Pub Date : 2017-10-25DOI: 10.1109/JSAC.2017.2760162
Insun Jang, Dongeun Suh, Sangheon Pack, G. Dán
In this paper, we consider the problem of optimal dynamic service function (SF) placement and flow routing in a SF chaining (SFC) enabled network. We formulate a multi-objective optimization problem to maximize the acceptable flow rate and to minimize the energy cost for multiple service chains. We transform the multi-objective optimization problem into a single-objective mixed integer linear programming (MILP) problem, and prove that the problem is NP-hard. We propose a polynomial time algorithm based on linear relaxation and rounding to approximate the optimal solution of the MILP. Extensive simulations are conducted to evaluate the effects of the energy budget, the network topology, and the amount of server resources on the acceptable flow rate. The results demonstrate that the proposed algorithm can achieve near-optimal performance and can significantly increase the acceptable flow rate and the service capacity compared to other algorithms under an energy cost budget.
{"title":"Joint Optimization of Service Function Placement and Flow Distribution for Service Function Chaining","authors":"Insun Jang, Dongeun Suh, Sangheon Pack, G. Dán","doi":"10.1109/JSAC.2017.2760162","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760162","url":null,"abstract":"In this paper, we consider the problem of optimal dynamic service function (SF) placement and flow routing in a SF chaining (SFC) enabled network. We formulate a multi-objective optimization problem to maximize the acceptable flow rate and to minimize the energy cost for multiple service chains. We transform the multi-objective optimization problem into a single-objective mixed integer linear programming (MILP) problem, and prove that the problem is NP-hard. We propose a polynomial time algorithm based on linear relaxation and rounding to approximate the optimal solution of the MILP. Extensive simulations are conducted to evaluate the effects of the energy budget, the network topology, and the amount of server resources on the acceptable flow rate. The results demonstrate that the proposed algorithm can achieve near-optimal performance and can significantly increase the acceptable flow rate and the service capacity compared to other algorithms under an energy cost budget.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2532-2541"},"PeriodicalIF":16.4,"publicationDate":"2017-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760162","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46292620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-16DOI: 10.1109/JSAC.2017.2760398
G. Antichi, Ignacio Castro, Marco Chiesa, E. L. Fernandes, Remy Lapeyrade, Daniel Kopp, J. H. Han, M. Bruyère, C. Dietzel, M. Gusat, A. Moore, P. Owezarski, S. Uhlig, M. Canini
Innovation in interdomain routing has remained stagnant for over a decade. Recently, Internet eXchange Points (IXPs) have emerged as economically-advantageous interconnection points for reducing path latencies and exchanging ever increasing traffic volumes among, possibly, hundreds of networks. Given their far-reaching implications on interdomain routing, IXPs are the ideal place to foster network innovation and extend the benefits of software defined networking (SDN) to the interdomain level. In this paper, we present, evaluate, and demonstrate ENDEAVOUR, an SDN platform for IXPs. ENDEAVOUR can be deployed on a multi-hop IXP fabric, supports a large number of use cases, and is highly scalable, while avoiding broadcast storms. Our evaluation with real data from one of the largest IXPs, demonstrates the benefits and scalability of our solution: ENDEAVOUR requires around 70% fewer rules than alternative SDN solutions thanks to our rule partitioning mechanism. In addition, by providing an open source solution, we invite everyone from the community to experiment (and improve) our implementation as well as adapt it to new use cases.
{"title":"ENDEAVOUR: A Scalable SDN Architecture For Real-World IXPs","authors":"G. Antichi, Ignacio Castro, Marco Chiesa, E. L. Fernandes, Remy Lapeyrade, Daniel Kopp, J. H. Han, M. Bruyère, C. Dietzel, M. Gusat, A. Moore, P. Owezarski, S. Uhlig, M. Canini","doi":"10.1109/JSAC.2017.2760398","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760398","url":null,"abstract":"Innovation in interdomain routing has remained stagnant for over a decade. Recently, Internet eXchange Points (IXPs) have emerged as economically-advantageous interconnection points for reducing path latencies and exchanging ever increasing traffic volumes among, possibly, hundreds of networks. Given their far-reaching implications on interdomain routing, IXPs are the ideal place to foster network innovation and extend the benefits of software defined networking (SDN) to the interdomain level. In this paper, we present, evaluate, and demonstrate ENDEAVOUR, an SDN platform for IXPs. ENDEAVOUR can be deployed on a multi-hop IXP fabric, supports a large number of use cases, and is highly scalable, while avoiding broadcast storms. Our evaluation with real data from one of the largest IXPs, demonstrates the benefits and scalability of our solution: ENDEAVOUR requires around 70% fewer rules than alternative SDN solutions thanks to our rule partitioning mechanism. In addition, by providing an open source solution, we invite everyone from the community to experiment (and improve) our implementation as well as adapt it to new use cases.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2553-2562"},"PeriodicalIF":16.4,"publicationDate":"2017-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760398","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42519426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-09DOI: 10.1109/JSAC.2017.2760354
Zhongliang Zhao, Eryk Schiller, Eirini Kalogeiton, T. Braun, B. Stiller, Mevlut Turker Garip, Joshua Joy, M. Gerla, Nabeel Akhtar, I. Matta
Autonomic communications aim to provide the quality-of-service in networks using self-management mechanisms. It inherits many characteristics from autonomic computing, in particular, when communication systems are running as specialized applications in software-defined networking (SDN) and network function virtualization (NFV)-enabled cloud environments. This paper surveys autonomic computing and communications in the context of software-driven networks, i.e., networks based on SDN/NFV concepts. Autonomic communications create new challenges in terms of security, operations, and business support. We discuss several goals, research challenges, and development issues on self-management mechanisms and architectures in software-driven networks. This paper covers multiple perspectives of autonomic communications in software-driven networks, such as automatic testing, integration, and deployment of network functions. We also focus on self-management and optimization, which make use of machine learning techniques.
{"title":"Autonomic Communications in Software-Driven Networks","authors":"Zhongliang Zhao, Eryk Schiller, Eirini Kalogeiton, T. Braun, B. Stiller, Mevlut Turker Garip, Joshua Joy, M. Gerla, Nabeel Akhtar, I. Matta","doi":"10.1109/JSAC.2017.2760354","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760354","url":null,"abstract":"Autonomic communications aim to provide the quality-of-service in networks using self-management mechanisms. It inherits many characteristics from autonomic computing, in particular, when communication systems are running as specialized applications in software-defined networking (SDN) and network function virtualization (NFV)-enabled cloud environments. This paper surveys autonomic computing and communications in the context of software-driven networks, i.e., networks based on SDN/NFV concepts. Autonomic communications create new challenges in terms of security, operations, and business support. We discuss several goals, research challenges, and development issues on self-management mechanisms and architectures in software-driven networks. This paper covers multiple perspectives of autonomic communications in software-driven networks, such as automatic testing, integration, and deployment of network functions. We also focus on self-management and optimization, which make use of machine learning techniques.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2431-2445"},"PeriodicalIF":16.4,"publicationDate":"2017-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42961035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-09DOI: 10.1109/JSAC.2017.2760186
Xinchen Lyu, Wei Ni, Hui Tian, R. Liu, Xin Wang, G. Giannakis, A. Paulraj
Mobile edge computing is of particular interest to Internet of Things (IoT), where inexpensive simple devices can get complex tasks offloaded to and processed at powerful infrastructure. Scheduling is challenging due to stochastic task arrivals and wireless channels, congested air interface, and more prominently, prohibitive feedbacks from thousands of devices. In this paper, we generate asymptotically optimal schedules tolerant to out-of-date network knowledge, thereby relieving stringent requirements on feedbacks. A perturbed Lyapunov function is designed to stochastically maximize a network utility balancing throughput and fairness. A knapsack problem is solved per slot for the optimal schedule, provided up-to-date knowledge on the data and energy backlogs of all devices. The knapsack problem is relaxed to accommodate out-of-date network states. Encapsulating the optimal schedule under up-to-date network knowledge, the solution under partial out-of-date knowledge preserves asymptotic optimality, and allows devices to self-nominate for feedback. Corroborated by simulations, our approach is able to dramatically reduce feedbacks at no cost of optimality. The number of devices that need to feed back is reduced to less than 60 out of a total of 5000 IoT devices.
{"title":"Optimal Schedule of Mobile Edge Computing for Internet of Things Using Partial Information","authors":"Xinchen Lyu, Wei Ni, Hui Tian, R. Liu, Xin Wang, G. Giannakis, A. Paulraj","doi":"10.1109/JSAC.2017.2760186","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760186","url":null,"abstract":"Mobile edge computing is of particular interest to Internet of Things (IoT), where inexpensive simple devices can get complex tasks offloaded to and processed at powerful infrastructure. Scheduling is challenging due to stochastic task arrivals and wireless channels, congested air interface, and more prominently, prohibitive feedbacks from thousands of devices. In this paper, we generate asymptotically optimal schedules tolerant to out-of-date network knowledge, thereby relieving stringent requirements on feedbacks. A perturbed Lyapunov function is designed to stochastically maximize a network utility balancing throughput and fairness. A knapsack problem is solved per slot for the optimal schedule, provided up-to-date knowledge on the data and energy backlogs of all devices. The knapsack problem is relaxed to accommodate out-of-date network states. Encapsulating the optimal schedule under up-to-date network knowledge, the solution under partial out-of-date knowledge preserves asymptotic optimality, and allows devices to self-nominate for feedback. Corroborated by simulations, our approach is able to dramatically reduce feedbacks at no cost of optimality. The number of devices that need to feed back is reduced to less than 60 out of a total of 5000 IoT devices.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2606-2615"},"PeriodicalIF":16.4,"publicationDate":"2017-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44488507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-06DOI: 10.1109/JSAC.2017.2760459
Jun Du, E. Gelenbe, Chunxiao Jiang, Haijun Zhang, Yong Ren
In heterogeneous ultra-dense networks (HetUDNs), the software-defined wireless network (SDWN) separates resource management from geo-distributed resources belonging to different service providers. A centralized SDWN controller can manage the entire network globally. In this paper, we focus on mobile traffic offloading and resource allocation in SDWN-based HetUDNs, constituted of different macro base stations and small-cell base stations (SBSs). We explore a scenario where SBSs’ capacities are available, but their offloading performance is unknown to the SDWN controller: this is the information asymmetric case. To address this asymmetry, incentivized traffic offloading contracts are designed to encourage each SBS to select the contract that achieves its own maximum utility. The characteristics of large numbers of SBSs in HetUDNs are aggregated in an analytical model, allowing us to select the SBS types that provide the off-loading, based on different contracts which offer rationality and incentive compatibility to different SBS types. This leads to a closed-form expression for selecting the SBS types involved, and we prove the monotonicity and incentive compatibility of the resulting contracts. The effectiveness and efficiency of the proposed contract-based traffic offloading mechanism, and its overall system performance, are validated using simulations.
{"title":"Contract Design for Traffic Offloading and Resource Allocation in Heterogeneous Ultra-Dense Networks","authors":"Jun Du, E. Gelenbe, Chunxiao Jiang, Haijun Zhang, Yong Ren","doi":"10.1109/JSAC.2017.2760459","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760459","url":null,"abstract":"In heterogeneous ultra-dense networks (HetUDNs), the software-defined wireless network (SDWN) separates resource management from geo-distributed resources belonging to different service providers. A centralized SDWN controller can manage the entire network globally. In this paper, we focus on mobile traffic offloading and resource allocation in SDWN-based HetUDNs, constituted of different macro base stations and small-cell base stations (SBSs). We explore a scenario where SBSs’ capacities are available, but their offloading performance is unknown to the SDWN controller: this is the information asymmetric case. To address this asymmetry, incentivized traffic offloading contracts are designed to encourage each SBS to select the contract that achieves its own maximum utility. The characteristics of large numbers of SBSs in HetUDNs are aggregated in an analytical model, allowing us to select the SBS types that provide the off-loading, based on different contracts which offer rationality and incentive compatibility to different SBS types. This leads to a closed-form expression for selecting the SBS types involved, and we prove the monotonicity and incentive compatibility of the resulting contracts. The effectiveness and efficiency of the proposed contract-based traffic offloading mechanism, and its overall system performance, are validated using simulations.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2457-2467"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760459","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49148816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-06DOI: 10.1109/JSAC.2017.2760458
Lianyong Qi, Xuyun Zhang, Wanchun Dou, Q. Ni
To maximize the economic benefits, a cloud service provider needs to recommend its services to as many users as possible based on the historical user-service quality data. However, when a cloud platform (e.g., Amazon) intends to make a service recommendation decision, considering only its own user-service quality data is insufficient, because a cloud user may invoke services from multiple distributed cloud platforms (e.g., Amazon and IBM). In this situation, it is promising for Amazon to collaborate with other cloud platforms (e.g., IBM) to utilize the integrated data for the service recommendation to improve the recommendation accuracy. However, two challenges are present in the above-mentioned collaboration process, where we attempt to use multi-source data for the service recommendation. First, protecting users’ privacy is challenging when IBM releases its own data to Amazon. Second, the recommendation efficiency and scalability are often low when the user-service quality data of Amazon and IBM update frequently. Considering these challenges, a privacy-preserving and scalable service recommendation approach based on distributed locality-sensitive hashing, i.e., $textit {SerRec}_{textit {distri-LSH}}$ , is proposed in this paper to handle the service recommendation in a distributed cloud environment. Extensive experiments on the WS-DREAM data set validate the feasibility of our approach in terms of service recommendation accuracy, scalability, and privacy preservation.
{"title":"A Distributed Locality-Sensitive Hashing-Based Approach for Cloud Service Recommendation From Multi-Source Data","authors":"Lianyong Qi, Xuyun Zhang, Wanchun Dou, Q. Ni","doi":"10.1109/JSAC.2017.2760458","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760458","url":null,"abstract":"To maximize the economic benefits, a cloud service provider needs to recommend its services to as many users as possible based on the historical user-service quality data. However, when a cloud platform (e.g., Amazon) intends to make a service recommendation decision, considering only its own user-service quality data is insufficient, because a cloud user may invoke services from multiple distributed cloud platforms (e.g., Amazon and IBM). In this situation, it is promising for Amazon to collaborate with other cloud platforms (e.g., IBM) to utilize the integrated data for the service recommendation to improve the recommendation accuracy. However, two challenges are present in the above-mentioned collaboration process, where we attempt to use multi-source data for the service recommendation. First, protecting users’ privacy is challenging when IBM releases its own data to Amazon. Second, the recommendation efficiency and scalability are often low when the user-service quality data of Amazon and IBM update frequently. Considering these challenges, a privacy-preserving and scalable service recommendation approach based on distributed locality-sensitive hashing, i.e., $textit {SerRec}_{textit {distri-LSH}}$ , is proposed in this paper to handle the service recommendation in a distributed cloud environment. Extensive experiments on the WS-DREAM data set validate the feasibility of our approach in terms of service recommendation accuracy, scalability, and privacy preservation.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2616-2624"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760458","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41795108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-06DOI: 10.1109/JSAC.2017.2760418
F. Z. Yousaf, M. Bredel, S. Schaller, Fabian Schneider
Communication networks are undergoing their next evolutionary step toward 5G. The 5G networks are envisioned to provide a flexible, scalable, agile, and programmable network platform over which different services with varying requirements can be deployed and managed within strict performance bounds. In order to address these challenges, a paradigm shift is taking place in the technologies that drive the networks, and thus their architecture. Innovative concepts and techniques are being developed to power the next generation mobile networks. At the heart of this development lie Network Function Virtualization and Software Defined Networking technologies, which are now recognized as being two of the key technology enablers for realizing 5G networks, and which have introduced a major change in the way network services are deployed and operated. For interested readers that are new to the field of SDN and NFV, this paper provides an overview of both these technologies with reference to the 5G networks. Most importantly, it describes how the two technologies complement each other and how they are expected to drive the networks of near future.
{"title":"NFV and SDN—Key Technology Enablers for 5G Networks","authors":"F. Z. Yousaf, M. Bredel, S. Schaller, Fabian Schneider","doi":"10.1109/JSAC.2017.2760418","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760418","url":null,"abstract":"Communication networks are undergoing their next evolutionary step toward 5G. The 5G networks are envisioned to provide a flexible, scalable, agile, and programmable network platform over which different services with varying requirements can be deployed and managed within strict performance bounds. In order to address these challenges, a paradigm shift is taking place in the technologies that drive the networks, and thus their architecture. Innovative concepts and techniques are being developed to power the next generation mobile networks. At the heart of this development lie Network Function Virtualization and Software Defined Networking technologies, which are now recognized as being two of the key technology enablers for realizing 5G networks, and which have introduced a major change in the way network services are deployed and operated. For interested readers that are new to the field of SDN and NFV, this paper provides an overview of both these technologies with reference to the 5G networks. Most importantly, it describes how the two technologies complement each other and how they are expected to drive the networks of near future.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2468-2478"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760418","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45349504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-06DOI: 10.1109/JSAC.2017.2760478
Syed Noor-ul-Hassan Shirazi, Antonios Gouglidis, Arsham Farshad, D. Hutchison
Mobile edge computing (MEC) and fog are emerging computing models that extend the cloud and its services to the edge of the network. The emergence of both MEC and fog introduce new requirements, which mean their supported deployment models must be investigated. In this paper, we point out the influence and strong impact of the extended cloud (i.e., the MEC and fog) on existing communication and networking service models of the cloud. Although the relation between them is fairly evident, there are important properties, notably those of security and resilience, that we study in relation to the newly posed requirements from the MEC and fog. Although security and resilience have been already investigated in the context of the cloud-to a certain extent-existing solutions may not be applicable in the context of the extended cloud. Our approach includes the examination of models and architectures that underpin the extended cloud, and we provide a contemporary discussion on the most evident characteristics associated with them. We examine the technologies that implement these models and architectures, and analyze them with respect to security and resilience requirements. Furthermore, approaches to security and resilience-related mechanisms are examined in the cloud (specifically, anomaly detection and policy-based resilience management), and we argue that these can also be applied in order to improve security and achieve resilience in the extended cloud environment.
{"title":"The Extended Cloud: Review and Analysis of Mobile Edge Computing and Fog From a Security and Resilience Perspective","authors":"Syed Noor-ul-Hassan Shirazi, Antonios Gouglidis, Arsham Farshad, D. Hutchison","doi":"10.1109/JSAC.2017.2760478","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760478","url":null,"abstract":"Mobile edge computing (MEC) and fog are emerging computing models that extend the cloud and its services to the edge of the network. The emergence of both MEC and fog introduce new requirements, which mean their supported deployment models must be investigated. In this paper, we point out the influence and strong impact of the extended cloud (i.e., the MEC and fog) on existing communication and networking service models of the cloud. Although the relation between them is fairly evident, there are important properties, notably those of security and resilience, that we study in relation to the newly posed requirements from the MEC and fog. Although security and resilience have been already investigated in the context of the cloud-to a certain extent-existing solutions may not be applicable in the context of the extended cloud. Our approach includes the examination of models and architectures that underpin the extended cloud, and we provide a contemporary discussion on the most evident characteristics associated with them. We examine the technologies that implement these models and architectures, and analyze them with respect to security and resilience requirements. Furthermore, approaches to security and resilience-related mechanisms are examined in the cloud (specifically, anomaly detection and policy-based resilience management), and we argue that these can also be applied in order to improve security and achieve resilience in the extended cloud environment.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2586-2595"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44025503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-06DOI: 10.1109/JSAC.2017.2760438
Chen Sun, J. Bi, Zhilong Zheng, Hongxin Hu
Network function virtualization (NFV) offers the potential for both enhancing service delivery flexibility and reducing overall costs by virtualizing network functions that are traditionally implemented in dedicated hardware. However, the flexibility of NFV comes with considerable compromises since virtual machine carried functions could introduce significant performance overhead. In this paper, we present a novel high-performance framework called HYPER, which combines programmable hardware infrastructure and traditional software infrastructure in NFV to achieve both high performance and flexibility for supporting virtualized network functions (VNFs). In HYPER, we design a mediator layer to hide underlying infrastructure heterogeneity from the NFV orchestrator to simplify VNF management. In addition, we design a SLA-aware service chaining algorithm in HYPER to leverage the benefits of the hybrid infrastructure to fulfill both functional and performance requirements from service subscribers (or tenants). To optimize resource utilization efficiency, we also introduce a performance-aware VNF placement algorithm in HYPER, which accommodates both resource and performance requirements in placing VNFs. We implement HYPER in a testbed based on OpenStack and ONetCard. Experimental results show that HYPER reduces the forwarding latency of a service chain by 40% to 67% compared with data plane development kit -based implementation, while maintaining the flexibility of VNF management.
{"title":"HYPER: A Hybrid High-Performance Framework for Network Function Virtualization","authors":"Chen Sun, J. Bi, Zhilong Zheng, Hongxin Hu","doi":"10.1109/JSAC.2017.2760438","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760438","url":null,"abstract":"Network function virtualization (NFV) offers the potential for both enhancing service delivery flexibility and reducing overall costs by virtualizing network functions that are traditionally implemented in dedicated hardware. However, the flexibility of NFV comes with considerable compromises since virtual machine carried functions could introduce significant performance overhead. In this paper, we present a novel high-performance framework called HYPER, which combines programmable hardware infrastructure and traditional software infrastructure in NFV to achieve both high performance and flexibility for supporting virtualized network functions (VNFs). In HYPER, we design a mediator layer to hide underlying infrastructure heterogeneity from the NFV orchestrator to simplify VNF management. In addition, we design a SLA-aware service chaining algorithm in HYPER to leverage the benefits of the hybrid infrastructure to fulfill both functional and performance requirements from service subscribers (or tenants). To optimize resource utilization efficiency, we also introduce a performance-aware VNF placement algorithm in HYPER, which accommodates both resource and performance requirements in placing VNFs. We implement HYPER in a testbed based on OpenStack and ONetCard. Experimental results show that HYPER reduces the forwarding latency of a service chain by 40% to 67% compared with data plane development kit -based implementation, while maintaining the flexibility of VNF management.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2490-2500"},"PeriodicalIF":16.4,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760438","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44491092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-10-05DOI: 10.1109/JSAC.2017.2760187
Pengzhan Wang, Hongli Xu, Liusheng Huang, Jie He, Zeyu Meng
Software defined networking (SDN) separates the data plane and control plane on independent devices. Since the data plane, consisting of switches, is responsible for packets forwarding, previous work often considers the different constraints (e.g., data link capacity and flow-table size) only in the data plane to provide better QoS for users. However, due to limited CPU processing power and low speed of flow-table updating on each switch, the control channels/links between switches and the controller often have very limited capacity, which will cause QoS performance (e.g., response time and throughput) degradation when the switch should handle a high traffic load. The goal of our paper is to achieve better QoS by jointly considering the control link constraint and other different constraints of the data plane in SDNs. We formally define the control link load balancing and low delay route deployment problems, and prove the NP-Hardness. We present two algorithms with bounded approximation factors for each problem and implement the proposed methods on our SDN testbed. Extensive simulation results and experimental results show that our algorithms can reduce control link load by about 50% and response time by about 60%, and increase the network throughput by 65% compared with previous methods.
SDN (Software defined networking)将数据平面和控制平面分隔在独立的设备上。由于数据平面由交换机组成，负责数据包的转发，以往的工作往往只考虑数据平面的不同约束(如数据链路容量、流表大小)，以便为用户提供更好的QoS。然而，由于每台交换机上CPU处理能力有限，流表更新速度较慢，交换机和控制器之间的控制通道/链路往往容量非常有限，当交换机应该处理高流量负载时，这将导致QoS性能(如响应时间和吞吐量)下降。本文的目标是通过综合考虑sdn中数据平面的控制链路约束和其他不同约束来实现更好的QoS。我们正式定义了控制链路负载均衡和低时延路由部署问题，并证明了np -硬度。我们针对每个问题提出了两种具有有界近似因子的算法，并在我们的SDN测试平台上实现了所提出的方法。大量的仿真和实验结果表明，与以往的方法相比，我们的算法可以将控制链路负载减少约50%，响应时间减少约60%，网络吞吐量提高约65%。
{"title":"Control Link Load Balancing and Low Delay Route Deployment for Software Defined Networks","authors":"Pengzhan Wang, Hongli Xu, Liusheng Huang, Jie He, Zeyu Meng","doi":"10.1109/JSAC.2017.2760187","DOIUrl":"https://doi.org/10.1109/JSAC.2017.2760187","url":null,"abstract":"Software defined networking (SDN) separates the data plane and control plane on independent devices. Since the data plane, consisting of switches, is responsible for packets forwarding, previous work often considers the different constraints (e.g., data link capacity and flow-table size) only in the data plane to provide better QoS for users. However, due to limited CPU processing power and low speed of flow-table updating on each switch, the control channels/links between switches and the controller often have very limited capacity, which will cause QoS performance (e.g., response time and throughput) degradation when the switch should handle a high traffic load. The goal of our paper is to achieve better QoS by jointly considering the control link constraint and other different constraints of the data plane in SDNs. We formally define the control link load balancing and low delay route deployment problems, and prove the NP-Hardness. We present two algorithms with bounded approximation factors for each problem and implement the proposed methods on our SDN testbed. Extensive simulation results and experimental results show that our algorithms can reduce control link load by about 50% and response time by about 60%, and increase the network throughput by 65% compared with previous methods.","PeriodicalId":13243,"journal":{"name":"IEEE Journal on Selected Areas in Communications","volume":"35 1","pages":"2446-2456"},"PeriodicalIF":16.4,"publicationDate":"2017-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/JSAC.2017.2760187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48019865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：