Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

A Cloud Native Solution for Dynamic Auto Scaling of MME in LTE

Due to rapid growth in the use of mobile devices and as a vital carrier of IoT traffic, mobile networks need to undergo infrastructure wide revisions to meet explosive traffic demand. In addition to data traffic, there has been a significant rise in the control signaling overhead due to dense deployment of small cells and IoT devices. Adoption of technologies like cloud computing, Software Defined Networking (SDN) and Network Functions Virtualization (NFV) is impressively successful in mitigating the existing challenges and driving the path towards 5G evolution. However, issues pertaining to scalability, ease of use, service resiliency, and high availability need considerable study for successful roll out of production grade 5G solutions in cloud. In this work, we propose a scalable Cloud Native Solution for Mobility Management Entity (CNS-MME) of mobile core in a production data center based on micro service architecture. The micro services are lightweight MME functionalities, in contrast to monolithic MME in Long Term Evolution (LTE). The proposed architecture is highly available and supports auto-scaling to dynamically scale-up and scale-down required micro services for load balancing. The performance of proposed CNS-MME architecture is evaluated against monolithic MME in terms of scalability, auto scaling of the service, resource utilization of MME, and efficient load balancing features. We observed that, compared to monolithic MME architecture, CNS-MME provides 7% higher MME throughput and also reduces the processing resource consumption by 26%

Agile management and interoperability testing of SDN/NFV-enriched 5G core networks

In the fifth generation (5G) era, the radio internet protocol capacity is expected to reach 20Gb/s per sector, and ultralarge content traffic will travel across a faster wireless/wireline access network and packet core network. Moreover, the massive and mission-critical Internet of Things is the main differentiator of 5G services. These types of real-time and large-bandwidth-consuming services require a radio latency of less than 1 ms and an end-to-end latency of less than a few milliseconds. By distributing 5G core nodes closer to cell sites, the backhaul traffic volume and latency can be significantly reduced by having mobile devices download content immediately from a closer content server. In this paper, we propose a novel solution based on software-defined network and network function virtualization technologies in order to achieve agile management of 5G core network functionalities with a proof-of-concept implementation targeted for the PyeongChang Winter Olympics and describe the results of interoperability testing experiences between two core networks

Live migration of virtual machine and container based mobile core network components: A comprehensive study

With the increasing demand for openness, flexibility, and monetization, the Network Function Virtualization (NFV) of mobile network functions has become the embracing factor for most mobile network operators. Early reported field deployments of virtualized Evolved Packet Core (EPC) - the core network (CN) component of 4G LTE and 5G non-standalone mobile networks - reflect this growing trend. To best meet the requirements of power management, load balancing, and fault tolerance in the cloud environment, the need for live migration of these virtualized components cannot be shunned. Virtualization platforms of interest include both Virtual Machines (VMs) and Containers, with the latter option offering more lightweight characteristics. This paper's first contribution is the proposal of a framework that enables migration of containerised virtual EPC components using an open-source migration solution which does not fully support the mobile network protocol stack yet. The second contribution is an experimental-based comprehensive analysis of live migration in two virtualization technologies - VM and Container - with the additional scrutinization on the container migration approach. The presented experimental comparison accounts for several system parameters and configurations: flavor (image) size, network characteristics, processor hardware architecture model, and the CPU load of the backhaul network components. The comparison reveals that the live migration completion time and also the end-user service interruption time of the virtualized EPC components is reduced approximately by 70% in the container platform when using the proposed framework.This work was supported in part by the NSF under Grant CNS-1405405, Grant CNS-1409849, Grant ACI-1541461, and Grant CNS-1531039T; and in part by the EU Commission through the 5GROWTH Project under Grant 856709

Signalling load reduction in 5G network based on cloud radio access network architecture

The rapid growth of both mobile users and application numbers has caused a huge load on the core network (CN). This is attributed to the large numbers of control messages circulating between CN entities for each communication or service request, however, making it imperative to develop innovative designs to handle this load. Consequently, a variety of proposed architectures, including a software defined network (SDN) paradigm focused on the separation of control and data plans, have been implemented to make networks more flexible. Cloud radio access network (C-RAN) architecture has been suggested for this purpose, which is based on separating base band units (BBU) from several base stations and assembling these in one place. In this work, a novel approach to realize this process is based on SDN and C-RAN, which also distributes the control elements of the CN and locates them alongside the BBU to obtain the lowest possible load. The performance of this proposed architecture was evaluated against traditional architecture using MATLAB simulation, and. the results of this assessment indicated a major reduction in signalling load as compared to that seen in the traditional architecture. Overall, the number of signalling messages exchanged between control entities was decreased by 53.19 percent as compared to that seen in the existing architecture

A Centralized SDN Architecture for the 5G Cellular Network

In order to meet the increasing demands of high data rate and low latency cellular broadband applications, plans are underway to roll out the Fifth Generation (5G) cellular wireless system by the year 2020. This paper proposes a novel method for adapting the Third Generation Partnership Project (3GPP)'s 5G architecture to the principles of Software Defined Networking (SDN). We propose to have centralized network functions in the 5G network core to control the network, end-to-end. This is achieved by relocating the control functionality present in the 5G Radio Access Network (RAN) to the network core, resulting in the conversion of the base station known as the gNB into a pure data plane node. This brings about a significant reduction in signaling costs between the RAN and the core network. It also results in improved system performance. The merits of our proposal have been illustrated by evaluating the Key Performance Indicators (KPIs) of the 5G network, such as network attach (registration) time and handover time. We have also demonstrated improvements in attach time and system throughput due to the use of centralized algorithms for mobility management with the help of ns-3 simulations

OpenEPC Integration within 5GTN as an NFV proof of concept

Abstract. Gone are the days, when a hardware is changed on every malfunctioning and the whole operation either stays down or load on the replacing hardware becomes too much which ultimately compromises the QoS. The IT industry is mature enough to tackle problems regarding scalability, space utilization, energy consumption, cost, agility and low availability. The expected throughput and network latency with 5G in the cellular Telecommunication Networks seems to be unachievable with the existing architecture and resources. Network Function Virtualization promises to merge IT and Telecommunications in such an efficient way that the expected results could be achieved no longer but sooner. The thesis work examines the compatibility and flexibility of a 3GPP virtual core network in a virtualization platform. The testbed is established on an LTE (Long Term Evolution) based network being already deployed and OpenEPC is added as virtual core network on it. The integration of OpenEPC in 5GTN (5TH Generation Test Network) is discussed in details in the thesis which will give an account of the possibility of implementing such a simulated vEPC (Virtual Evolved Packet Core) in a real network platform. The deployed setup is tested to check its feasibility and flexibility for a platform which could be used for NFV deployment in future. The monitoring of OpenEPC’s individual components while utilizing the major resources within them, forms the primary performance test. The CPU Load and Memory Utilization is tested on different CPU stress levels having a constant data traffic from actual UEs. At the completion of the thesis work, a consensus is built up based on the test results that the test setup can hold number of subscribers to a certain amount without any performance degradation. Moreover, the virtual core network throughput and network latency is also compared to the commercial LTE networks and theoretical maximum values on similar resources to check performance consistency OpenEPC must offer

Getting the Most Out of Your VNFs: Flexible Assignment of Service Priorities in 5G

Through their computational and forwarding capabilities, 5G networks can support multiple vertical services. Such services may include several common virtual (network) functions (VNFs), which could be shared to increase resource efficiency. In this paper, we focus on the seldom studied VNF-sharing problem, and decide (i) whether sharing a VNF instance is possible/beneficial or not, (ii) how to scale virtual machines hosting the VNFs to share, and (iii) the priorities of the different services sharing the same VNF. These decisions are made with the aim to minimize the mobile operator's costs while meeting the verticals' performance requirements. Importantly, we show that the aforementioned priorities should not be determined a priori on a per-service basis, rather they should change across VNFs since such additional flexibility allows for more efficient solutions. We then present an effective methodology called FlexShare, enabling near-optimal VNF-sharing decisions in polynomial time. Our performance evaluation, using real-world VNF graphs, confirms the effectiveness of our approach, which consistently outperforms baseline solutions using per-service priorities