scholarly journals Energy Efficiency Opposition-Based Learning and Brain Storm Optimization for VNF-SC Deployment in IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hejun Xuan ◽  
Xuelin Zhao ◽  
Zhenghui Liu ◽  
Jianwei Fan ◽  
Yanling Li
Keyword(s):  
Energy Consumption ◽  
Optimal Solution ◽  
Network Function Virtualization ◽  
Simulation Experiments ◽  
Important Indicator ◽  
Service Chain ◽  
Network Function ◽  
Opposition Based Learning ◽  
The Internet Of Things ◽  
Virtual Network Function

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.

scholarly journals Deep Reinforcement Learning-Based Algorithm for VNF-SC Deployment

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Junlei Xuan ◽  
Huifang Yang ◽  
Xuelin Zhao ◽  
Xingpo Ma ◽  
Xiaokai Yang
Keyword(s):  
Real Time ◽  
Optimization Model ◽  
Virtual Network ◽  
Network Function Virtualization ◽  
Prediction Algorithm ◽  
Network Service ◽  
The Real ◽  
Service Chain ◽  
Network Function ◽  
Virtual Network Function

Network function virtualization (NFV) has the potential to lead to significant reductions in capital expenditure and can improve the flexibility of the network. Virtual network function (VNF) deployment problem will be one of key problems that need to be addressed in NFV. To solve the problem of routing and VNF deployment, an optimization model, which minimizes the maximum index of used frequency slots, the number of used frequency slots, and the number of initialized VNF, is established. In this optimization model, the dependency among the different VNFs is considered. In order to solve the service chain mapping problem of high dynamic virtual network, a new virtual network function service chain mapping algorithm PDQN-VNFSC was proposed by combining prediction algorithm and DQN (Deep Q-Network). Firstly, the real-time mapping of virtual network service chains is modeled into a partial observable Markov decision process. Then, the real-time mapping process of virtual network service chain is optimized by using global and long-term benefits. Finally, the service chain of virtual network function is mapped through the learning decision framework of offline learning and online deployment. The simulation results show that, compared with the existing algorithms, the proposed algorithm has a lower the maximum index of used frequency slots, the number of used frequency slots, and the number of initialized VNF.

scholarly journals On Blockchain-Based Cross-Service Communication and Resource Orchestration on Edge Clouds

Informatics ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 13
Author(s):  
Konstantinos Papadakis-Vlachopapadopoulos ◽  
Ioannis Dimolitsas ◽  
Dimitrios Dechouniotis ◽  
Eirini Eleni Tsiropoulou ◽  
Ioanna Roussaki ◽  
...  
Keyword(s):  
Network Function Virtualization ◽  
Network Resources ◽  
Service Orchestration ◽  
Network Slicing ◽  
Network Function ◽  
Resource Orchestration ◽  
Full Capacity ◽  
Cloud Datacenter ◽  
Set Up ◽  
The Internet Of Things

With the advent of 5G verticals and the Internet of Things paradigm, Edge Computing has emerged as the most dominant service delivery architecture, placing augmented computing resources in the proximity of end users. The resource orchestration of edge clouds relies on the concept of network slicing, which provides logically isolated computing and network resources. However, though there is significant progress on the automation of the resource orchestration within a single cloud or edge cloud datacenter, the orchestration of multi-domain infrastructure or multi-administrative domain is still an open challenge. Towards exploiting the network service marketplace at its full capacity, while being aligned with ETSI Network Function Virtualization architecture, this article proposes a novel Blockchain-based service orchestrator that leverages the automation capabilities of smart contracts to establish cross-service communication between network slices of different tenants. In particular, we introduce a multi-tier architecture of a Blockchain-based network marketplace, and design the lifecycle of the cross-service orchestration. For the evaluation of the proposed approach, we set up cross-service communication in an edge cloud and we demonstrate that the orchestration overhead is less than other cross-service solutions.

scholarly journals Design and Implementation of Virtual Security Function Based on Multiple Enclaves

2021 ◽  
Vol 13 (1) ◽  
pp. 12
Author(s):  
Juan Wang ◽  
Yang Yu ◽  
Yi Li ◽  
Chengyang Fan ◽  
Shirong Hao
Keyword(s):  
Intrusion Detection System ◽  
Detection System ◽  
Network Function Virtualization ◽  
Sensitive Data ◽  
Network Function ◽  
State Security ◽  
Security Challenges ◽  
Iot Platforms ◽  
Scalable Network ◽  
Virtual Network Function

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.

scholarly journals Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

2021 ◽  
Vol 11 (22) ◽  
pp. 10547
Author(s):  
Marios Gatzianas ◽  
Agapi Mesodiakaki ◽  
George Kalfas ◽  
Nikos Pleros ◽  
Francesca Moscatelli ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Network Function Virtualization ◽  
User Association ◽  
Computational Resource ◽  
Mixed Integer Linear Program ◽  
Resource Allocation Algorithm ◽  
Network Function

In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.

The Key Impacts of Softwarization in the Modern Era of 5G and the Internet of Things

2020 ◽  
Vol 12 (3) ◽  
pp. 16-27
Author(s):  
Opeoluwa Tosin Eluwole ◽  
Mike Oluwatayo Ojo
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Network Function Virtualization ◽  
The Internet ◽  
Mobile Edge Computing ◽  
New Era ◽  
Network Function ◽  
Advanced Computing ◽  
Modern Era ◽  
The Internet Of Things

Fascinating technologies, such as software defined networking (SDN), network function virtualization (NFV) and mobile edge computing (MEC) among others, have introduced software-enabling capabilities to telecommunications, mobile and wireless communications. To depict this systemic evolution, various terminologies, such as system cloudification, network programmability, advanced computing and most popularly, softwarization, have been used by numerous scholars. Softwarization is now becoming a fully established phenomenon, especially in the new era of the rapidly evolving Internet of Things (IoT), artificial intelligence (AI) and the looming 5G technology. Away from the research and development (R&D) focus on the technological capabilities of softwarization, this article highlights the main stakeholders in softwarization and underlines a tripartite influence of the systemic evolution i.e. technical, social and economic impacts, all of which will be vital in ensuring a sustainable 5G technology and beyond.

Service Chain Embedding for Diversified 5G Slices With Virtual Network Function Sharing

2019 ◽  
Vol 23 (5) ◽  
pp. 826-829 ◽  
Author(s):  
Tram Truong-Huu ◽  
Purnima Murali Mohan ◽  
Mohan Gurusamy
Keyword(s):  
Virtual Network ◽  
Service Chain ◽  
Network Function ◽  
Function Sharing ◽  
Virtual Network Function

scholarly journals A Cross-Domain Service Function Chain Deployment Scheme Based on Bargaining Game

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Guoyan Li ◽  
Yajuan Ren ◽  
Yi Liu
Keyword(s):  
Bargaining Game ◽  
Network Function Virtualization ◽  
Service Chain ◽  
Service Function ◽  
Network Function ◽  
Cross Domain ◽  
Optimal Node ◽  
Consumption Cost ◽  
Service Function Chain ◽  
Multiple Domains

Software-defined networking (SDN) and network function virtualization (NFV) technologies provide support for service function chain (SFC) deployment. As the scale of a network expands, SDN domains are maintained and managed by their respective network operators. When deploying an SFC in multiple domains, to protect the privacy of each domain is challenging. We propose a cross-domain SFC deployment scheme based on a bargaining game. We establish an effective cross-domain service chain system model and combine resource consumption cost and load balance to translate SFC deployment to an optimization problem. A bargaining game model is established so as to reasonably optimize these contradictory parameters. We solve the model by an improved imperialist competition algorithm and obtain the optimal node mapping relationship. Experimental results show that our method performs better than the current one in terms of network load balancing and mapping overhead and has better scalability.

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