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Data Aggregation in Massive Machine Type Communication: Challenges and Solutions

Authors: Tabinda Salam; Waheed ur Rehman; Xiaofeng Tao 0001;

Data Aggregation in Massive Machine Type Communication: Challenges and Solutions

Abstract

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.

Keywords

Fog, data aggregation, cooperative aggregation, D2D, Electrical engineering. Electronics. Nuclear engineering, 5G networks, hybrid aggregation, TK1-9971

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    47
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
47
Top 10%
Top 10%
Top 1%
gold