The container has several advantages over the traditional virtual machine technology such as light-weight, fast booting time, and fast recovery. Kubernetes is one the most outstanding container management and deployment platforms. The Kubernetes provides autoscaling function, which will increase and decrease the hardware resources to adapt with the current traffic load situation to keep the user experience. Two popular autoscaling methods are horizontal autoscaling and vertical autoscaling. Based on the monitoring resource utilization, horizontal autoscaling will increase the number of PoDs (point of deployment) or vertical autoscaling will increase the hardware resources of each PoD to achieve the target utilization. In this paper, we present a hybrid solution that combines the advantages of both autoscaling solutions and proposes a bandwidth-efficient scheduler strategy. By numerical analysis, our hybrid approach is better than the normal HPA approach in terms of bandwidth cost and has lower autoscaling latency than the VPA approach
Video streaming over error-prone wireless networks can result in unsatisfactory user experience, which includes two factors: video distortion due to video compression and packet loss and video smoothness due to the mismatch of video bitrate and channel bandwidth, packet retransmission delay. Existing algorithms have addressed the problem of adaptive video bitrate and optimization of transport layer parameters separately, which can lead to non-optimal solution in terms of user experience. In this paper, we propose a cross-layer design, which integrates an optimization framework for selecting optimal video bitrate and redundancy models under varying channel conditions. In this design, to enhance video quality and satisfy delay constraint of streaming applications, different redundancy levels are configured for different types of video frames based on their importance and video bitrate also is configured adaptively according to selected redundancy and channel bandwidth. Our cross-layer design features a neural network model-based distortion estimator to facilitate the decision of redundancy and video bitrate. This distortion estimator takes into account video characteristics, redundancy models, encoder settings, and channel packet error rate to accurately predict the video distortion for each option of video bitrate and redundancy model under varying channel conditions. Simulation shows that our approach can improve the distortion of video streaming with different types of videos in the different wireless network enviroments.
Named-Data Networking (NDN) is one of the promising approaches for the Future Internet to cope with the explosion and current usage pattern of Internet traffic.Content provider mobility in the NDN allows users to receive real-time traffic when the content providers are on the move.However, the current solutions for managing these mobile content providers suffer several issues such as long handover latency, high cost, and non-optimal routing path.In this paper, we survey main approaches for provider mobility in NDN and propose an optimal scheme to support the mobile content providers in the large-scale NDN domain.Our scheme predicts the movement of the provider and uses state information in the NDN forwarding plane to set up an optimal new routing path for mobile providers.By numerical analysis, our approach provides NDN users with better service access delay and lower total handover cost compared with the current solutions.
Distributed mobility management (DMM) is currently being researched and standardized in academia and standardization development organizations for the purpose of overcoming the major issues of existing centralized mobility management. The most recent DMM protocols are being redesigned with regard to the control and data plane separation concept. However, at present, there is no solution for supporting IP multicast listeners in such new DMM environments. In this paper, we review ongoing academic research works, standardization activities and propose an IP multicast mobility design for the DMM environment using the control and data plane concept.
A management and orchestration framework (MANO) in network function virtualization (NFV) enables the agile deployment and operation of virtual network functions over a geographically distributed cloud infrastructure.This facilitates the deployment of redundancy models (i.e., high availability clusters) over different cloud centers, to guarantee the high availability of network services.In particular, in the telecommunications field, availability and resiliency are always required at a high level.Existing placement algorithms only consider one type of redundancy model at a given time.However, in reality, different redundancy configurations can be utilized to ensure the availability of virtual functions.In this article, we present an optimization model and topology-aware resource-efficient placement algorithm (TARE), which can be employed to optimally deploy high availability clusters with different redundancy configurations over geo-distributed cloud infrastructures.This model takes into account the different requirements of various high availability clusters in terms of bandwidth and computing resource demands.By simulation, the TARE has better performance than other baseline solutions in terms of the bandwidth usage, while maintaining an acceptable level of availability.
In service-based 5G core networks, the mobile core functions can be decoupled as “stateless”control functions and state management functions to support fast failure recovery and independent scalability. With the arrival of the network function virtualization framework, these 5G mobile core functions can be deployed as virtual network functions over geo-distributed cloud infrastructures without much effort. With this new service-based 5G architecture, the availability of the core network depends on the availability of these state management functions. Therefore, protection plans are required to protect these state management functions. In this paper, we present a model to optimally place the standby functions protecting the active state management functions over geo-distributed cloud infrastructures. This model considers the constraints related to state management functions and considers a new factor (i.e., availability zones) in the estimation of the availability level of each protection plan. We focus on the optimization of total resources, including network bandwidth and computing resources. To minimize complexity, we propose a heuristic algorithm that achieves the optimal total resources while satisfying the availability requirements.
This document describes two use cases for policy-based resource
management in VNF-FG. These two use cases are not covered by two
documents [irtf-nfvrg-resource-management] and [irtf-nfvrg-policy-
based-resource-management]. These two use cases considers service plan
policies in VNF-FG placement and affinity policies in Network
forwarding path update.
Network function virtualization (NFV) is a promising solution for cost reduction, service agility, and scalability to cope with the dynamic changes of traffic volume and business requirements. In the NFV framework, management and orchestration framework (MANO) plays an important roles in the automated provisioning, configuration, lifecycle management, and high availability of virtual network functions (VNF). In order to achieve high availability and auto-scaling for VNFs, the MANO needs to integrate with cluster management service for scaling VNF in and out on demand basis. In this paper, we introduce an architecture which integrates clustering service into the MANO framework and define policies for cluster management in TOSCA template. Our architecture exploits policies-based cluster management and TOSCA service description template to provide the high availability and scalability to the NFV framework. We also shows our implementation using related open source projects.
The increases in ICT infrastructure/equipment investment and increased ICT adoption tend to be strongly correlated with economic growth and productivity. However, the digital economy needs more participation of digital government, and the people who run the economy plays an important role. Economy operators/leaders need to be equipped with a sufficiently deep understanding of technology trends and innovation technology to apply digital economy development. Digital technology has significantly changed the speed of operation in the economy. The internet and digital devices are drivers of economic growth. This article analyzes the Vietnam digital economy and society in the context of comparison with ASEAN countries and draws conclusions regarding future development trends.
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