nakjung Choi, M. Thottan, J. Merwe","doi":"10.23919/INM.2017.7987319","DOIUrl":"https://doi.org/10.23919/INM.2017.7987319","url":null,"abstract":"In future mobile networks, e.g., 5G, emerging IoT services are expected to support billions of IoT devices with unique characteristics and traffic patterns. In this paper we propose an SDN-based IoT Mobile Edge Cloud Architecture (SIMECA1) which can deploy diverse IoT services at the mobile edge by leveraging distributed, lightweight control and data planes optimized for IoT communications. We prototyped our architecture using a pre-commercial mobile networking software stack to demonstrate the feasibility and utility of our approach.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"11 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":"123097901","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.2017.7987324
Satadal Sengupta, V. Yadav, Yash Saraf, Harshit Gupta, Niloy Ganguly, Sandip Chakraborty, Pradipta De
Among the mobile applications contributing to the surging Internet traffic, video applications are some of the biggest contributors. Most of these video applications use HTTP/HTTPS tunneling making it difficult to apply port based or packet data based identification of flows. This makes it challenging for network operators to enforce bandwidth regulation policies for app based service differentiation due to lack of flow identification mechanisms for mobile apps. We explore a packet data agnostic feature of video flows, namely packet-size, to identify the flows. We show that it is possible to train a classifier that can distinguish packets from streaming and interactive video apps with high accuracy. We design and implement a system, called MoViDiff, with this classifier at the core, that allows bandwidth regulation between video traffic of two different categories, streaming and interactive. We show that we can achieve an average accuracy of 96% in classifying the traffic, with the maximum accuracy reaching as high as 98%.
{"title":"MoViDiff: Enabling service differentiation for mobile video apps","authors":"Satadal Sengupta, V. Yadav, Yash Saraf, Harshit Gupta, Niloy Ganguly, Sandip Chakraborty, Pradipta De","doi":"10.23919/INM.2017.7987324","DOIUrl":"https://doi.org/10.23919/INM.2017.7987324","url":null,"abstract":"Among the mobile applications contributing to the surging Internet traffic, video applications are some of the biggest contributors. Most of these video applications use HTTP/HTTPS tunneling making it difficult to apply port based or packet data based identification of flows. This makes it challenging for network operators to enforce bandwidth regulation policies for app based service differentiation due to lack of flow identification mechanisms for mobile apps. We explore a packet data agnostic feature of video flows, namely packet-size, to identify the flows. We show that it is possible to train a classifier that can distinguish packets from streaming and interactive video apps with high accuracy. We design and implement a system, called MoViDiff, with this classifier at the core, that allows bandwidth regulation between video traffic of two different categories, streaming and interactive. We show that we can achieve an average accuracy of 96% in classifying the traffic, with the maximum accuracy reaching as high as 98%.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"72 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":"126806225","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.2017.7987258
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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