The Experts below are selected from a list of 443643 Experts worldwide ranked by ideXlab platform
Jaafar M H Elmirghani - One of the best experts on this subject based on the ideXlab platform.
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Optimized Energy Aware 5G Network Function Virtualization
IEEE Access, 2019Co-Authors: Ahmed N. Al-quzweeni, Taisir E H Elgorashi, Ahmed Qasim Lawey, Jaafar M H ElmirghaniAbstract:In this paper, Network Function virtualization (NFV) is identified as a promising key technology, which can contribute to energy-efficiency improvement in 5G Networks. An optical Network supported architecture is proposed and investigated in this paper to provide the wired infrastructure needed in 5G Networks and to support NFV toward an energy efficient 5G Network. In this paper, the mobile core Network Functions, as well as baseband Function, are virtualized and provided as VMs. The impact of the total number of active users in the Network, backhaul/fronthaul configurations, and VM inter-traffic are investigated. A mixed integer linear programming (MILP) optimization model is developed with the objective of minimizing the total power consumption by optimizing the VMs location and VMs servers’ utilization. The MILP model results show that virtualization can result in up to 38% (average 34%) energy saving. The results also reveal how the total number of active users affects the baseband virtual machines (BBUVMs) optimal distribution whilst the core Network virtual machines (CNVMs) distribution is affected mainly by the inter-traffic between the VMs. For real-time implementation, two heuristics are developed, an energy efficient NFV without CNVMs inter-traffic (EENFVnoITr) heuristic and an energy efficient NFV with CNVMs inter-traffic (EENFVwithITr) heuristic, both produce comparable results to the optimal MILP results. Finally, a genetic algorithm is developed for further verification of the results.
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optimized energy aware 5g Network Function virtualization
arXiv: Networking and Internet Architecture, 2018Co-Authors: Ahmed Alquzweeni, Ahmed Qasim Lawey, Taisir E H Elgorashi, Jaafar M H ElmirghaniAbstract:In this paper, Network Function virtualization (NFV) is identified as a promising key technology that can contribute to energy-efficiency improvement in 5G Networks. an optical Network supported architecture is proposed and investigated in this work to provide the wired infrastructure needed in 5G Networks and to support NFV towards an energy efficient 5G Networks. In this architecture the mobile core Network Functions as well as baseband Function are virtualized and provided as VMs. the impact of the total number of active users in the Network, backhaul/fronthaul configurations and VM inter-traffic are investigated. A mixed integer linear programming (MILP) optimising model is developed with the objective of minimising the total power consumption by optimizing the VMs location and VMs servers' utilisation. The MILP model results show that virtualization can result in up to 38% (average 34) energy saving. The results also reveal how the total number of active users affects the baseband VMs optimal distribution whilst the core Network VMs distribution is affected mainly by the inter-traffic between the VMs. For real-time implementation, two heuristics are developed an Energy Efficient NFV without CNVMs inter-traffic (EENFVnoITr) heuristic and an Energy Efficient NFV with CNVMs inter-traffic (EENFVwithITr) heuristic, both produce comparable results to the optimal MILP results
Song Guo - One of the best experts on this subject based on the ideXlab platform.
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Service Chaining for Hybrid Network Function
IEEE Transactions on Cloud Computing, 2019Co-Authors: Huawei Huang, Song GuoAbstract:In the Service-Function-Chaining (SFC) enabled Networks, various sophisticated policy-aware Network Functions, such as intrusion detection, access control and unified threat management, can be realized in either physical middleboxes or virtualized Network Function (VNF) appliances. In this paper, we study the service chaining towards the hybrid SFC clouds, where both physical appliances and VNF appliances provide services collaboratively. In such hybrid SFC Networks, the challenge is how to efficiently steer the service chains for traffic demands while matching their individual policy chains concurrently such that a utility associated with the total admitted traffic rate and the induced overheads can be maximized. We find such problem has not been well solved so far. To this end, we devise a Markov Approximation (MA) based algorithm. The approximation property of the proposed algorithm is also proved. Extensive evaluation results show that the proposed MA algorithm can yield near-optimal solutions and outperform other benchmark algorithms significantly.
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throughput maximization of delay sensitive request admissions via virtualized Network Function placements and migrations
International Conference on Communications, 2018Co-Authors: Meitian Huang, Weifa Liang, Song GuoAbstract:Network Function Virtualization (NFV) has attracted significant attentions from both industry and academia as an important paradigm change in Network service provisioning. Most existing studies on NFV dealt with admissions of user requests through deploying Virtualized Network Function (VNF) instances for individual user requests, without considering sharing VNF instances among multiple user requests to provide better Network services and improve Network throughput. In this paper, we study the Network throughput maximization problem by adopting two different VNF instance scalings: (i) horizontal scaling by migrating existing VNF instances from their current locations to new locations; and (ii) vertical scaling by instantiating more VNF instances if needed. Specifically, we first propose a unified framework that jointly considers both vertical and horizontal scalings to maximize the Network throughput, by admitting as many requests as possible while meeting their resource demands and end-to-end transmission delay requirements. We then devise an efficient heuristic algorithm for the problem. We finally conduct experiments to evaluate the performance of the proposed algorithm. Experimental results demonstrate that the proposed algorithm outperforms a baseline algorithm.
Attila Takács - One of the best experts on this subject based on the ideXlab platform.
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Network Function placement for nfv chaining in packet optical datacenters
Journal of Lightwave Technology, 2015Co-Authors: Ming Xia, Meral Shirazipour, Howard Green, Ying Zhang, Attila TakácsAbstract:In an operator's datacenter, optical technologies can be employed to perform Network Function (NF) chaining for larger aggregated flows in parallel with the conventional packet-based fine-grained traffic steering schemes. When Network Function virtualization (NFV) is enabled, virtualized NFs (vNF) can be placed when and where needed. In this study, we identify the possibility of minimizing the expensive optical/electronic/optical (O/E/O) conversions for NFV chaining in packet/optical datacenters, which is introduced by the on-demand placement of vNFs. When the vNFs of the same NF chain are properly grouped into fewer pods, traffic flows can avoid unnecessary traversals in the optical domain. We formulate the problem of optimal vNF placement in binary integer programming (BIP), and propose an alternative efficient heuristic algorithm to solve this problem. Evaluation results show that our algorithm can achieve near-optimal O/E/O conversions comparable to BIP. We also demonstrate the effectiveness of our algorithm under various scenarios, with comparison to a simple first-fit algorithm.
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Optical service chaining for Network Function virtualization
IEEE Communications Magazine, 2015Co-Authors: Ming Xia, Meral Shirazipour, Howard Green, Ying Zhang, Attila TakácsAbstract:This article presents an efficient optical service chaining architecture for Network Function virtualization in data centers. Service chaining (i.e., steering traffic through a sequence of Network Functions) is one emerging application of software-defined Networking. However, existing schemes steer traffic solely in the packet domain, which is well suited for fine-grained (e.g., peruser level) flows carrying a relatively small volume of traffic. This article discusses how packet-based schemes do not yield sufficient efficiency for large/aggregated flows steered through high-capacity core Network Functions. It introduces an optical steering domain into the operator's data centers for NFV service chaining at a coarse-grained traffic level using wavelength switching. Performance evaluation shows that the optical steering domain can achieve significant power savings compared to using packet technologies as flow rates and the number of vNFs per service chain grow.
Raouf Boutaba - One of the best experts on this subject based on the ideXlab platform.
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topology aware prediction of virtual Network Function resource requirements
IEEE Transactions on Network and Service Management, 2017Co-Authors: Rashid Mijumbi, Sidhant Hasija, Steven Davy, Alan Davy, Brendan Jennings, Raouf BoutabaAbstract:Network Functions virtualization (NFV) continues to gain attention as a paradigm shift in the way telecommunications services are deployed and managed. By separating Network Function from traditional middleboxes, NFV is expected to lead to reduced capital expenditure and operating expenditure, and to more agile services. However, one of the main challenges to achieving these objectives is how physical resources can be efficiently, autonomously, and dynamically allocated to virtualized Network Function (VNF) whose resource requirements ebb and flow. In this paper, we propose a graph neural Network-based algorithm which exploits VNF forwarding graph topology information to predict future resource requirements for each VNF component (VNFC). The topology information of each VNFC is derived from combining its past resource utilization as well as the modeled effect on the same from VNFCs in its neighborhood. Our proposal has been evaluated using a deployment of a virtualized IP multimedia subsystem, and real VoIP traffic traces, with results showing an average prediction accuracy of 90%, compared to 85% obtained while using traditional feed-forward neural Networks. Moreover, compared to a scenario where resources are allocated manually and/or statically, our technique reduces the average number of dropped calls by at least 27% and improves call setup latency by over 29%.
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elastic virtual Network Function placement
IEEE International Conference on Cloud Networking, 2015Co-Authors: Milad Ghaznavi, Aimal Khan, Nashid Shahriar, Khalid Alsubhi, Reaz Ahmed, Raouf BoutabaAbstract:Nowadays, many cloud providers offer Virtual Network Function (VNF) services that are dynamically scaled according to the workload. Enterprises enjoy these services by only paying for the actual consumed resources. From a cloud provider's standpoint, the cost of these services must be kept as low as possible, while QoS is maintained and service downtime is minimized. In this paper, we introduce Elastic Virtual Network Function Placement (EVNFP) problem and present a model for minimizing operational costs in providing VNF services. In this model, the elasticity overhead and the trade-off between bandwidth and host resource consumption are considered together, while the previous works ignored this perspective of the problem. We propose a solution called Simple Lazy Facility Location (SLFL) that optimizes the placement of VNF instances in response to on-demand workload. Our experiments suggest that SLFL can accept two times more workload while incurring similar operational cost compared to first-fit and random placements.
Ahmed N. Al-quzweeni - One of the best experts on this subject based on the ideXlab platform.
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Optimized Energy Aware 5G Network Function Virtualization
IEEE Access, 2019Co-Authors: Ahmed N. Al-quzweeni, Taisir E H Elgorashi, Ahmed Qasim Lawey, Jaafar M H ElmirghaniAbstract:In this paper, Network Function virtualization (NFV) is identified as a promising key technology, which can contribute to energy-efficiency improvement in 5G Networks. An optical Network supported architecture is proposed and investigated in this paper to provide the wired infrastructure needed in 5G Networks and to support NFV toward an energy efficient 5G Network. In this paper, the mobile core Network Functions, as well as baseband Function, are virtualized and provided as VMs. The impact of the total number of active users in the Network, backhaul/fronthaul configurations, and VM inter-traffic are investigated. A mixed integer linear programming (MILP) optimization model is developed with the objective of minimizing the total power consumption by optimizing the VMs location and VMs servers’ utilization. The MILP model results show that virtualization can result in up to 38% (average 34%) energy saving. The results also reveal how the total number of active users affects the baseband virtual machines (BBUVMs) optimal distribution whilst the core Network virtual machines (CNVMs) distribution is affected mainly by the inter-traffic between the VMs. For real-time implementation, two heuristics are developed, an energy efficient NFV without CNVMs inter-traffic (EENFVnoITr) heuristic and an energy efficient NFV with CNVMs inter-traffic (EENFVwithITr) heuristic, both produce comparable results to the optimal MILP results. Finally, a genetic algorithm is developed for further verification of the results.
