The Experts below are selected from a list of 5325 Experts worldwide ranked by ideXlab platform
Xiaojun Cao - One of the best experts on this subject based on the ideXlab platform.
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service function chaining and embedding with spanning closed walk
High Performance Switching and Routing, 2019Co-Authors: Danyang Zheng, Guangchun Luo, Ling Tian, Chengzong Peng, Xueting Liao, Xiaojun CaoAbstract:Network Function Virtualization (NFV) takes advantages of the emerging technologies in virtualization and automation to offer new ways in design, deployment, and management of networking services. In NFV, the Proprietary Hardware-based network functions are replaced by the software-based modules named as Virtual Network Functions (VNFs) or Service Functions (SFs). A network service request from the customer can be formed by multiple SFs. To satisfy a network service request, the service provider has to chain the SFs in the request into a Service Function Chain (SFC) and embed the constructed SFC onto the shared substrate network. In this paper, we comprehensively study how to composite and embed an SFC onto a shared substrate network with unique service function. We formulate this problem with the Integer Linear Programming (ILP) technique. We also propose an efficient heuristic algorithm with 2-approximation boundary, namely, Spanning Closed Walk based SFC Embedding (SCW-SFCE). Our extensive simulations and analysis show that the proposed approach can achieve near-optimal performance in a small network and outperform the Nearest Neighbour (NN) algorithm.
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dependence aware service function chain embedding in optical networks
International Conference on Communications, 2019Co-Authors: Danyang Zheng, Evrim Guler, Guangchun Luo, Ling Tian, Chengzong Peng, Xiaojun CaoAbstract:Network Function Virtualization (NFV) technology decouples network functions from Proprietary Hardware equipments. As a result, Internet Service Providers (ISPs) implement software-based network functions on generic highvolume substrate network devices. In NFV, a Service Function Chain (SFC) is defined as an ordered set of abstract network functions running on specific substrate nodes (e.g., servers). A challenging issue in NFV management and orchestration is how to optimize the Dependence-aware SFC Embedding in substrate Optical networks (D_SFCE_O). In this paper, we propose a novel algorithm, namely, Dependence-aware SFC embedding with Least-Used consecutive subcarriers (D_SFC_LU), which jointly optimizes SFC design, SFC mapping and spectrum allocation in optical networks. To minimize resource consumption, D_SFC_LU takes advantages of the proposed techniques: Impact Factor based Node Selection (IFNS), Chain Node Mapping (CNM) and Chain-Fit (CF) spectrum allocation. Our simulation and analysis demonstrate that D_SFC_LU can efficiently embed a network requests while minimizing the required substrate resource in optical networks.
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Embedding dependence-aware service function chains
Journal of Optical Communications and Networking, 2018Co-Authors: Maryam Jalalitabar, Danyang Zheng, Evrim Guler, Guangchun Luo, Ling Tian, Xiaojun CaoAbstract:Network function virtualization (NFV) provides an effective way to decouple network functions from the Proprietary Hardware, allowing the network providers to implement network functions as virtual machines running on standard servers. In the NFV environment, an NFV service request is provisioned in the form of a service function chain (SFC). The SFC defines the exact sequence of actions or virtual network functions (VNFs) that the data stream from the service request is subjected to. These actions or VNFs need to bemapped onto specific physical networks to provide network services for end users. In this paper,we investigate the problem of dependence-aware service function chain (D_SFC) design and mapping. We study how to efficiently map users’ service requests over the physical network while taking into consideration the computing resource demand, function dependence of the VNFs, and the bandwidth demand for the service request. We propose an efficient algorithm, namely, Dependence-Aware SFC Embedding With Group Mapping (D_SFC_GM), which integrates the proposed techniques of dependence sorting, independent grouping, adaptive mapping, and tetragon remapping to jointly design and map users’ service requests. The proposed D_SFC_GM algorithm takes advantage of VNF’s dependence relationships and the available resources in the physical network to efficiently design the chain and reserve the computing/bandwidth in the physical network. The extensive performance analysis in both IP and physical networks shows that the proposed D_SFC_GM significantly outperforms the traditional approach based on topological sorting and sequential embedding.
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joint topology design and mapping of service function chains in network function virtualization
Global Communications Conference, 2016Co-Authors: Xiaojun Cao, Chunming QiaoAbstract:Network Function Virtualization (NFV) is promising to lower the network operator's capital expenditure and operational expenditure by replacing Proprietary Hardware-based network equipment with software-based virtual network functions that can be consolidated into telecom clouds. In particular, NFV provides an efficient way to deploy network services using service function chains that consist of a set of virtual network functions interconnected by virtual links. A practical and yet theoretically challenging issue related to NFV Management and Orchestration is how to jointly optimize the topology design and mapping of multiple service function chains, which is called the JTDM problem. In this paper, we develop an Integer Linear Programming (ILP) model to formulate the JTDM problem with the objective of minimizing the bandwidth consumption in the physical substrate. We propose a novel heuristic algorithm, namely Closed-loop with Critical Mapping Feedback (CCMF), to efficiently address this problem. Through comprehensive simulations, we demonstrate that the CCMF algorithm is efficient in terms of the bandwidth consumption in various scenarios, and can achieve a bandwidth consumption that is close to the minimum obtained by ILP.
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Joint topology design and mapping of service function chains for efficient, scalable, and reliable network functions virtualization
IEEE Network, 2016Co-Authors: Zilong Ye, Xiaojun Cao, Hongfang Yu, Jian Ping Wang, Chunming QiaoAbstract:NFV is promising to lower the network operator’s capital expenditure and oper- ational expenditure by replacing Proprietary Hardware-based network equipment with software-based VNFs that can be consolidated into telecom clouds. In par- ticular, NFV provides an efficient way to deploy network services using SFCs that consist of a set of VNFs interconnected by virtual links. A practical but theoretically challenging problem related to NFV management and orchestration is how to jointly optimize the topology design and mapping of multiple SFCs such that the TBC is minimized, which is called the JTDM problem. In this article, we propose a novel heuristic algorithm, Closed-Loop with Critical Mapping Feedback, to efficiently address the JTDM problem. While minimizing the TBC, we also propose scalable and reliable JTDM strategies that can significantly reduce the network reconfigura- tions and enhance the service reliability, respectively.
Shuang Qin - One of the best experts on this subject based on the ideXlab platform.
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joint two tier network function parallelization on multicore platform
IEEE Transactions on Network and Service Management, 2019Co-Authors: Mengjie Liu, Gang Feng, Jianhong Zhou, Shuang QinAbstract:As network function virtualization (NFV) is realized based on general-purpose processors for avoiding Proprietary Hardware, its benefits of flexibility and agility could be compromised by the increased packet latency and reduced throughput. An effective approach for improving the latency and throughput performance is to exploit new network function (NF) processing framework on general purpose processors. In this paper, we propose a new joint two-tier NF parallelization (TNP) framework, which can agilely and flexibly organize parallel NF processing to greatly improve the latency and throughput performance of service function chain (SFC) which is constituted by a set of NFs. In TNP, we jointly organize the parallelization of multiple NFs at the service tier and perform multicore mapping of individual NFs at the substrate network tier. We formulate the optimal TNP design problem as minimizing link bandwidth consumption subject to end-to-end latency and computing resource constraints. We solve the problem by decomposing it into two easier subproblems: 1) subproblem 1 (SP1) is to solve the optimal SFC parallelization graph design in conjunction with link mapping problem and 2) subproblem 2 (SP2) is to jointly solve computing resource allocation in conjunction with node mapping problem. The global optimal solution is accomplished by searching in a set of feasible regions in sequence. Numerical results demonstrate that our proposed TNP can significantly decrease service latency and improve network throughput compared with known single layer NF parallelization schemes. Moreover, the link bandwidth utilization and SFC request acceptance rate in the substrate network can also be greatly improved.
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joint two tier network function parallelization on multicore platform
Global Communications Conference, 2018Co-Authors: Mengjie Liu, Gang Feng, Jianhong Zhou, Shuang QinAbstract:As Network Function Virtualization (NFV) is based on general purpose processors for avoiding any Proprietary Hardware, the benefits of NFV could be compromised by increased packet latency and reduced throughput. One feasible solution is to exploit new network function (NF) framework with aim of reducing the processing latency in NFs. In this paper, we propose a new joint Two-Tier NF Parallelization (TNP) framework, which can agilely and flexibly organize parallel NF processing and map individual NFs to one or multiple processing core(s). In TNP, we jointly design the parallelization of multiple NFs at service tier and the multicore mapping of individual NF at substrate network tier. We formulate the optimal TNP design problem as maximizing link bandwidth utilization subject to end-to-end latency and computing resource constraints. The global optimal solution is accomplished by searching in a set of feasible regions in sequence. Numerical results demonstrate that our proposed TNP can significantly decrease the latency in NF processing and improve network throughput compared with single layer parallelization SFC framework.
Chunming Qiao - One of the best experts on this subject based on the ideXlab platform.
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joint topology design and mapping of service function chains in network function virtualization
Global Communications Conference, 2016Co-Authors: Xiaojun Cao, Chunming QiaoAbstract:Network Function Virtualization (NFV) is promising to lower the network operator's capital expenditure and operational expenditure by replacing Proprietary Hardware-based network equipment with software-based virtual network functions that can be consolidated into telecom clouds. In particular, NFV provides an efficient way to deploy network services using service function chains that consist of a set of virtual network functions interconnected by virtual links. A practical and yet theoretically challenging issue related to NFV Management and Orchestration is how to jointly optimize the topology design and mapping of multiple service function chains, which is called the JTDM problem. In this paper, we develop an Integer Linear Programming (ILP) model to formulate the JTDM problem with the objective of minimizing the bandwidth consumption in the physical substrate. We propose a novel heuristic algorithm, namely Closed-loop with Critical Mapping Feedback (CCMF), to efficiently address this problem. Through comprehensive simulations, we demonstrate that the CCMF algorithm is efficient in terms of the bandwidth consumption in various scenarios, and can achieve a bandwidth consumption that is close to the minimum obtained by ILP.
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Joint topology design and mapping of service function chains for efficient, scalable, and reliable network functions virtualization
IEEE Network, 2016Co-Authors: Zilong Ye, Xiaojun Cao, Hongfang Yu, Jian Ping Wang, Chunming QiaoAbstract:NFV is promising to lower the network operator’s capital expenditure and oper- ational expenditure by replacing Proprietary Hardware-based network equipment with software-based VNFs that can be consolidated into telecom clouds. In par- ticular, NFV provides an efficient way to deploy network services using SFCs that consist of a set of VNFs interconnected by virtual links. A practical but theoretically challenging problem related to NFV management and orchestration is how to jointly optimize the topology design and mapping of multiple SFCs such that the TBC is minimized, which is called the JTDM problem. In this article, we propose a novel heuristic algorithm, Closed-Loop with Critical Mapping Feedback, to efficiently address the JTDM problem. While minimizing the TBC, we also propose scalable and reliable JTDM strategies that can significantly reduce the network reconfigura- tions and enhance the service reliability, respectively.
Carol Fung - One of the best experts on this subject based on the ideXlab platform.
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a requirement oriented design of nfv topology by formal synthesis
IEEE Transactions on Network and Service Management, 2019Co-Authors: A H M Jakaria, Mohammad Ashiqur Rahman, Carol FungAbstract:Computer networks today heavily depend on expensive and Proprietary Hardware deployed at fixed locations. Network functions virtualization (NFV), one of the fastest emerging topics in networking, reduces the limitations of these vendor-specific Hardware with respect to the flexibility of network architecture and elasticity in handling varying traffic patterns. Many defense mechanisms against cyberattacks, as well as quality enhancing techniques have been proposed by leveraging the capabilities of the NFV architecture. NFV allows a flexible and dynamic implementation of virtual network functions in virtual machines running on commercial-off-the-shelf (COTS) servers. These quality enhancing network functions often work as a filter to distinguish between a legitimate packet and an attack packet and can be deployed dynamically to balance the variable attack load. However, allocating resources to these virtual machines is an NP-hard problem. In this paper, we propose a solution to this problem and determine the number and placement of the virtual machines (VMs) hosted on COTS servers. We design and implement two separate automated frameworks for defense and quality maintenance that model the resource specifications, incoming packet processing requirements, and network bandwidth constraints. It uses satisfiability modulo theories (SMT) for modeling this synthesis problem and provides a satisfiable solution.
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a collaborative ddos defence framework using network function virtualization
IEEE Transactions on Information Forensics and Security, 2017Co-Authors: Bahman Rashidi, Carol Fung, Elisa BertinoAbstract:High-profile and often destructive distributed denial of service (DDoS) attacks continue to be one of the top security concerns as the DDoS attacks volumes are increasing constantly. Among them, the SYN Flood attack is the most common type. Conventional DDoS defense solutions may not be preferable, since they demand highly capable Hardware resources, which induce high cost and long deployment cycle. The emerging of network function virtualization (NFV) technology introduces new opportunities to decrease the amount of Proprietary Hardware that is needed to launch and operate network services. In this paper, we propose a DDoS defense mechanism named CoFence, which facilitates a “domain-helps-domain” collaboration network among NFV-based domain networks. CoFence allows domain networks to help each other in handling large volume of DDoS attacks through resource sharing. Specifically, we design a dynamic resource allocation mechanism for domains so that the resource allocation is fair, efficient, and incentive-compatible. The resource sharing mechanism is modeled as a multi-leader-follower Stackelberg game. In this game, all domains have a degree of control to maximize their own utility. The resource supplier domains determine the amount of resource to each requesting peer based on optimizing a reciprocal-based utility function. On the other hand, the resource requesting domains decide the level of demand to send to the resource supplier domains in order to reach sufficient support. Our simulation results demonstrate that the designed resource allocation game is effective, incentive compatible, fair, and reciprocal under its Nash equilibrium.
Mengjie Liu - One of the best experts on this subject based on the ideXlab platform.
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joint two tier network function parallelization on multicore platform
IEEE Transactions on Network and Service Management, 2019Co-Authors: Mengjie Liu, Gang Feng, Jianhong Zhou, Shuang QinAbstract:As network function virtualization (NFV) is realized based on general-purpose processors for avoiding Proprietary Hardware, its benefits of flexibility and agility could be compromised by the increased packet latency and reduced throughput. An effective approach for improving the latency and throughput performance is to exploit new network function (NF) processing framework on general purpose processors. In this paper, we propose a new joint two-tier NF parallelization (TNP) framework, which can agilely and flexibly organize parallel NF processing to greatly improve the latency and throughput performance of service function chain (SFC) which is constituted by a set of NFs. In TNP, we jointly organize the parallelization of multiple NFs at the service tier and perform multicore mapping of individual NFs at the substrate network tier. We formulate the optimal TNP design problem as minimizing link bandwidth consumption subject to end-to-end latency and computing resource constraints. We solve the problem by decomposing it into two easier subproblems: 1) subproblem 1 (SP1) is to solve the optimal SFC parallelization graph design in conjunction with link mapping problem and 2) subproblem 2 (SP2) is to jointly solve computing resource allocation in conjunction with node mapping problem. The global optimal solution is accomplished by searching in a set of feasible regions in sequence. Numerical results demonstrate that our proposed TNP can significantly decrease service latency and improve network throughput compared with known single layer NF parallelization schemes. Moreover, the link bandwidth utilization and SFC request acceptance rate in the substrate network can also be greatly improved.
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joint two tier network function parallelization on multicore platform
Global Communications Conference, 2018Co-Authors: Mengjie Liu, Gang Feng, Jianhong Zhou, Shuang QinAbstract:As Network Function Virtualization (NFV) is based on general purpose processors for avoiding any Proprietary Hardware, the benefits of NFV could be compromised by increased packet latency and reduced throughput. One feasible solution is to exploit new network function (NF) framework with aim of reducing the processing latency in NFs. In this paper, we propose a new joint Two-Tier NF Parallelization (TNP) framework, which can agilely and flexibly organize parallel NF processing and map individual NFs to one or multiple processing core(s). In TNP, we jointly design the parallelization of multiple NFs at service tier and the multicore mapping of individual NF at substrate network tier. We formulate the optimal TNP design problem as maximizing link bandwidth utilization subject to end-to-end latency and computing resource constraints. The global optimal solution is accomplished by searching in a set of feasible regions in sequence. Numerical results demonstrate that our proposed TNP can significantly decrease the latency in NF processing and improve network throughput compared with single layer parallelization SFC framework.
