Performance Analysis of the ATM Adaptation Layer 2 (AAL2)

Ko, Gwangzeen; Moon, Sungdon; Ahmad, Aftab; Kim, Kiseon

doi:10.1078/1434-8411-54100228

Cited by 3 publications

(4 citation statements)

References 10 publications

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“…The rest of the 47 bytes are available for multiplexing the short CPS packets. The multiplexing approach presented in [34] is analogous to the aggregation and multiplexing scheme proposed for the small-sized M2M data packets. The list of the various symbols with a brief description is provided in Table 2.…”

Section: Analytical Modeling For Multiplexing Transition Probabilitiesmentioning

confidence: 98%

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Data aggregation of mobile M2M traffic in relay enhanced LTE-A networks

Marwat

Mehmood

Görg

et al. 2016

J Wireless Com Network

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Machine-to-machine (M2M) communication is becoming an increasingly essential part of mobile traffic and thus also a major focus of the latest 4G and upcoming 5G mobile networks. M2M communication offers various ubiquitous services and is one of the main enablers of the Internet-of-things (IoTs) vision. Nevertheless, the concept of mobile M2M communication has emerged due to the wide range, coverage provisioning, high reliability as well as decreasing costs of future mobile networks. Resultantly, M2M traffic poses drastic challenges to mobile networks, particularly due to the expected large number of devices sending small-sized data. Moreover, mobile M2M traffic is anticipated to degrade the performance of traditional cellular traffic due to inefficient utilization of the scarce radio spectrum. This paper presents a novel data aggregation and multiplexing scheme for mobile M2M traffic and thus focuses on the latest 3GPP (3 rd Generation Partnership Project) tong-term-evolution-advanced (LTE-A) networks. 3GPP standardized layer 3 inband Relay Nodes (RNs) are used to aggregate uplink M2M traffic by sharing the Physical Resource Blocks (PRBs) among several devices. The proposed scheme is validated through extensive system level simulations in an LTE-A based implementation for the Riverbed Modeler simulator. Our simulation results show that besides coverage extensions, RNs serve approximately 40 % more M2M devices with the proposed data multiplexing scheme compared to the conventional without multiplexing approach. Moreover, in this paper an analytical model is developed to compute the multiplexing transition probabilities. In the end, the simulation and analytical results of multiplexing transition probabilities are compared in order to analyze the multiplexing scheme.

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Section: Analytical Modeling For Multiplexing Transition Probabilitiesmentioning

confidence: 98%

“…In this section, an analytical model is developed based on the work done in [34] for multiplexing of small common part sub-layer (CPS) packets into large ATM cells with the AAL2 layer multiplexer. An ATM cell is made up of a 5-byte header and a 48-byte payload.…”

Section: Analytical Modeling For Multiplexing Transition Probabilitiesmentioning

confidence: 99%

Data aggregation of mobile M2M traffic in relay enhanced LTE-A networks

Marwat

Mehmood

Görg

et al. 2016

J Wireless Com Network

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“…Authors of [ 23 ] present a mathematical model for evaluation of AAL2 type multiplexer’s performance parameters like expected sojourn time, mean queue length, and the probability of delay violation. Authors of [ 24 ] analyze the AAL2 multiplexer by modelling the multiplexer departure process as an r-stage Coxian process. The authors of [ 25 ] present the performance evaluation of voice traffic in mobile radio networks with Coxian distributed channel holding time.…”

Section: Literature Surveymentioning

confidence: 99%

“…Packet arrival rate from IoT devices,

is considered to be exponentially distributed. It can be shown that the total waiting time of

packet is Erlangian [ 24 ]. Therefore, the probability of subsequent arrival of packet prior to multiplexing with

packets already in the buffer is denoted as

and given as:

…”

Section: Analytical Modelmentioning

confidence: 99%

Method for Handling Massive IoT Traffic in 5G Networks

Marwat

Mehmood

Khan

et al. 2018

Sensors

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The ever-growing Internet of Things (IoT) data traffic is one of the primary research focuses of future mobile networks. 3rd Generation Partnership Project (3GPP) standards like Long Term Evolution-Advanced (LTE-A) have been designed for broadband services. However, IoT devices are mainly based on narrowband applications. Standards like LTE-A might not provide efficient spectrum utilization when serving IoT applications. The aggregation of IoT data at an intermediate node before transmission can answer the issues of spectral efficiency. The objective of this work is to utilize the low cost 3GPP fixed, inband, layer-3 Relay Node (RN) for integrating IoT traffic into 5G network by multiplexing data packets at the RN before transmission to the Base Station (BS) in the form of large multiplexed packets. Frequency resource blocks can be shared among several devices with this method. An analytical model for this scheme, developed as an r-stage Coxian process, determines the radio resource utilization and system gain achieved. The model is validated by comparing the obtained results with simulation results.

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Transient Analysis of Multiprocessor Systems

Parthasarathy

Sudhesh²

2005 Annual IEEE India Conference - Indicon

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Performance Analysis of the ATM Adaptation Layer 2 (AAL2)

Cited by 3 publications

References 10 publications

Data aggregation of mobile M2M traffic in relay enhanced LTE-A networks

Data aggregation of mobile M2M traffic in relay enhanced LTE-A networks

Method for Handling Massive IoT Traffic in 5G Networks

Transient Analysis of Multiprocessor Systems

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