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Network Function Virtualization (NFV) is an enabling technology that brings together automated network service management and corresponding virtualized network functions that use an NFV Infrastructure (NFVI) framework. The Virtual Network Function Manager (VNFM) placement in a large-scale distributed NFV deployment is therefore a challenging task d...
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... performance is measured based on the criterion function, as it includes two metrics: the compute resource cost and LCM cost. The bandwidth consumption of LCM is bigger than the value, and the placement is favored in minimizing the LCM cost, as represented in Table 4. The uniformity in bandwidth cost over communication links in NFVI-PoPs translates the additional placement of VNFM on NFVI for managing VNF instances. ...Citations
... They also explore the challenges and solutions for deploying and optimizing networks to support these services. For example, the authors in [26,27] analyze the resources division and resource division mechanism of the 5G communication network to support different business models. Finally, Security and Interoperability, described in [28], focuses on understanding the security challenges and solutions for URLLC, eMBB, and mMTC services, including blockchain and other secure communications technologies. ...
This research work analyzes economic alternatives for the provision of ultra-reliable low latency communication (URLLC) and enhanced mobile broadband (eMBB) services by mobile network operators over the same fifth-generation (5G) network. Two business models are proposed to provide the two services to end users. Concretely, a monopoly is a single operator who offers both services, and a duopoly is two different operators that share network resources and offer one service each. In addition, two types of network scenarios for resource sharing are studied. Specifically, a shared network (SN) is a type of network scenario allowing resources to be shared between the two services without priority. A differentiated network (DN) is a type of network scenario that allows resources to be shared between the two services with a priority to URLLC service using network slicing (NS). Regarding the economic aspects, the incentive is modeled through the user’s utility and the operator’s benefit. At the same time, game theory is used to model the strategic interaction between users and operators, and queuing theory is used to model the interaction between the two services. We conclude that the monopoly social welfare (SW) is closer to the SW of the social optimum than the duopoly SW. In addition, the DN scenario to offer the services through NS is more suitable than the SN scenario since the point of view of service prices, user utilities, and operator benefit.
... The authors analyze the advantages related to the co-location of functions belonging to fixed and mobile services. In [55] the authors address the service placement problem from a technological viewpoint showing solutions for infrastructure VNF observation and networking. ...
Towards 6G, a key challenge lies in the placement of virtual network functions on physical resources. This becomes complex due to the dynamic nature of mobile environments, making the design a major point of research. We propose a framework that sees this challenge as a complex and dynamic collective process, presenting a novel perspective which encompasses transport network and wireless segment aspects. The framework is built around an analytical modeling and algorithmic tools that rely on complex systems’ paradigm as multiplex networks and evolutionary game theory. The multiplex network enables capturing the layered and heterogeneous nature of the environment. Evolutionary game theory models the dynamical behavior of the system as a collective social process, where each decision on functions influences the overall outcome. Our model allows us to achieve a placement scheme that optimizes 6G functions deployment and minimizes the number of active computational nodes. Compared to traditional transport network centric approach, it effectively reduces interference, ensuring the network’s effective operation and performance. Results show the efficacy of the strategy, enabling the dynamic distribution of functions as the outcome of a social dilemma, and highlight the potential applicability of this approach to tackle the network function placement problem in 6G networks.
... instances of NFs are creating by helps of containers at a NFV systems based on a network demand during single virtual machine [17]- [21]. ...
A recent progression of unmanned aerial vehicles (UAV) augmentation its employments for different applications. It’s also vulnerable to being, stolen, lost, stray, or destroyed at status of a security infringements for the UAV network. The proposed strategy is defending against of different attacks through using artificial intelligence by implements five steps: RGSK, GCSCS, SEDC, HSSC, and FVNF. UAV authentication is happened in the first step through the Curve448. We performance deep reinforcement learning to run with GCS for packet assignment as it implemented for switch current state identification before updating. In our work we ability to alleviate for attack of flow table overloading by assigned of packets as an under loaded or idle switches. Then, selected the least loaded switch by applied 5 tuples. Hence, we divided SDN to SEDCs and HSSC forms. First in the SEDC we using Shannon entropy to achieve classified of input packet in to regular and suspicious packets. Last will forwarded regular packets to cloud layer. By growing multiple self-organizing maps for maintained in NFV that used to classify suspicious packets as classes normal or malicious packet. The proposed performance work evaluates using NS3.26 show up the better strategy to secure UAV for different attacks.
Network function virtualization (NFV) technology significantly changes the traditional communication network environments by providing network functions as virtual network functions (VNFs) on commercial off-the-shelf (COTS) servers. Moreover, for using VNFs in a predetermined sequence to provide each network service, service chaining is essential. A VNF can provide multiple service chains with the corresponding network function, reducing the number of VNFs. However, VNFs might be the source or the target of a cyberattack. If the node where the VNF is installed is attacked, the VNF would also be easily attacked because of its security vulnerabilities. Contrarily, a malicious VNF may attack the node where it is installed, and other VNFs installed on the node may also be attacked. Few studies have been done on the security of VNFs and nodes for service chaining. This study proposes a service chain construction with security-level management. The security-level management concept is introduced to built many service chains. Moreover, the cost optimization problem for service chaining is formulated and the heuristic algorithm is proposed. We demonstrate the effectiveness of the proposed method under certain network topologies using numerical examples.
