M2M meets D2D: Harnessing D2D interfaces for the aggregation of M2M data

Afzal, Asma; Zaidi, Syed Ali Raza; McLernon, Des; Ghogho, Mounir; Feki, Afef

doi:10.1109/icc.2017.7997135

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…Similar to the work by [141], the authors in [145] have proposed trunking and aggregation of MTC data in a large scale network. They have considered homogeneous deployment of MTCDs in an area and have proposed the association of at most one MTCD with the UE.…”

Section: A: Single Ue As Gatewaymentioning

confidence: 96%

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Data Aggregation in Massive Machine Type Communication: Challenges and Solutions

2019

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Machine type communication (MTC) is a fundamental technology to realize the concept of fully connected world in fifth generation (5G) Internet of Things (IoT). The massive roll out of the MTC devices is a serious challenge for cellular networks from operational and management perspective, including massive access and network congestion. Many proposals have been put forward by the research community to cater to the nuisance of massive MTC (mMTC) access in cellular networks. Recently, data aggregation has attracted a lot of research attention owing to its robust ability to resolve the above-mentioned challenges. In this paper, we review the recent development in data aggregation techniques, including their application scenarios, design, and limitations. Commencing with the application scenarios and current challenges in the MTC network, the classification of various proposed solutions for massive access along with the family of data aggregation techniques is discussed in detail. By doing so, it provides an insight about the future design trends that can propel the current research efforts to curb the mMTC access in a cellular network.

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Section: A: Single Ue As Gatewaymentioning

confidence: 96%

“…The solutions proposed in [140], [141], [143], [145], [147] are based on single UE. Except [147], all of these works are focusing on the uniform QoS requirements for all the MTCDs.…”

Section: B: Multiple Ues As Gatewaysmentioning

confidence: 99%

Data Aggregation in Massive Machine Type Communication: Challenges and Solutions

2019

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“…Using a UE as SMDA has been proposed in [17][33][34] [36]. In [17], the conventional UE is used as a single mobile gateway aggregator, and the communication between D2D is exploited in the cellular system to aggregate and multiplex the traffic from surrounding MTCDs.…”

Section: ) Mobile Data Aggregatormentioning

confidence: 99%

“…They show improvement in system connectivity but at the cost of smartphone battery depletion and increased delay for MTCD traffic. In [36], the authors propose a scheme for MTCD traffic aggregation and trunking within the resources of D2D users in a large-scale system. They introduce a comprehensive stochastic geometry framework to analyze the coverage area of regular users, to make sure that the MTCDs send their data using the shortest path to a nearest regular user.…”

Section: ) Mobile Data Aggregatormentioning

confidence: 99%

QoS-Based Data Aggregation and Resource Allocation Algorithm for Machine Type Communication Devices in Next-Generation Networks

Ahmed

Rikli

2021

IEEE Access

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Machine Type Communication (MTC) becomes one of enablers of the internet of things, it faces many challenges in its integration with human-to-human (H2H) communication methods. To this aim, the Long Term Evolution (LTE) needs some adaptation in the scheduling algorithms that assign resources efficiently to both MTC devices (MTCDs) and H2H users. The minimum amount of LTE resources that can be assigned to one user is much larger than the requirements of a single MTCD. In this paper, a QoS-enabled algorithm is proposed to aggregate MTCD traffic coming from many sources at the Relay Node (RN) that classifies and aggregates the MTCD traffic based on the source type and delay requirements. In this study, three types of MTCD and one H2H sources will be considered. Each type of MTCD traffic will be grouped into a separate queue, and will be served with the appropriate priority. Resources are then assigned to the aggregated MTC traffic instead of an individual assignment for each MTCD, while the H2H users will be directly connected to the LTE. Two schemes of resource partitioning and sharing between the MTCDs and the H2H users will be considered: one proportional and the other moving-boundary. Simulation models will be built to evaluate the proposed algorithms. While the obtained results for the first scheme showed a clear improvement in LTE resource utilization for the MTCDs, a negative effect was noticed in the performance of the H2H users. The second scheme achieved a positive improvement for both MTCDs and H2H users. INDEX TERMS5G networks, Data aggregation, Internet of Things IoT, MTC, resource allocation, Quality of Service QoS. I. INTRODUCTIONAn increasing demand for high data rates, high capacity, and low latency to support a fully connected networked society that offers access to information and the sharing of data anywhere and anytime for anyone and anything, has led to the introduction of a new type of communication paradigm called machine-to-machine communication (M2M) or machine type communication (MTC). This type of communication implies that machines have the ability to communicate with each other in a smart approach without or with a minimum of human intervention [1]. Interest in MTCDs has increased in recent decades because they exist in many applications of the internet of things, such as but not limited to e-Healthcare, smart metering, smart cities, intelligent transportation systems, supply chains, surveillance monitoring systems, the prediction of natural disasters, and many social applications [2].LTE-Advanced (LTE-A) is a candidate as the most suitable cellular technology to support MTC, due to its high data rates, large coverage area, high capacity, and spectrum efficiency. However, there are many challenges in the integration of MTCDs in an LTE-A network [3][4][5]. LTE-A has largely been designed to support H2H devices, which typically require high data rates and a small delay, have a small number of users (compared to MTCDs) and transmit a large volume of data packets. In contrast, MTCDs have di...

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Cooperative Data Aggregation and Dynamic Resource Allocation for Massive Machine Type Communication

2018

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M2M meets D2D: Harnessing D2D interfaces for the aggregation of M2M data

Cited by 5 publications

References 13 publications

Data Aggregation in Massive Machine Type Communication: Challenges and Solutions

Data Aggregation in Massive Machine Type Communication: Challenges and Solutions

QoS-Based Data Aggregation and Resource Allocation Algorithm for Machine Type Communication Devices in Next-Generation Networks

Cooperative Data Aggregation and Dynamic Resource Allocation for Massive Machine Type Communication

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