Pub Date : 2016-04-25DOI: 10.1109/NOMS.2016.7502923
B. Karaçali, J. Tracey
Growth in cloud computing motivates cloud networks that provide excellent performance and scalability. Improvements rely on the ability to measure these characteristics. Measurement is complicated by a combinatorial explosion of implementations, configurations, metrics, workloads and scenarios. We present tools and a framework that facilitate performance and scalability evaluation. We present the results of applying the framework to six OpenStack network implementations/configurations. The results validate the framework's ability to highlight the performance and scalability impact of changes to the underlying cloud implementation and configuration. Our experience also yields important lessons regarding cloud network evaluation.
{"title":"Experiences evaluating OpenStack network data plane performance and scalability","authors":"B. Karaçali, J. Tracey","doi":"10.1109/NOMS.2016.7502923","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502923","url":null,"abstract":"Growth in cloud computing motivates cloud networks that provide excellent performance and scalability. Improvements rely on the ability to measure these characteristics. Measurement is complicated by a combinatorial explosion of implementations, configurations, metrics, workloads and scenarios. We present tools and a framework that facilitate performance and scalability evaluation. We present the results of applying the framework to six OpenStack network implementations/configurations. The results validate the framework's ability to highlight the performance and scalability impact of changes to the underlying cloud implementation and configuration. Our experience also yields important lessons regarding cloud network evaluation.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121903255","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502804
Vahid Aghaei-Foroushani, A. Zincir-Heywood
Tracing IP packets to their sources, known as IP-Traceback, is a critical task in defending against IP spoofing and DoS attacks. There are several solutions to traceback to the origin of the attack. However, all these solutions require either all routers or ISPs to support the same IP-Traceback mechanism. To address this limitation, we propose an IP-Traceback approach at the level of autonomous systems, called Autonomous System-based Flow Marking, ASFM, to identify some key locations in the path where attacker packets are being forwarded. ASFM employs the BGP update message community attribute that enables information to be passed across ASs even if they are not necessarily involved in the IP-Traceback scheme. We also propose an authentication method, so a downstream AS can examine the correctness of the marking provided by the upstream ASs, thus eliminating the fake marking embedded by subverted routers. Finally, we evaluate and analyze the performance of our proposal, using real life datasets.
{"title":"Autonomous system based flow marking scheme for IP-Traceback","authors":"Vahid Aghaei-Foroushani, A. Zincir-Heywood","doi":"10.1109/NOMS.2016.7502804","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502804","url":null,"abstract":"Tracing IP packets to their sources, known as IP-Traceback, is a critical task in defending against IP spoofing and DoS attacks. There are several solutions to traceback to the origin of the attack. However, all these solutions require either all routers or ISPs to support the same IP-Traceback mechanism. To address this limitation, we propose an IP-Traceback approach at the level of autonomous systems, called Autonomous System-based Flow Marking, ASFM, to identify some key locations in the path where attacker packets are being forwarded. ASFM employs the BGP update message community attribute that enables information to be passed across ASs even if they are not necessarily involved in the IP-Traceback scheme. We also propose an authentication method, so a downstream AS can examine the correctness of the marking provided by the upstream ASs, thus eliminating the fake marking embedded by subverted routers. Finally, we evaluate and analyze the performance of our proposal, using real life datasets.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122145263","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502871
A. M. Ghaleb, Tarek Khalifa, Sara Ayoubi, K. Shaban
Virtual network embedding (VNE) is defined as the allocation of network resources to multiple virtual networks (VNs) and is recognized to be a challenging task to perform efficiently. Virtual network survivability is a new term that describes the measures taken to provide a failure-proof VN against physical link and/or node failure. Indeed, a single link or node failure in a substrate network can bring down multiple hosted VNs, i.e., the ones that utilize that failed link or node. As such, virtual network survivability becomes an essential part of VNE. While much work has been dedicated to studying the impact of a variety of failure cases in a VN, little attention has been directed towards studying the link failure impact on multicast virtual network (MVN) applications, which principally restrict end-to-end delay and delay variation measures. In fact, most of the introduced survivability schemes adopt protection techniques by reserving backup resources prior to embedding, which inevitably leads to under-utilization of the network resources. In this paper, we first investigate the impact of physical link failure on MVNs. Then, we introduce a novel recovery approach to restore MVNs while considering their end-delay and delay variation requirements. Simulation experiments prove that our recovery technique achieves good restoration ratio in considerably fast execution time and low link mapping cost with little impact on the admittance ratio.
{"title":"Surviving link failures in multicast VN embedded applications","authors":"A. M. Ghaleb, Tarek Khalifa, Sara Ayoubi, K. Shaban","doi":"10.1109/NOMS.2016.7502871","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502871","url":null,"abstract":"Virtual network embedding (VNE) is defined as the allocation of network resources to multiple virtual networks (VNs) and is recognized to be a challenging task to perform efficiently. Virtual network survivability is a new term that describes the measures taken to provide a failure-proof VN against physical link and/or node failure. Indeed, a single link or node failure in a substrate network can bring down multiple hosted VNs, i.e., the ones that utilize that failed link or node. As such, virtual network survivability becomes an essential part of VNE. While much work has been dedicated to studying the impact of a variety of failure cases in a VN, little attention has been directed towards studying the link failure impact on multicast virtual network (MVN) applications, which principally restrict end-to-end delay and delay variation measures. In fact, most of the introduced survivability schemes adopt protection techniques by reserving backup resources prior to embedding, which inevitably leads to under-utilization of the network resources. In this paper, we first investigate the impact of physical link failure on MVNs. Then, we introduce a novel recovery approach to restore MVNs while considering their end-delay and delay variation requirements. Simulation experiments prove that our recovery technique achieves good restoration ratio in considerably fast execution time and low link mapping cost with little impact on the admittance ratio.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131791586","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502873
Chuan Pham, Nguyen H. Tran, Minh N. H. Nguyen, Shaolei Ren, W. Saad, C. Hong
In this paper, the problem of resource allocation in cloud datacenters, that own highly complex and heterogeneous tasks and servers, is considered. To address this problem, a novel framework, dubbed joint operation cost and network traffic cost (JOT) framework, is proposed. This framework combines notions from Gibbs sampling and matching theory to find an efficient solution addressing the NP-hard problem JOT. The proposed model is shown to be capable of controlling the active server set, in a coordinated manner while allocating VMs in order to reduce both operation cost and network traffic cost of the cloud datacenter. We also conduct a case-study to validate our proposed algorithm and the results show that JOT can reduce the total incurred cost by up to 19% compared to the existing non-coordinated approach.
{"title":"Hosting virtual machines on a cloud datacenter: A matching theoretic approach","authors":"Chuan Pham, Nguyen H. Tran, Minh N. H. Nguyen, Shaolei Ren, W. Saad, C. Hong","doi":"10.1109/NOMS.2016.7502873","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502873","url":null,"abstract":"In this paper, the problem of resource allocation in cloud datacenters, that own highly complex and heterogeneous tasks and servers, is considered. To address this problem, a novel framework, dubbed joint operation cost and network traffic cost (JOT) framework, is proposed. This framework combines notions from Gibbs sampling and matching theory to find an efficient solution addressing the NP-hard problem JOT. The proposed model is shown to be capable of controlling the active server set, in a coordinated manner while allocating VMs in order to reduce both operation cost and network traffic cost of the cloud datacenter. We also conduct a case-study to validate our proposed algorithm and the results show that JOT can reduce the total incurred cost by up to 19% compared to the existing non-coordinated approach.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116201937","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502829
S. Zhang, A. Tizghadam, Byungchul Park, H. Bannazadeh, A. Leon-Garcia
Network function visualization (NFV) has emerged as a promising paradigm in networking, where the hardware-based middleboxes are replaced with software-based virtualized entities typically running on the cloud to provide specific functionalities. By deploying NFV, network services become more adaptive and cost-effective. Many multicast services such as real-time multimedia streaming and intrusion detection require appropriate services chaining; however, NFVs placement in the network as well as traffic routing strategy to guarantee that the multicast flows traverse through the services chain before reaching the end user is still an open problem. In this paper, we present an algorithm to solve this problem.
{"title":"Joint NFV placement and routing for multicast service on SDN","authors":"S. Zhang, A. Tizghadam, Byungchul Park, H. Bannazadeh, A. Leon-Garcia","doi":"10.1109/NOMS.2016.7502829","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502829","url":null,"abstract":"Network function visualization (NFV) has emerged as a promising paradigm in networking, where the hardware-based middleboxes are replaced with software-based virtualized entities typically running on the cloud to provide specific functionalities. By deploying NFV, network services become more adaptive and cost-effective. Many multicast services such as real-time multimedia streaming and intrusion detection require appropriate services chaining; however, NFVs placement in the network as well as traffic routing strategy to guarantee that the multicast flows traverse through the services chain before reaching the end user is still an open problem. In this paper, we present an algorithm to solve this problem.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116246583","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502995
R. Ghannam, Anthony Chung
Traffic flowing through a software defined network is vulnerable to disruptions caused by malicious switches. The malicious behaviors are diverse such as dropping traffic, adding traffic or modifying it. A switch could be malicious or otherwise dysfunctional or misconfigured. A lot of work in SDN has addressed the problem by securing the control plane and having it validate network wide properties and policy compliance, e.g., loop-freedom, reachability and resolution of conflicting rules. In this paper, we argue that it is imperative as well to ensure the correctness of traffic forwarding itself. Therefore we define a threat model for the security and correctness of forwarding in an SDN switch. We describe several malicious behaviors that could be encountered at an SDN switch and propose possible solutions to each fault type. The capabilities of the SDN paradigm to detect and deter such attacks are analyzed.
{"title":"Handling malicious switches in software defined networks","authors":"R. Ghannam, Anthony Chung","doi":"10.1109/NOMS.2016.7502995","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502995","url":null,"abstract":"Traffic flowing through a software defined network is vulnerable to disruptions caused by malicious switches. The malicious behaviors are diverse such as dropping traffic, adding traffic or modifying it. A switch could be malicious or otherwise dysfunctional or misconfigured. A lot of work in SDN has addressed the problem by securing the control plane and having it validate network wide properties and policy compliance, e.g., loop-freedom, reachability and resolution of conflicting rules. In this paper, we argue that it is imperative as well to ensure the correctness of traffic forwarding itself. Therefore we define a threat model for the security and correctness of forwarding in an SDN switch. We describe several malicious behaviors that could be encountered at an SDN switch and propose possible solutions to each fault type. The capabilities of the SDN paradigm to detect and deter such attacks are analyzed.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132229472","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502958
V. Bumgardner, V. Marek, Ray L. Hyatt
Through the collection and association of discrete time-series resource metrics and workloads, we can both provide benchmark and intra-job resource collations, along with system-wide job profiling. Traditional RDBMSes are not designed to store and process long-term discrete time-series metrics and the commonly used resolution-reducing round robin databases (RRDB), make poor long-term sources of data for workload analytics. We implemented a system that employs “Big-data” (Hadoop/HBase) and other analytics (R) techniques and tools to store, process, and characterize HPC workloads. Using this system we have collected and processed over a 30 billion time-series metrics from existing short-term high-resolution (15-sec RRDB) sources, profiling over 200 thousand jobs across a wide spectrum of workloads. The system is currently in use at the University of Kentucky for better understanding of individual jobs and system-wide profiling as well as a strategic source of data for resource allocation and future acquisitions.
{"title":"Collating time-series resource data for system-wide job profiling","authors":"V. Bumgardner, V. Marek, Ray L. Hyatt","doi":"10.1109/NOMS.2016.7502958","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502958","url":null,"abstract":"Through the collection and association of discrete time-series resource metrics and workloads, we can both provide benchmark and intra-job resource collations, along with system-wide job profiling. Traditional RDBMSes are not designed to store and process long-term discrete time-series metrics and the commonly used resolution-reducing round robin databases (RRDB), make poor long-term sources of data for workload analytics. We implemented a system that employs “Big-data” (Hadoop/HBase) and other analytics (R) techniques and tools to store, process, and characterize HPC workloads. Using this system we have collected and processed over a 30 billion time-series metrics from existing short-term high-resolution (15-sec RRDB) sources, profiling over 200 thousand jobs across a wide spectrum of workloads. The system is currently in use at the University of Kentucky for better understanding of individual jobs and system-wide profiling as well as a strategic source of data for resource allocation and future acquisitions.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132246009","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502806
T. Tsvetkov, Janne Ali-Tolppa, H. Sanneck, G. Carle
The verification of Configuration Management (CM) changes has become an important step in the operation of a mobile Self-Organizing Network (SON). Typically, a verification mechanism operates in three phases. At first, it partitions the network into verification areas, then it triggers an anomaly detection algorithm for those areas, and finally generates CM undo requests for the abnormally performing ones. Those requests set the CM parameters to a previous stable state. However, verification areas may overlap and share anomalous cells which results in a verification collision. As a consequence, the verification mechanism is not able to simultaneously deploy the undo requests since there is an uncertainty which to execute and which to potentially omit. In such a case, it has to serialize the deployment process and resolve the collisions. This procedure, though, can be negatively impacted if unnecessary collisions are processed, since they might delay the execution of the queued CM undo requests. To overcome this issue, we propose an approach for changing the size of the verification areas with respect to the detected collisions. We achieve our goal by using a Minimum Spanning Tree (MST)-based clustering approach that is able to group similarly behaving cells together. Based on the group they have been assigned to, we remove cells from a verification area and prevent false positive collisions from being further processed. Furthermore, we evaluate the proposed solution in two different scenarios. First, we highlight its benefits by applying it on CM and Performance Management (PM) data collected from a real Long Term Evolution (LTE) network. Second, in a simulation study we show how it positively affects the network performance after eliminating the false positives.
{"title":"A minimum spanning tree-based approach for reducing verification collisions in self-organizing networks","authors":"T. Tsvetkov, Janne Ali-Tolppa, H. Sanneck, G. Carle","doi":"10.1109/NOMS.2016.7502806","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502806","url":null,"abstract":"The verification of Configuration Management (CM) changes has become an important step in the operation of a mobile Self-Organizing Network (SON). Typically, a verification mechanism operates in three phases. At first, it partitions the network into verification areas, then it triggers an anomaly detection algorithm for those areas, and finally generates CM undo requests for the abnormally performing ones. Those requests set the CM parameters to a previous stable state. However, verification areas may overlap and share anomalous cells which results in a verification collision. As a consequence, the verification mechanism is not able to simultaneously deploy the undo requests since there is an uncertainty which to execute and which to potentially omit. In such a case, it has to serialize the deployment process and resolve the collisions. This procedure, though, can be negatively impacted if unnecessary collisions are processed, since they might delay the execution of the queued CM undo requests. To overcome this issue, we propose an approach for changing the size of the verification areas with respect to the detected collisions. We achieve our goal by using a Minimum Spanning Tree (MST)-based clustering approach that is able to group similarly behaving cells together. Based on the group they have been assigned to, we remove cells from a verification area and prevent false positive collisions from being further processed. Furthermore, we evaluate the proposed solution in two different scenarios. First, we highlight its benefits by applying it on CM and Performance Management (PM) data collected from a real Long Term Evolution (LTE) network. Second, in a simulation study we show how it positively affects the network performance after eliminating the false positives.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128223025","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502854
G. Geronimo, Rafael Brundo Uriarte, Carlos Becker Westphall
This paper presents the implementation and tests of a flexible and extensible framework, named Order@Cloud, that improves the Virtual Machine placements of a Cloud. It receives new VMs on the Cloud and organises them by relocating their placements based on the Multiple-Objectives of the environment. These Objectives are represented by Rules, Qualifiers and Costs, which can be easily added, extended and prioritised. Based on Evolutionary and Greedy Searches, Order@Cloud theoretically guarantees the adoption of a better set of Placements. More specifically, it seeks the non-dominated solutions (Pareto Set) and compares them considering the implementation cost of the scenario and its benefits. In contrast to existing solutions, that address specific objectives, our framework was devised to be objective-agnostic and easily extensible, which enables the implementation of new and generic prioritised elements. To understand the applicability and performance of our solution we conducted experiments using a real Cloud environment and discuss its performance, flexibility and optimality.
{"title":"Order@Cloud: A VM organisation framework based on multi-objectives placement ranking","authors":"G. Geronimo, Rafael Brundo Uriarte, Carlos Becker Westphall","doi":"10.1109/NOMS.2016.7502854","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502854","url":null,"abstract":"This paper presents the implementation and tests of a flexible and extensible framework, named Order@Cloud, that improves the Virtual Machine placements of a Cloud. It receives new VMs on the Cloud and organises them by relocating their placements based on the Multiple-Objectives of the environment. These Objectives are represented by Rules, Qualifiers and Costs, which can be easily added, extended and prioritised. Based on Evolutionary and Greedy Searches, Order@Cloud theoretically guarantees the adoption of a better set of Placements. More specifically, it seeks the non-dominated solutions (Pareto Set) and compares them considering the implementation cost of the scenario and its benefits. In contrast to existing solutions, that address specific objectives, our framework was devised to be objective-agnostic and easily extensible, which enables the implementation of new and generic prioritised elements. To understand the applicability and performance of our solution we conducted experiments using a real Cloud environment and discuss its performance, flexibility and optimality.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"528 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132907309","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 : 2016-04-25DOI: 10.1109/NOMS.2016.7502946
Antonio Marsico, R. D. Corin, M. Gerola, D. Siracusa, Arne Schwabe
The Memory Management Subsystem (MMS) provides automated services for SDN controllers that optimize the management of network devices' memory. Among other functions, it cleans the memory of network devices upon the update or the removal of SDN applications. The potential of this MMS function is demonstrated in a scenario where a critical security update for a network application would be otherwise ineffective.
{"title":"A non-disruptive automated approach to update SDN applications at runtime","authors":"Antonio Marsico, R. D. Corin, M. Gerola, D. Siracusa, Arne Schwabe","doi":"10.1109/NOMS.2016.7502946","DOIUrl":"https://doi.org/10.1109/NOMS.2016.7502946","url":null,"abstract":"The Memory Management Subsystem (MMS) provides automated services for SDN controllers that optimize the management of network devices' memory. Among other functions, it cleans the memory of network devices upon the update or the removal of SDN applications. The potential of this MMS function is demonstrated in a scenario where a critical security update for a network application would be otherwise ineffective.","PeriodicalId":344879,"journal":{"name":"NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133055682","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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