A Control-Plane Perspective on Reducing Data Access Latency in LTE Networks

Li, Yuanjie; Yuan, Zengwen; Peng, Chunyi

doi:10.1145/3117811.3117838

Cited by 45 publications

(8 citation statements)

References 35 publications

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“…To connect to commercial mobile networks, we use the Sierra Wireless AirPrime MC7455 miniPCI modem, which supports LTE CAT 6 (LTE-advanced). 2 The modem uses external antenna, which are visible in Figure 1. To enhance the availability of the nodes, we attach them to a smart power socket that can be power-cycled remotely via SMS.…”

Section: Measurement Datamentioning

confidence: 99%

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Predicting High Delays in Mobile Broadband Networks

et al. 2021

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The number of applications that run over mobile networks, expecting bounded end-to-end delay, is increasing steadily. However, the stochastic and shared nature of the wireless medium makes providing such guarantees challenging. Using several network interfaces simultaneously can help address fluctuating delays, provided that transport protocols can switch between them in a timely manner. Today's protocols are mostly closed-loop and thus require at least one round trip before reacting to increased delay. This paper examines whether jumps in round trip times (RTTs) have a pattern that can be predicted beforehand. Using per second RTT measurements from hundreds of probes in two Long Term Evolution (LTE) cellular networks, we train an ensemble of classifiers to detect increases in delay. We construct a parsimonious explainable model that provides an accuracy of 80% and does not appear to be specific to a particular mobile operator. Further, we examine whether our model can be extended to 5G using a small dataset with extra 5G metadata, resulting in an accuracy of 88%. Our model indicates that RTTs are long-range correlated and shows that radio measurements of channel occupancy are accurate predictors of the onset of high delays. These results suggest that it is feasible to build an open-loop control system for multiplexing among several interfaces to proactively bound delays.

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Section: Measurement Datamentioning

confidence: 99%

“…Delays can increase for a number of reasons, including interference, handover, and congestion both in the radio and beyond [2], [3]. New error correction mechanisms and novel radio access strategies, such as the flexible numerology introduced by 5G new radio [4], may help drive delay down [5].…”

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confidence: 99%

Predicting High Delays in Mobile Broadband Networks

et al. 2021

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“…The Handover procedure handles the mobility and TAU (Tracking Area Updates) procedure is responsible for migrating each device's associated states to other MMEs, and MME scaling (in response to overload or failures). In an ideal scenario, these procedures on an average takes few hundred milliseconds to complete; in case of overload or failures, these procedures can take seconds or at times even minutes to complete [5,30,42]. The UE and MME retain these association details (called static bindings or associations) until the UE is completely detached from the core network.…”

Section: Overview Of Lte Architecturementioning

confidence: 99%

“…CoMB [62] demonstrated the composition of NF services into a consolidated middlebox. In the context of cellular networks, techniques are proposed to optimize the control procedure latency by customizing the LTE control messaging architecture [31,41]. ECHO [42] deals with reliability of EPC in public cloud infrastructures.…”

Section: Related Workmentioning

confidence: 99%

MMLite

Nagendra

Bhattacharya

Gandhi

et al. 2019

Proceedings of the 2019 ACM Symposium on SDN Research

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With increase in cellular-enabled IoT devices having diverse traffic characteristics and service level objectives (SLOs), handling the control traffic in a scalable and resource-efficient manner in the cellular packet core network is critical. The traditional monolithic design of the cellular core adopted by service-providers is inflexible with respect to the diverse requirements and bursty loads of IoT devices, specifically for properties such as elasticity, customizability, and scalability. To address this key challenge, we focus on the most critical control plane component of the cellular packet core network, the Mobility Management Entity (MME). We present MMLite, a functionally decomposed and stateless MME design wherein individual control procedures are implemented as microservices and states are decoupled from their processing, thus enabling elasticity and fault tolerance. For SLO compliance, we develop a multi-level load balancing approach based on skewed consistent hashing to efficiently distribute incoming connections. We evaluate the performance benefits of MMLite over existing approaches with respect to scaling, fault tolerance, SLO compliance and resource efficiency.

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“…Bousia et al proposed an infrastructure-sharing algorithm that allows operators to share resources and switch off redundant base stations [34]. Li et al proposed DPCM to eliminate some instructions to enhance the performance of LTE control plane [35].…”

Section: Related Workmentioning

confidence: 99%

Empirical Experience and Experimental Evaluation of Open5GCore over Hypervisor and Container

Chang

Qiu

Chen

et al. 2018

Wireless Communications and Mobile Computing

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One of the most important technologies for future 5G networks is to utilize Network Function Virtualization (NFV) to virtualize the network components. NFV provides flexibility, short time to market, and low cost solution to build network services, which are important features of 5G networks. Although the idea of virtualization is just being applied to cellular networks, it has been used in the community of cloud computing. There are two main virtualization techniques, hypervisor and container. In this paper, we present our practical experience of virtualizing Open5GCore, a commercial product of SDN-enabled Evolved Packet Core (EPC), over hypervisor and container. In addition to describing how to virtualize Open5GCore, we also present the experimental performance evaluation of the systems. Finally, some important lessons learned are provided.

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A Control-Plane Perspective on Reducing Data Access Latency in LTE Networks

Cited by 45 publications

References 35 publications

Predicting High Delays in Mobile Broadband Networks

Predicting High Delays in Mobile Broadband Networks

MMLite

Empirical Experience and Experimental Evaluation of Open5GCore over Hypervisor and Container

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