# Method for Handling Massive IoT Traffic in 5G Networks
## 2 Literature Survey  
The literature available on RN indicates that research work in this field is mostly focused on implementation aspects and improving system performance [1; 2; 3; 4]. Performance of relaying in mobile networks has been studied by several researchers. In [5], algorithms for energy efficiency enhancement and optimum node placement are proposed. In [6], challenges related to mobile communication in high-speed trains such as attenuation and high Doppler spread are addressed. In [7], power control mechanisms are investigated for enhancing the outage performance of relaying scheme via centralized and distributed power adjustment schemes. Performance evaluation of relaying systems for the end-to-end delay is studied with the help of semi-Markov processes in [8]. The derivation of analytical results for the expected packet end-to-end delay is also explored in [8]. An investigation of connectivity and service interruption time before reconnecting to RN in 4G networks for handhelds and relays is carried out in [9]. Data security issues during handover in mobile networks are addressed in [10] using mobile relaying. Deployment of an unmanned aerial vehicle as a relaying node in wireless communication is explored in [11].  
Research work available on packet multiplexing is mostly based on 4G and previous mobile communication systems. Statistical multiplexer's performance for the determination of packet delay arising in voice traffic is studied in [12] using Markov modulated Poisson process. The authors of [13] discuss an end-to-end packet delay performance of data encapsulation as well as packet aggregation technique with arrivals having Poisson distribution and service time with phase-type distribution. As of multiplexed flows, approximation methods for finding probability distribution function for packet waiting time are presented in [14]. In [15], the authors present a scheme for packet aggregation to handle M2M data traffic having small-sized messages by sharing radio resources of LTE-A in downlink; however, uplink M2M traffic is not considered. In [16], an analysis of aggregation delay for packets from multiple sensors with on-off type of data traffic in Wireless Body Area Networks is presented. In [17], the authors present a framework for dimensioning of the 5G access network by utilizing G/G/1 queuing models for delay percentiles. In [18], capacity development for packet-based radio access technologies through multiplexing gain is investigated. The authors conclude that multiplexing gain is achievable for traffic with variable bit rate but not for traffic with constant bit rate. A Software Defined Network (SDN)-based approach to packet aggregation and then disaggregation after transmission is presented in [19].  
The Asynchronous Transfer Mode (ATM) Adaptation Layer 2 (AAL2) represents a technique for multiplexing of packets in networks such as 3G. In this technique, several small packets are fitted into large ATM cells. In [20], the authors present a probabilistic model of AAL2 for the 3G core network. In [21], a queuing model for the evaluation of AAL2 packet multiplexer performance modelled as batch Markovian arrivals having timer mechanism is presented. Extension of [21] presented in [22] is for modelling of multiplexing buffer. 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. The authors of [26] propose a method of performance analysis for a continuous time Markovian arrival process at the ATM Adaptation Layer 2 (AAL2), where the Common Part Sublayer (CPS) packets get multiplexed at the AAL2 buffer before being sent to transmission buffer. Both the buffers are modelled as queues.