DMME: A Distributed LTE Mobility Management Entity

An, Xueli; Pianese, Fabio; Widjaja, Indra; Acer, Utku Günay

doi:10.1002/bltj.21547

Cited by 32 publications

(14 citation statements)

References 15 publications

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“…In two-tier architectures, the MME VNF is mostly decomposed into a front-end Signaling Load Balancer (SLB in [147]) or MME Load Balancer (MLB in [144]) and a cluster of MME processing entities (MMPs). As an exception, the DMME architecture in [151] and [152] separates the MME VNF into DMME nodes, which are similar to MMPs, and a reliable object storage (ROS) subsystem. In three-tier architectures such as Takano et al [153], Premsankar et al [143], and vMME [145], [146], there is also a front-end load balancer, which is the same as the one in the two-tier architecture.…”

Section: B Scalable Reliable and High Available Designmentioning

confidence: 99%

SDN/NFV-Based Mobile Packet Core Network Architectures: A Survey

Nguyen

Brunström

Grinnemo

et al. 2017

IEEE Commun. Surv. Tutorials

268

155

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The emergence of two new technologies, namely, software defined networking (SDN) and network function virtualization (NFV), have radically changed the development of network functions and the evolution of network architectures. These two technologies bring to mobile operators the promises of reducing costs, enhancing network flexibility and scalability, and shortening the time-to-market of new applications and services. With the advent of SDN and NFV and their offered benefits, the mobile operators are gradually changing the way how they architect their mobile networks to cope with ever-increasing growth of data traffic, massive number of new devices and network accesses, and to pave the way toward the upcoming fifth generation networking. This survey aims at providing a comprehensive survey of state-of-the-art research work, which leverages SDN and NFV into the most recent mobile packet core network architecture, evolved packet core. The research work is categorized into smaller groups according to a proposed four-dimensional taxonomy reflecting the: 1) architectural approach, 2) technology adoption, 3) functional implementation, and 4) deployment strategy. Thereafter, the research work is exhaustively compared based on the proposed taxonomy and some added attributes and criteria. Finally, this survey identifies and discusses some major challenges and open issues, such as scalability and reliability, optimal resource scheduling and allocation, management and orchestration, and network sharing and slicing that raise from the taxonomy and comparison tables that need to be further investigated and explored.

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Section: B Scalable Reliable and High Available Designmentioning

confidence: 99%

SDN/NFV-Based Mobile Packet Core Network Architectures: A Survey

Nguyen

Brunström

Grinnemo

et al. 2017

IEEE Commun. Surv. Tutorials

268

155

View full text Add to dashboard Cite

show abstract

“…An estimate and synthetic values set is listed in Table III, for α and β, according to the traffic density pattern from the productive realistic network scenarios proposed in [18] and [29].…”

Section: A Integration Of Mtc Traffic Into Eps and Traffic Flow Manamentioning

confidence: 99%

IoT Traffic Management and Integration in the QoS Supported Network

Al-Shammari

Al-Aboody

Al-Raweshidy

2018

IEEE Internet Things J.

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This paper proposes: 1) a traffic flow management policy, which allocates and organizes machine type communication (MTC) traffic flows network resources sharing within evolved packet system (EPS); 2) an access element as a wireless sensor network gateway for providing an overlaying access channel between the machine type devices and EPS; and 3) it addresses the effect and interaction in the heterogeneity of applications, services and terminal devices, and the related quality of service (QoS) issues among them. This paper overcomes the problems of network resource starvation by preventing deterioration of network performance. The scheme is validated through simulation, which indicates the proposed traffic flow management policy outperforms the current traffic management policy. Specifically, simulation results show that the proposed model achieves an enhancement in QoS performance for the MTC traffic flows, including a decrease of 99.45% in packet loss rate (PLR), a decrease of 99.89% in packet end to end (E2E) delay, a decrease of 99.21% in packet delay variation (PDV). Furthermore, it retains the perceived quality of experience of the real time application users within high satisfaction levels, such as the voice over long term evolution service possessing a mean opinion score (MOS) of 4.349 and enhancing the QoS of a video conference service within the standardized values of a 3GPP body, with a decrease of 85.28% in PLR, a decrease of 85% in packet E2E delay and a decrease of 88.5% in PDV. Index Terms-Application quality of service (AQoS), end to end (E2E) delay, gateway, human type communication (HTC), Internet of Things (IoT), jitter, machine type communication (MTC), network QoS (NQoS), quality of experience (QoE), QoS class identifier (QCI), traffic policy.

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“…A distributed MME model is, also, proposed in [10] and [11]. In contrast with the approach proposed in [9], the MME model is stateless and based on an external users' state storage system.…”

Section: Related Workmentioning

confidence: 99%

On the scalability of 5G core network: The AMF case

Alawe

Hadjadj‐Aoul

Ksentini

et al. 2018

2018 15th IEEE Annual Consumer Communications &Amp; Networking Conference (CCNC)

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Abstract-One of the requirement of 5G is to support massive number of connected devices, considering many use-cases such as IoT and massive Machine Type Communication (MTC). While this represents an interesting opportunity for operators to grow their business, it will need new mechanisms to scale and manage the envisioned high number of devices and their generated traffic. Particularity, the signaling traffic, which will overload the 5G core Network Function (NF) in charge of authentication and mobility, namely Access and Mobility Management Function (AMF). The objective of this paper is to provide an algorithm based on Control Theory allowing: (i) to equilibrate the load on the AMF instances in order to maintain an optimal response time with limited computing latency; (ii) to scale out or in the AMF instance (using NFV techniques) depending on the network load to save energy and avoid wasting resources. Obtained results via computer system indicate the superiority of our algorithm in ensuring fair load balancing while scaling dynamically with the traffic load.

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DMME: A Distributed LTE Mobility Management Entity

Cited by 32 publications

References 15 publications

SDN/NFV-Based Mobile Packet Core Network Architectures: A Survey

SDN/NFV-Based Mobile Packet Core Network Architectures: A Survey

IoT Traffic Management and Integration in the QoS Supported Network

On the scalability of 5G core network: The AMF case

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