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1

Rüttimann-Johnson, Carmen, Luis M. Rubio, Dennis R. Dean, and Paul W. Ludden. "VnfY Is Required for Full Activity of the Vanadium-Containing Dinitrogenase in Azotobacter vinelandii." Journal of Bacteriology 185, no. 7 (April 1, 2003): 2383–86. http://dx.doi.org/10.1128/jb.185.7.2383-2386.2003.

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ABSTRACT A gene from Azotobacter vinelandii whose product exhibits primary sequence similarity to the NifY, NafY, NifX, and VnfX family of proteins, and which is required for effective V-dependent diazotrophic growth, was identified. Because this gene is located downstream from vnfK in an arrangement similar to the relative organization of the nifK and nifY genes, it was designated vnfY. A mutant strain having an insertion mutation in vnfY has 10-fold less vnf dinitrogenase activity and exhibits a greatly diminished level of 49V label incorporation into the V-dependent dinitrogenase when compared to the wild type. These results indicate that VnfY has a role in the maturation of the V-dependent dinitrogenase, with a specific role in the formation of the V-containing cofactor and/or its insertion into apodinitrogenase.
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2

Xuan, Hejun, Lei You, Zhenghui Liu, Yanling Li, and Xiaokai Yang. "HS-MOEA/D: An Oriented Algorithm for Delay and Reliability VNF-SC Deployment." Security and Communication Networks 2021 (August 24, 2021): 1–9. http://dx.doi.org/10.1155/2021/5538931.

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Network function virtualization (NFV) technology can realize on-demand distribution of network resources and improve network flexibility. It has become one of the key technologies for next-generation communications. Virtual network function service chain (VNF-SC) deployment is an important problem faced by network function virtualization technology. In this paper, the problem, VNF deployment for VNF-SC, is investigated. First, a two-objective mathematical model, which maximizes balancing and reliability of SFC, is established. In this model, VNFs are divided into two classes, i.e., part of required VNFs in each VNF-SC is dependent, others are independent. Second, harmony search-based MOEA/D (HS-MOEA/D) is proposed to solve the model effectively. In HS-MOEA/D, Chebyshev decomposition mechanism is used to transform multiobjective optimization problem into a series of single-objective optimization subproblems. A new evolutionary strategy is deeply studied in order to propose a new harmony search (HS) algorithm. Finally, to show high performance of the proposed algorithm, a large number of experiments are conducted. The simulation results show that the proposed algorithm enhances the reliability of SFC and reduces the end-to-end delay.
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3

Marchetto, Guido, Riccardo Sisto, Matteo Virgilio, and Jaloliddin Yusupov. "A VNF modeling approach for verification purposes." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 4 (August 1, 2019): 2627. http://dx.doi.org/10.11591/ijece.v9i4.pp2627-2636.

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<span lang="EN-US">Network Function Virtualization (NFV) architectures are emerging to increase networks flexibility. However, this renewed scenario poses new challenges, because virtualized networks, need to be carefully verified before being actually deployed in production environments in order to preserve network coherency (e.g., absence of forwarding loops, preservation of security on network traffic, etc.). Nowadays, model checking tools, SAT solvers, and Theorem Provers are available for formal verification of such properties in virtualized networks. Unfortunately, most of those verification tools accept input descriptions written in specification languages that are difficult to use for people not experienced in formal methods. Also, in order to enable the use of formal verification tools in real scenarios, vendors of Virtual Network Functions (VNFs) should provide abstract mathematical models of their functions, coded in the specific input languages of the verification tools. This process is error-prone, time-consuming, and often outside the VNF developers’ expertise. This paper presents a framework that we designed for automatically extracting verification models starting from a Java-based representation of a given VNF. It comprises a Java library of classes to define VNFs in a more developer-friendly way, and a tool to translate VNF definitions into formal verification models of different verification tools.</span>
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Sharma, Gourav Prateek, Wouter Tavernier, Didier Colle, and Mario Pickavet. "VNF-AAPC: Accelerator-aware VNF placement and chaining." Computer Networks 177 (August 2020): 107329. http://dx.doi.org/10.1016/j.comnet.2020.107329.

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5

Xu, Yansen, and Ved P. Kafle. "An Availability-Enhanced Service Function Chain Placement Scheme in Network Function Virtualization." Journal of Sensor and Actuator Networks 8, no. 2 (June 14, 2019): 34. http://dx.doi.org/10.3390/jsan8020034.

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A service function chain (SFC) is an ordered virtual network function (VNF) chain for processing traffic flows to deliver end-to-end network services in a virtual networking environment. A challenging problem for an SFC in this context is to determine where to deploy VNFs and how to route traffic between VNFs of an SFC on a substrate network. In this paper, we formulate an SFC placement problem as an integer linear programing (ILP) model, and propose an availability-enhanced VNF placing scheme based on the layered graphs approach. To improve the availability of SFC deployment, our scheme distributes VNFs of an SFC to multiple substrate nodes to avoid a single point of failure. We conduct numerical analysis and computer simulation to validate the feasibility of our SFC scheme. The results show that the proposed scheme outperforms well in different network scenarios in terms of end-to-end delay of the SFC and computation time cost.
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6

Wang, Juan, Yang Yu, Yi Li, Chengyang Fan, and Shirong Hao. "Design and Implementation of Virtual Security Function Based on Multiple Enclaves." Future Internet 13, no. 1 (January 6, 2021): 12. http://dx.doi.org/10.3390/fi13010012.

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Network function virtualization (NFV) provides flexible and scalable network function for the emerging platform, such as the cloud computing, edge computing, and IoT platforms, while it faces more security challenges, such as tampering with network policies and leaking sensitive processing states, due to running in a shared open environment and lacking the protection of proprietary hardware. Currently, Intel® Software Guard Extensions (SGX) provides a promising way to build a secure and trusted VNF (virtual network function) by isolating VNF or sensitive data into an enclave. However, directly placing multiple VNFs in a single enclave will lose the scalability advantage of NFV. This paper combines SGX and click technology to design the virtual security function architecture based on multiple enclaves. In our design, the sensitive modules of a VNF are put into different enclaves and communicate by local attestation. The system can freely combine these modules according to user requirements, and increase the scalability of the system while protecting its running state security. In addition, we design a new hot-swapping scheme to enable the system to dynamically modify the configuration function at runtime, so that the original VNFs do not need to stop when the function of VNFs is modified. We implement an IDS (intrusion detection system) based on our architecture to verify the feasibility of our system and evaluate its performance. The results show that the overhead introduced by the system architecture is within an acceptable range.
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7

Loveless, Telisa M., and Paul E. Bishop. "Identification of genes unique to Mo-independent nitrogenase systems in diverse diazotrophs." Canadian Journal of Microbiology 45, no. 4 (April 1, 1999): 312–17. http://dx.doi.org/10.1139/w99-007.

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A number of nitrogen-fixing bacteria were screened using PCR for genes (vnfG and anfG) unique to the V-containing nitrogenase (vnf) and the Fe-only nitrogenase (anf) systems. Products with sequences similar to that of vnfG were obtained from Azotobacter paspali and Azotobacter salinestris genomic DNAs, and products with sequences similar to that of anfG were obtained from Azomonas macrocytogenes, Rhodospirillum rubrum, and Azotobacter paspali DNAs. Phylogenetic analysis of the deduced amino acid sequences of anfG and vnfG genes shows that each gene product forms a distinct cluster. Furthermore, amplification of an internal 839-bp region in anfD and vnfD yielded a product similar to anfD from Heliobacterium gestii and a product similar to vnfD from Azotobacter paspali and Azotobacter salinestris. Phylogenetic analysis of NifD, VnfD, and AnfD amino acid sequences indicates that AnfD and VnfD sequences are more closely related to each other than either is to NifD. The results of this study suggest that Azotobacter salinestris possesses the potential to express the vanadium (V)-containing nitrogenase (nitrogenase 2) and that R. rubrum, Azomonas macrocytogenes, and H. gestii possess the potential to express the Fe-only nitrogenase (nitrogenase 3). Like Azotobacter vinelandii, Azotobacter paspali appears to have the potential to express both the V-containing nitrogenase and the Fe-only nitrogenase.Key words: Mo-independent nitrogenase systems, diverse diazotrophs, vnfG, anfG.
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8

Xuan, Hejun, Xuelin Zhao, Zhenghui Liu, Jianwei Fan, and Yanling Li. "Energy Efficiency Opposition-Based Learning and Brain Storm Optimization for VNF-SC Deployment in IoT." Wireless Communications and Mobile Computing 2021 (February 13, 2021): 1–9. http://dx.doi.org/10.1155/2021/6651112.

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Network Function Virtualization (NFV) can provide the resource according to the request and can improve the flexibility of the network. It has become the key technology of the Internet of Things (IoT). Resource scheduling for the virtual network function service chain (VNF-SC) is the key issue of the NFV. Energy consumption is an important indicator for the IoT; we take the energy consumption into the objective and define a novel objective to satisfying different objectives of the decision-maker. Due to the complexity of VNF-SC deployment problem, through taking into consideration of the heterogeneity of nodes (each node only can provide some specific VNFs), and the limitation of resources in each node, a novel optimal model is constructed to define the problem of VNF-SC deployment problem. To solve the optimization model effectively, a weighted center opposition-based learning is introduced to brainstorm optimization to find the optimal solution (OBLBSO). To show the efficiency of the proposed algorithm, numerous of simulation experiments have been conducted. Experimental results indicate that OBLBSO can improve the accuracy of the solution than compared algorithm.
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9

Qu, Hua, Ke Wang, and Jihong Zhao. "Reliable Service Function Chain Deployment Method Based on Deep Reinforcement Learning." Sensors 21, no. 8 (April 13, 2021): 2733. http://dx.doi.org/10.3390/s21082733.

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Network function virtualization (NFV) is a key technology to decouple hardware device and software function. Several virtual network functions (VNFs) combine into a function sequence in a certain order, that is defined as service function chain (SFC). A significant challenge is guaranteeing reliability. First, deployment server is selected to place VNF, then, backup server is determined to place the VNF as a backup which is running when deployment server is failed. Moreover, how to determine the accurate locations dynamically with machine learning is challenging. This paper focuses on resource requirements of SFC to measure its priority meanwhile calculates node priority by current resource capacity and node degree, then, a novel priority-awareness deep reinforcement learning (PA-DRL) algorithm is proposed to implement reliable SFC dynamically. PA-DRL determines the backup scheme of each VNF, then, the model jointly utilizes delay, load balancing of network as feedback factors to optimize the quality of service. In the experimental results, resource efficient utilization, survival rate, and load balancing of PA-DRL were improved by 36.7%, 35.1%, and 78.9% on average compared with benchmark algorithm respectively, average delay was reduced by 14.9%. Therefore, PA-DRL can effectively improve reliability and optimization targets compared with other benchmark methods.
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10

Vladislavić, Đani, Darko Huljenić, and Julije Ožegović. "Virtual Network Resource Optimization Model for Network Function Virtualization." Wireless Communications and Mobile Computing 2021 (August 17, 2021): 1–21. http://dx.doi.org/10.1155/2021/9928210.

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Network function virtualization (NFV) is a concept aimed at achieving telecom grade cloud ecosystem for new-generation networks focusing on capital and operational expenditure (CAPEX and OPEX) savings. This study introduces empirical throughput prediction model for the virtual network function (VNF) and network function virtualization infrastructure (NFVI) architectures based on Linux kernel. The model arises from the methodology for performance evaluation and modeling based on execution area (EA) distribution by CPU core pinning. EA is defined as a software execution unit that can run isolated on a compute resource (CPU core). EAs are derived from the elements and packet processing principles in NFVIs and VNFs based on Linux kernel. Performing measurements and observing linearity of the measured results open the possibility to apply model calibration technique to achieve general VNF and NFVI architecture model with performance prediction and environment setup optimization. The modeling parameters are derived from the cumulative packet processing cost obtained by measurements for collocated EAs on the CPU core hosting the bottleneck EA. The VNF and NFVI architecture model with performance prediction is successfully validated against the measurement results obtained in emulated environment and used to predict optimal system configurations and maximal throughput results for different CPUs.
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11

Berekashvili, Ketevan, Alicia M. Zha, Mohammed Abdel-Al, Xu Zhang, Jazba H. Soomro, Samuel J. Prater, and James C. Grotta. "Emergency Medicine Physicians Accurately Select Acute Stroke Patients for Tissue-Type Plasminogen Activator Treatment Using a Checklist." Stroke 51, no. 2 (February 2020): 663–65. http://dx.doi.org/10.1161/strokeaha.119.026948.

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Background and Purpose— There is uncertainty among many emergency medicine physicians about the decision to give intravenous tPA (tissue-type plasminogen activator), which limits its use. A checklist approach has been suggested as a solution. We compared agreement on tPA treatment in suspected acute ischemic stroke patients between emergency medicine residents (EMRs) using a checklist and vascular neurology fellows (VNFs). Methods— Every suspected acute stroke patient brought to our comprehensive stroke center emergency room within 4.5 hours from symptom onset was prospectively evaluated simultaneously and independently by VNFs and EMRs. The latter used a tPA screening checklist, which included guideline exclusion criteria to help with their treatment decision. Agreement was determined using kappa (k) statistics. Results— Over 6 months, 60 patients were enrolled; 10% large vessel atherosclerosis, 18% cardioembolism, 12% small vessel, 12% cryptogenic, and 47% mimic. Forty-two percent were deemed tPA eligible by the EMR, 30% by the VNF, and 37% by the vascular neurology faculty. There were no complications in any tPA-treated patients. Agreement was substantial between EMR and VNF (κ=0.68 [95% CI, 0.49–0.87]) and between EMR and vascular neurology faculty (κ=0.69 [95% CI, 0.50–0.87]). Stroke mimics were the main cause of disagreement between EMR and VNF (κ=0.24 [95% CI, −0.15 to 0.63]) and between EMR and vascular neurology faculty (κ=0.35 [95% CI, −0.08 to 0.78]). Conclusions— Our data suggest that with the aid of a checklist, EMRs can accurately treat stroke patients with tPA. Areas for improvement include recognition of stroke mimics. Further studies are warranted to evaluate checklist-enhanced tPA treatment to allay emergency medicine physician uncertainty and expand the use of tPA.
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12

Abdelaal, Marwa A., Gamal A. Ebrahim, and Wagdy R. Anis. "Efficient Placement of Service Function Chains in Cloud Computing Environments." Electronics 10, no. 3 (January 30, 2021): 323. http://dx.doi.org/10.3390/electronics10030323.

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The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.
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13

Chetty, Swarna Bindu, Hamed Ahmadi, Sachin Sharma, and Avishek Nag. "Virtual Network Function Embedding under Nodal Outage Using Deep Q-Learning." Future Internet 13, no. 3 (March 23, 2021): 82. http://dx.doi.org/10.3390/fi13030082.

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With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards efficient management of such complex networks, by virtualizing network functions and placing them on shared commodity servers. However, one of the critical issues in NFV is the resource allocation for the highly complex services; moreover, this problem is classified as an NP-Hard problem. To solve this problem, our work investigates the potential of Deep Reinforcement Learning (DRL) as a swift yet accurate approach (as compared to integer linear programming) for deploying Virtualized Network Functions (VNFs) under several Quality-of-Service (QoS) constraints such as latency, memory, CPU, and failure recovery requirements. More importantly, the failure recovery requirements are focused on the node-outage problem where outage can be either due to a disaster or unavailability of network topology information (e.g., due to proprietary and ownership issues). In DRL, we adopt a Deep Q-Learning (DQL) based algorithm where the primary network estimates the action-value function Q, as well as the predicted Q, highly causing divergence in Q-value’s updates. This divergence increases for the larger-scale action and state-space causing inconsistency in learning, resulting in an inaccurate output. Thus, to overcome this divergence, our work has adopted a well-known approach, i.e., introducing Target Neural Networks and Experience Replay algorithms in DQL. The constructed model is simulated for two real network topologies—Netrail Topology and BtEurope Topology—with various capacities of the nodes (e.g., CPU core, VNFs per Core), links (e.g., bandwidth and latency), several VNF Forwarding Graph (VNF-FG) complexities, and different degrees of the nodal outage from 0% to 50%. We can conclude from our work that, with the increase in network density or nodal capacity or VNF-FG’s complexity, the model took extremely high computation time to execute the desirable results. Moreover, with the rise in complexity of the VNF-FG, the resources decline much faster. In terms of the nodal outage, our model provided almost 70–90% Service Acceptance Rate (SAR) even with a 50% nodal outage for certain combinations of scenarios.
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Dwiardhika, Dhanu, and Takuji Tachibana. "Virtual Network Embedding Based on Security Level with VNF Placement." Security and Communication Networks 2019 (February 3, 2019): 1–11. http://dx.doi.org/10.1155/2019/5640134.

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In this paper, in order to embed virtual networks by considering network security, we propose a virtual network embedding based on security level with VNF placement. In this method, virtual networks are embedded in a substrate network by considering security and some security VNFs are placed in order to increase the security level of substrate networks. By using our proposed method, many virtual networks can be embedded by considering security level. As a result, the reward can be increased and the cost of placing VNFs is not increased so much. We evaluate the performance of our proposed method with simulation. The performance of this method is compared with the performance of a method that places VNFs randomly and the performance of a method without placing VNFs. From numerical examples, we investigate the effectiveness of this method. In numerical examples, we show that the proposed method is effective in embedding virtual networks by considering network security.
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15

Eramo, V., A. Tosti, and E. Miucci. "Server Resource Dimensioning and Routing of Service Function Chain in NFV Network Architectures." Journal of Electrical and Computer Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/7139852.

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The Network Function Virtualization (NFV) technology aims at virtualizing the network service with the execution of the single service components in Virtual Machines activated on Commercial-off-the-shelf (COTS) servers. Any service is represented by the Service Function Chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFI) that in general are software components executed on Virtual Machines. In this paper we cope with the routing and resource dimensioning problem in NFV architectures. We formulate the optimization problem and due to its NP-hard complexity, heuristics are proposed for both cases of offline and online traffic demand. We show how the heuristics works correctly by guaranteeing a uniform occupancy of the server processing capacity and the network link bandwidth. A consolidation algorithm for the power consumption minimization is also proposed. The application of the consolidation algorithm allows for a high power consumption saving that however is to be paid with an increase in SFC blocking probability.
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Elvidge, Christopher, Mikhail Zhizhin, Kimberly Baugh, Feng Hsu, and Tilottama Ghosh. "Extending Nighttime Combustion Source Detection Limits with Short Wavelength VIIRS Data." Remote Sensing 11, no. 4 (February 15, 2019): 395. http://dx.doi.org/10.3390/rs11040395.

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The Visible Infrared Imaging Radiometer Suite (VIIRS) collects low light imaging data at night in five spectral bands. The best known of these is the day/night band (DNB) which uses light intensification for imaging of moonlit clouds in the visible and near-infrared (VNIR). The other four low light imaging bands are in the NIR and short-wave infrared (SWIR), designed for daytime imaging, which continue to collect data at night. VIIRS nightfire (VNF) tests each nighttime pixel for the presence of sub-pixel IR emitters across six spectral bands with two bands each in three spectral ranges: NIR, SWIR, and MWIR. In pixels with detection in two or more bands, Planck curve fitting leads to the calculation of temperature, source area, and radiant heat using physical laws. An analysis of January 2018 global VNF found that inclusion of the NIR and SWIR channels results in a doubling of the VNF pixels with temperature fits over the detection numbers involving the MWIR. The addition of the short wavelength channels extends detection limits to smaller source areas across a broad range of temperatures. The VIIRS DNB has even lower detection limits for combustion sources, reaching 0.001 m2 at 1800 K, a typical temperature for a natural gas flare. Comparison of VNF tallies and DNB fire detections in a 2015 study area in India found the DNB had 15 times more detections than VNF. The primary VNF error sources are false detections from high energy particle detections (HEPD) in space and radiance saturation on some of the most intense events. The HEPD false detections are largely eliminated in the VNF output by requiring multiband detections for the calculation of temperature and source size. Radiance saturation occurs in about 1% of the VNF detections and occurs primarily in the M12 spectral band. Inclusion of the radiances affected by saturation results in temperature and source area calculation errors. Saturation is addressed by identifying the presence of saturation and excluding those radiances from the Planck curve fitting. The extremely low detection limits for the DNB indicates that a DNB fire detection algorithm could reveal vast numbers of combustion sources that are undetectable in longer wavelength VIIRS data. The caveats with the DNB combustion source detection capability is that it should be restricted to pixels that are outside the zone of known VIIRS detected electric lighting.
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Ruiz, Lidia, Ramón Durán, Ignacio de Miguel, Pouria Khodashenas, Jose-Juan Pedreño-Manresa, Noemí Merayo, Juan Aguado, et al. "A Genetic Algorithm for VNF Provisioning in NFV-Enabled Cloud/MEC RAN Architectures." Applied Sciences 8, no. 12 (December 13, 2018): 2614. http://dx.doi.org/10.3390/app8122614.

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5G technologies promise to bring new network and service capacities and are expected to introduce significant architectural and service deployment transformations. The Cloud-Radio Access Networks (C-RAN) architecture, enabled by the combination of Software Defined Networking (SDN), Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) technologies, play a key role in the development of 5G. In this context, this paper addresses the problems of Virtual Network Functions (VNF) provisioning (VNF-placement and service chain allocation) in a 5G network. In order to solve that problem, we propose a genetic algorithm that, considering both computing resources and optical network capacity, minimizes both the service blocking rate and CPU usage. In addition, we present an algorithm extension that adds a learning stage and evaluate the algorithm performance benefits in those scenarios where VNF allocations can be reconfigured. Results reveal and quantify the advantages of reconfiguring the VNF mapping depending on the current demands. Our methods outperform previous proposals in the literature, reducing the service blocking ratio while saving energy by reducing the number of active core CPUs.
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Rafiq, Adeel, Asif Mehmood, Talha Ahmed Khan, Khizar Abbas, Muhammad Afaq, and Wang-Cheol Song. "Intent-Based End-to-End Network Service Orchestration System for Multi-Platforms." Sustainability 12, no. 7 (April 1, 2020): 2782. http://dx.doi.org/10.3390/su12072782.

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On-demand service is the main feature of the 5G network, and Network Function Virtualization (NFV) provides it by virtualizing the existing 5G network infrastructure. NFV crafts various virtual networks on a shared physical network, but one of the core challenges in future 5G networks is to automate the modeling of Virtualized Network Functions (VNFs) and end-to-end Network Service (NS) orchestration with less human interaction. Traditionally, the descriptor of VNF and NS is created manually, which requires expert-level skills. This manual approach has a big threat of human error, which can be avoided by using the Intent-Based Networking (IBN) approach. The IBN approach eliminates the requirement of expertise for designing VNFs and NS by taking users’ intentions as an input. In this paper, the proposed system presents the Intent Management System for VNF modeling and end-to-end NS orchestration for multi-platforms. This system takes the high-level information related to a specific service, configures it accordingly, and converts it into the selected platform. The proposed system is tested using Mobile Central Office Re-architected as Data Center (M-CORD) and Open-Source Management and Orchestration (OSM) orchestrators. The results section shows that the proposed system reduces the effort of the end-user in creating network slices and provides seamless end-to-end service orchestration.
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Wu, Xing, Jing Duan, Mingyu Zhong, Peng Li, and Jianjia Wang. "VNF Chain Placement for Large Scale IoT of Intelligent Transportation." Sensors 20, no. 14 (July 8, 2020): 3819. http://dx.doi.org/10.3390/s20143819.

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With the advent of the Internet of things (IoT), intelligent transportation has evolved over time to improve traffic safety and efficiency as well as to reduce congestion and environmental pollution. However, there are some challenging issues to be addressed so that it can be implemented to its full potential. The major challenge in intelligent transportation is that vehicles and pedestrians, as the main types of edge nodes in IoT infrastructure, are on the constant move. Hence, the topology of the large scale network is changing rapidly over time and the service chain may need reestablishment frequently. Existing Virtual Network Function (VNF) chain placement methods are mostly good at static network topology and any evolvement of the network requires global computation, which leads to the inefficiency in computing and the waste of resources. Mapping the network topology to a graph, we propose a novel VNF placement method called BVCP (Border VNF Chain Placement) to address this problem by elaborately dividing the graph into multiple subgraphs and fully exploiting border hypervisors. Experimental results show that BVCP outperforms the state-of-the-art method in VNF chain placement, which is highly efficient in large scale IoT of intelligent transportation.
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20

Liu, Yanyang, Jing Ran, Hefei Hu, and Bihua Tang. "Energy-Efficient Virtual Network Function Reconfiguration Strategy Based on Short-Term Resources Requirement Prediction." Electronics 10, no. 18 (September 17, 2021): 2287. http://dx.doi.org/10.3390/electronics10182287.

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In Network Function Virtualization, the resource demand of the network service evolves with the change of network traffic. VNF dynamic migration has become an effective method to improve network performance. However, for the time-varying resource demand, how to minimize the long-term energy consumption of the network while guaranteeing the Service Level Agreement (SLA) is the key issue that lacks previous research. To tackle this dilemma, this paper proposes an energy-efficient reconfiguration algorithm for VNF based on short-term resource requirement prediction (RP-EDM). Our algorithm uses LSTM to predict VNF resource requirements in advance to eliminate the lag of dynamic migration and determines the timing of migration. RP-EDM eliminates SLA violations by performing VNF separation on potentially overloaded servers and consolidates low-load servers timely to save energy. Meanwhile, we consider the power consumption of servers when booting up, which is existing objectively, to avoid switching on/off the server frequently. The simulation results suggest that RP-EDM has a good performance and stability under machine learning models with different accuracy. Moreover, our algorithm increases the total service traffic by about 15% while ensuring a low SLA interruption rate. The total energy cost is reduced by more than 20% compared with the existing algorithms.
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Toscano, Luciana C., Arlindo L. Boiça Júnior, Jaime Maia Santos, and João B. S. A. Almeida. "Tipos de tricomas em genótipos de Lycopersicon." Horticultura Brasileira 19, no. 3 (November 2001): 336–38. http://dx.doi.org/10.1590/s0102-05362001000300009.

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Foram identificados os tipos de tricomas em alguns genótipos de Lycopersicon, utilizando microscópio eletrônico de varredura. Foram utilizados os genótipos L. hirsutum (PI 127826 e PI 127827), L. hirsutum var. glabratum (PI 134417), L. pennellii (LA 716) e L. esculentum (híbrido Bruna VFN e Santa Clara). Os tricomas glandulares encontrados foram tipo IV em LA 716, PI 127826, PI 127827 e PI 134417; tipo VIc em PI 127826, PI 127827, PI 134417 e Santa Clara; tipo VII em PI 127826, PI 127827 e PI 134417; tipo I em PI 127826, PI 127827, PI 134417, híbrido Bruna VFN e Santa Clara; tipo VIa em híbrido Bruna VFN. Os tricomas não glandulares observados foram: tipo Va em PI 127826, PI 127827, PI 134417, híbrido Bruna VFN e Santa Clara; VIII em híbrido Bruna VNF e os tipos III e Vb em Santa Clara.
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Houidi, Omar, Oussama Soualah, Wajdi Louati, and Djamal Zeghlache. "Dynamic VNF Forwarding Graph Extension Algorithms." IEEE Transactions on Network and Service Management 17, no. 3 (September 2020): 1389–402. http://dx.doi.org/10.1109/tnsm.2020.2990815.

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Nelson, Jessica M., Duncan A. Hauser, José A. Gudiño, Yessenia A. Guadalupe, John C. Meeks, Noris Salazar Allen, Juan Carlos Villarreal, and Fay-Wei Li. "Complete Genomes of Symbiotic Cyanobacteria Clarify the Evolution of Vanadium-Nitrogenase." Genome Biology and Evolution 11, no. 7 (June 27, 2019): 1959–64. http://dx.doi.org/10.1093/gbe/evz137.

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Abstract Plant endosymbiosis with nitrogen-fixing cyanobacteria has independently evolved in diverse plant lineages, offering a unique window to study the evolution and genetics of plant–microbe interaction. However, very few complete genomes exist for plant cyanobionts, and therefore little is known about their genomic and functional diversity. Here, we present four complete genomes of cyanobacteria isolated from bryophytes. Nanopore long-read sequencing allowed us to obtain circular contigs for all the main chromosomes and most of the plasmids. We found that despite having a low 16S rRNA sequence divergence, the four isolates exhibit considerable genome reorganizations and variation in gene content. Furthermore, three of the four isolates possess genes encoding vanadium (V)-nitrogenase (vnf), which is uncommon among diazotrophs and has not been previously reported in plant cyanobionts. In two cases, the vnf genes were found on plasmids, implying possible plasmid-mediated horizontal gene transfers. Comparative genomic analysis of vnf-containing cyanobacteria further identified a conserved gene cluster. Many genes in this cluster have not been functionally characterized and would be promising candidates for future studies to elucidate V-nitrogenase function and regulation.
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Khoshkholghi, Mohammad Ali, Michel Gokan Khan, Kyoomars Alizadeh Noghani, Javid Taheri, Deval Bhamare, Andreas Kassler, Zhengzhe Xiang, Shuiguang Deng, and Xiaoxian Yang. "Service Function Chain Placement for Joint Cost and Latency Optimization." Mobile Networks and Applications 25, no. 6 (November 21, 2020): 2191–205. http://dx.doi.org/10.1007/s11036-020-01661-w.

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AbstractNetwork Function Virtualization (NFV) is an emerging technology to consolidate network functions onto high volume storages, servers and switches located anywhere in the network. Virtual Network Functions (VNFs) are chained together to provide a specific network service, called Service Function Chains (SFCs). Regarding to Quality of Service (QoS) requirements and network features and states, SFCs are served through performing two tasks: VNF placement and link embedding on the substrate networks. Reducing deployment cost is a desired objective for all service providers in cloud/edge environments to increase their profit form demanded services. However, increasing resource utilization in order to decrease deployment cost may lead to increase the service latency and consequently increase SLA violation and decrease user satisfaction. To this end, we formulate a multi-objective optimization model to joint VNF placement and link embedding in order to reduce deployment cost and service latency with respect to a variety of constraints. We, then solve the optimization problem using two heuristic-based algorithms that perform close to optimum for large scale cloud/edge environments. Since the optimization model involves conflicting objectives, we also investigate pareto optimal solution so that it optimizes multiple objectives as much as possible. The efficiency of proposed algorithms is evaluated using both simulation and emulation. The evaluation results show that the proposed optimization approach succeed in minimizing both cost and latency while the results are as accurate as optimal solution obtained by Gurobi (5%).
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Fan, Hongwei, Yuxiang Hu, Shaojun Zhang, and Quan Ren. "Hardware Acceleration Resource Allocation Mechanism for VNF." Procedia Computer Science 131 (2018): 746–55. http://dx.doi.org/10.1016/j.procs.2018.04.320.

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Yi, Bo, Xingwei Wang, and Min Huang. "Optimised approach for VNF embedding in NFV." IET Communications 12, no. 20 (December 20, 2018): 2630–38. http://dx.doi.org/10.1049/iet-com.2018.5509.

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Zheng, Gao, Anthony Tsiopoulos, and Vasilis Friderikos. "Optimal VNF Chains Management for Proactive Caching." IEEE Transactions on Wireless Communications 17, no. 10 (October 2018): 6735–48. http://dx.doi.org/10.1109/twc.2018.2863685.

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Bo, Wang, and Odini Marie-Paule. "Lightweight VNF Manager Solution for Virtual Functions." Journal of ICT Standardization 3, no. 1 (2015): 91–104. http://dx.doi.org/10.13052/jicts2245-800x.315.

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Malandrino, Francesco, Carla Fabiana Chiasserini, Gil Einziger, and Gabriel Scalosub. "Reducing Service Deployment Cost Through VNF Sharing." IEEE/ACM Transactions on Networking 27, no. 6 (December 2019): 2363–76. http://dx.doi.org/10.1109/tnet.2019.2945127.

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Nguyen, Tri-Hai, and Myungsik Yoo. "A VNF Placement Optimization Framework for Network Function Virtualization." Journal of Korean Institute of Communications and Information Sciences 44, no. 10 (October 31, 2019): 1956–60. http://dx.doi.org/10.7840/kics.2019.44.10.1956.

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Manzanares-Lopez, Pilar, Juan Pedro Muñoz-Gea, and Josemaria Malgosa-Sanahuja. "VNF Placement for Service Function Chains with Strong Low-Delay Restrictions in Edge Computing Networks." Applied Sciences 10, no. 18 (September 20, 2020): 6573. http://dx.doi.org/10.3390/app10186573.

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The edge computing paradigm, allowing the location of network services close to end users, defines new network scenarios. One of them considers the existence of micro data centers, with reduced resources but located closer to service requesters, to complement remote cloud data centers. This hierarchical and geo-distributed architecture allows the definition of different time constraints that can be taken into account when mapping services into data centers. This feature is especially useful in the Virtual Network Function (VNF) placement problem, where the network functions composing a Service Function Chain (SFC) may require more or less strong delay restrictions. We propose the ModPG (Modified Priority-based Greedy) heuristic, a VNF placement solution that weighs the latency, bandwidth, and resource restrictions, but also the instantiation cost of VNFs. ModPG is an improved solution of a previous proposal (called PG). Although both heuristics share the same optimization target, that is the reduction of the total substrate resource cost, the ModPG heuristic identifies and solves a limitation of the PG solution: the mapping of sets of SFCs that include a significant proportion of SFC requests with strong low-delay restrictions. Unlike PG heuristic performance evaluation, where the amount of SFC requests with strong low-delay restrictions is not considered as a factor to be analyzed, in this work, both solutions are compared considering the presence of 1%, 15%, and 25% of this type of SFC request. Results show that the ModPG heuristic optimizes the target cost similarly to the original proposal, and at the same time, it offers a better performance when a significant number of low-delay demanding SFC requests are present.
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Leivadeas, Aris, George Kesidis, Mohamed Ibnkahla, and Ioannis Lambadaris. "VNF Placement Optimization at the Edge and Cloud †." Future Internet 11, no. 3 (March 9, 2019): 69. http://dx.doi.org/10.3390/fi11030069.

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Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers’ goal of low deployment costs.
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Zhou, Xinhao, Bo Yi, Xingwei Wang, and Min Huang. "Approach for minimising network effect of VNF migration." IET Communications 12, no. 20 (December 20, 2018): 2574–81. http://dx.doi.org/10.1049/iet-com.2018.5188.

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Yi, Bo, Xingwei Wang, and Min Huang. "A Generalized VNF Sharing Approach for Service Scheduling." IEEE Communications Letters 22, no. 1 (January 2018): 73–76. http://dx.doi.org/10.1109/lcomm.2017.2761874.

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Tahmasbi Nejad, Mohammad Ali, Saeedeh Parsaeefard, Mohammad Ali Maddah-Ali, Toktam Mahmoodi, and Babak Hossein Khalaj. "vSPACE: VNF Simultaneous Placement, Admission Control and Embedding." IEEE Journal on Selected Areas in Communications 36, no. 3 (March 2018): 542–57. http://dx.doi.org/10.1109/jsac.2018.2815318.

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Yao, Yifu, Songtao Guo, Pan Li, Guiyan Liu, and Yue Zeng. "Forecasting assisted VNF scaling in NFV-enabled networks." Computer Networks 168 (February 2020): 107040. http://dx.doi.org/10.1016/j.comnet.2019.107040.

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Tao, Xiaoyi, Kaoru Ota, Mianxiong Dong, Heng Qi, and Keqiu Li. "Cost as Performance: VNF Placement at the Edge." IEEE Networking Letters 3, no. 2 (June 2021): 70–74. http://dx.doi.org/10.1109/lnet.2021.3065651.

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38

Dinh, Ngoc-Thanh, and Younghan Kim. "An Efficient Availability Guaranteed Deployment Scheme for IoT Service Chains over Fog-Core Cloud Networks." Sensors 18, no. 11 (November 15, 2018): 3970. http://dx.doi.org/10.3390/s18113970.

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High availability is one of the important requirements of many end-to-end services in the Internet of Things (IoT). This is a critical issue in network function virtualization (NFV) and NFV-enabled service function chaining (SFC) due to hard- and soft-ware failures. Thus, merely mapping primary VNFs is not enough to ensure high availability, especially for SFCs deployed over fog - core cloud networks due to resource limitations of fogs. As a result, additional protection schemes, like VNF redundancy deployments, are required to improve the availability of SFCs to meet predefined requirements. With limited resources of fog instances, a cost-efficient protection scheme is required. This paper proposes a cost-efficient availability guaranteed deployment scheme for IoT services over fog-core cloud networks based on measuring the improvement potential of VNFs for improving the availability of SFCs. In addition, various techniques for redundancy placement for VNFs at the fog layer are also presented. Obtained analysis and simulation results show that the proposed scheme achieves a significant improvement in terms of the cost efficiency and scalability compared to the state-of-the-art approaches.
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Naidu, D. J. Samatha, and G. Hima Bindu. "INVESTIGATION ON ONLINE VNF SCALING IN A CLOUD DATACENTER USING ILP." International Journal of Computer Science and Mobile Computing 10, no. 8 (August 30, 2021): 32–35. http://dx.doi.org/10.47760/ijcsmc.2021.v10i08.005.

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NFV is the advanced technology in present situation. Online VNF Scaling in a cloud datacenter under multi-resource constraints were consider for formulating mathematical model. A new novel ILP Scaling algorithm works based on the regularization technique and dependent rounding.
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40

Nixon, N. L., P. F. Liddle, G. Worwood, M. Liotti, and E. Nixon. "Prefrontal cortex function in remitted major depressive disorder." Psychological Medicine 43, no. 6 (October 1, 2012): 1219–30. http://dx.doi.org/10.1017/s0033291712002164.

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BackgroundRecent models of major depressive disorder (MDD) have proposed the rostral anterior cingulate (rACC) and dorsomedial prefrontal cortex (dmPFC) as nexus sites in the dysfunctional regulation of cognitive-affective state. Limited evidence from remitted-state MDD supports these theories by suggesting that aberrant neural activity proximal to the rACC and the dmPFC may play a role in vulnerability to recurrence/relapse within this disorder. Here we present a targeted analysis assessing functional activity within these two regions of interest (ROIs) for groups with identified vulnerability to MDD: first, remitted, high predicted recurrence-risk patients; and second, patients suffering observed 1-year recurrence.MethodBaseline T2* images sensitive to blood oxygen level-dependent (BOLD) contrast were acquired from patients and controls during a Go/No-Go (GNG) task incorporating negative feedback, with 1-year patient follow-up to identify recurrence. BOLD contrast data for error commission (EC) and visual negative feedback (VNF) were used in an ROI analysis based on rACC and dmPFC coordinates from the literature, comparing patientsversuscontrols and recurrenceversusnon-recurrenceversuscontrol groups.ResultsAnalysis of patients (n = 20)versuscontrols (n = 20) showed significant right dmPFC [Brodmann area (BA) 9] hypoactivity within the patient group, co-localized during EC and VNF, with additional significant rACC (BA 32) hypoactivity during EC. The results from the follow-up analysis were undermined by small groups and potential confounders but suggested persistent right dmPFC (BA 9) hypoactivity associated with 1-year recurrence.ConclusionsConvergent hypoactive right dmPFC (BA 9) processing of VNF and EC, possibly impairing adaptive reappraisal of negative experience, was associated most clearly with clinically predicted vulnerability to MDD.
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Oda, Yasuhiro, Sudip K. Samanta, Federico E. Rey, Liyou Wu, Xiudan Liu, Tingfen Yan, Jizhong Zhou, and Caroline S. Harwood. "Functional Genomic Analysis of Three Nitrogenase Isozymes in the Photosynthetic Bacterium Rhodopseudomonas palustris." Journal of Bacteriology 187, no. 22 (November 15, 2005): 7784–94. http://dx.doi.org/10.1128/jb.187.22.7784-7794.2005.

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ABSTRACT The photosynthetic bacterium Rhodopseudomonas palustris is one of just a few prokaryotes described so far that has vnf and anf genes for alternative vanadium cofactor (V) and iron cofactor (Fe) nitrogenases in addition to nif genes for a molybdenum cofactor (Mo) nitrogenase. Transcriptome data indicated that the 32 genes in the nif gene cluster, but not the anf or vnf genes, were induced in wild-type and Mo nitrogenase-expressing strains grown under nitrogen-fixing conditions in Mo-containing medium. Strains that were unable to express a functional Mo nitrogenase due to mutations in Mo nitrogenase structural genes synthesized functional V and Fe nitrogenases and expressed vnf and anf genes in nitrogen-fixing growth media that contained Mo and V at concentrations far in excess of those that repress alternative nitrogenase gene expression in other bacteria. Thus, not only does R. palustris have multiple enzymatic options for nitrogen fixation, but in contrast to reports on other nitrogen-fixing bacteria, the expression of its alternative nitrogenases is not repressed by transition metals. Between 95 and 295 genes that are not directly associated with nitrogenase synthesis and assembly were induced under nitrogen-fixing conditions, depending on which nitrogenase was being used by R. palustris. Genes for nitrogen acquisition were expressed at particularly high levels during alternative nitrogenase-dependent growth. This suggests that alternative nitrogenase-expressing cells are relatively starved for nitrogen and raises the possibility that fixed nitrogen availability may be the primary signal that controls the synthesis of the V and Fe nitrogenases.
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42

Velusamy, Gandhimathi, and Ricardo Lent. "Smart Site Diversity for a High Throughput Satellite System with Software-Defined Networking and a Virtual Network Function." Future Internet 12, no. 12 (December 7, 2020): 225. http://dx.doi.org/10.3390/fi12120225.

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High Throughput Satellite (HTS) systems aim to push data rates to the order of Terabit/s, making use of Extremely High Frequencies (EHF) or free-space optical (FSO) in the feeder links. However, one challenge that needs to be addressed is that the use of such high frequencies makes the feeder links vulnerable to atmospheric conditions, which can effectively disable channels at times or temporarily increases the bit error rates. One way to cope with the problem is to introduce site diversity and to forward the data through the gateways not affected, or at least less constrained, by adverse conditions. In this paper, a virtual network function (VNF) introduced through reinforcement learning defines a smart routing service for an HTS system. Experiments were conducted on an emulated ground-satellite system in CloudLab, testing a VNF implementation of the approach with software-defined networking virtual switches, which indicate the expected performance of the proposed method.
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Yi, Bo, Xingwei Wang, Min Huang, and Kexin Li. "Design and Implementation of Network-Aware VNF Migration Mechanism." IEEE Access 8 (2020): 44346–58. http://dx.doi.org/10.1109/access.2020.2978002.

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44

Qi, Dandan, Subin Shen, and Guanghui Wang. "Towards an efficient VNF placement in network function virtualization." Computer Communications 138 (April 2019): 81–89. http://dx.doi.org/10.1016/j.comcom.2019.03.005.

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Van Rossem, Steven, Wouter Tavernier, Didier Colle, Mario Pickavet, and Piet Demeester. "VNF Performance modelling: From stand-alone to chained topologies." Computer Networks 181 (November 2020): 107428. http://dx.doi.org/10.1016/j.comnet.2020.107428.

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Wu, Yunyi, Weichang Zheng, Yongbing Zhang, and Jie Li. "Reliability-Aware VNF Placement Using a Probability-Based Approach." IEEE Transactions on Network and Service Management 18, no. 3 (September 2021): 2478–91. http://dx.doi.org/10.1109/tnsm.2021.3093199.

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Nguyen, Tri-Hai, and Myungsik Yoo. "Workflow Policy-Based VNF Monitoring Model in Tacker-Based NFV System." Journal of Korean Institute of Communications and Information Sciences 43, no. 9 (September 30, 2018): 1483–88. http://dx.doi.org/10.7840/kics.2018.43.9.1483.

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48

Bruschi, Roberto, Alessandro Carrega, and Franco Davoli. "A Game for Energy-Aware Allocation of Virtualized Network Functions." Journal of Electrical and Computer Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4067186.

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Network Functions Virtualization (NFV) is a network architecture concept where network functionality is virtualized and separated into multiple building blocks that may connect or be chained together to implement the required services. The main advantages consist of an increase in network flexibility and scalability. Indeed, each part of the service chain can be allocated and reallocated at runtime depending on demand. In this paper, we present and evaluate an energy-aware Game-Theory-based solution for resource allocation of Virtualized Network Functions (VNFs) within NFV environments. We consider each VNF as a player of the problem that competes for the physical network node capacity pool, seeking the minimization of individual cost functions. The physical network nodes dynamically adjust their processing capacity according to the incoming workload, by means of an Adaptive Rate (AR) strategy that aims at minimizing the product of energy consumption and processing delay. On the basis of the result of the nodes’ AR strategy, the VNFs’ resource sharing costs assume a polynomial form in the workflows, which admits a unique Nash Equilibrium (NE). We examine the effect of different (unconstrained and constrained) forms of the nodes’ optimization problem on the equilibrium and compare the power consumption and delay achieved with energy-aware and non-energy-aware strategy profiles.
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TABOTA, Kohei, and Takuji TACHIBANA. "Greedy-Based VNF Placement Algorithm for Dynamic Multipath Service Chaining." IEICE Transactions on Communications E102.B, no. 3 (March 1, 2019): 429–38. http://dx.doi.org/10.1587/transcom.2018nvp0006.

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Gao, Tao, Xin Li, Yu Wu, Weixia Zou, Shanguo Huang, Massimo Tornatore, and Biswanath Mukherjee. "Cost-Efficient VNF Placement and Scheduling in Public Cloud Networks." IEEE Transactions on Communications 68, no. 8 (August 2020): 4946–59. http://dx.doi.org/10.1109/tcomm.2020.2992504.

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