Aggregation and trunking of M2M traffic via D2D connections

Rigazzi, Giovanni; Pratas, Nuno K.; Popovski, Petar; Fantacci, Romano

doi:10.1109/icc.2015.7248779

Cited by 52 publications

(43 citation statements)

References 14 publications

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“…Currently, there are many studies in IoT communication aiming to offer QoS guarantees for different IoT applications. In this section, we will highlight the studies related to our research . Lien et al proposed a time‐controlled scheduling scheme known as fixed access grant time interval (AGTI).…”

Section: Related Workmentioning

confidence: 99%

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Performance evaluation of a priority‐based resource allocation scheme for multiclass services in IoT

AlQahtani

2019

Int J Communication

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Summary Recently, the deployment of novel smart network concepts, such as the Internet of things (IoT) or machine‐to‐machine communication, has gained more attention owing to its role in providing communication among various smart devices. The IoT involves a set of IoT devices (IoTDs) such as actuators and sensors that communicate with IoT applications via IoT gateways without human intervention. The IoTDs have different traffic types with various delay requirements, and we can classify them into two main groups: critical and massive IoTDs. The fundamental promising technology in the IoT is the advanced long‐term evolution (LTE‐A). In the future, the number of IoTDs attempting to access an LTE‐A network in a short period will increase rapidly and, thus, significantly reduce the performance of the LTE‐A network and affect the QoS required by variant IoT traffic. Therefore, efficient resource allocation is required. In this paper, we propose a priority‐based allocation scheme for multiclass service in IoT to efficiently share resources between critical and massive IoTD traffic based on their specific characteristics while protecting the critical IoTDs, which have a higher priority over the massive IoTDs. The performance of the proposed scheme is analyzed using the Geo/G/1 queuing system focusing on QoS guarantees and resource utilization of both critical and massive IoTDs. The distribution of service time of the proposed system is determined and, thus, the average waiting and service times are derived. The results indicate that the performance of the massive IoTDs depends on the data traffic characteristics of the critical IoTDs. Furthermore, the results emphasize the importance of the system delay analysis and demonstrate its effects on IoT configurations.

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Section: Related Workmentioning

confidence: 99%

“…In this section, we will highlight the studies related to our research. [11][12][13][14][15][16][17][18][19] Lien et al 11 proposed a time-controlled scheduling scheme known as fixed access grant time interval (AGTI). In this scheme, machine-to-machine (M2M) clusters are scheduled at specific LTE frame periodic intervals.…”

Section: Related Workmentioning

confidence: 99%

Performance evaluation of a priority‐based resource allocation scheme for multiclass services in IoT

AlQahtani

2019

Int J Communication

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“…The MTD success probability is a metric to assess the performance of a single MTD, while the average number of successful MTDs is a metric to assess the impact of aggregators. We have adapted their definitions from [12]. Both metrics are dependent, to a certain extent, on the available channel resources.…”

Section: Rationalementioning

confidence: 99%

“…The joint-user decoding was studied in [11] and a closed-form expression of the maximum zero-outage downlink rate was derived when multiple MTDs are attached to a cellular user. By employing the trunked radio system, the authors in [12] investigated the basic trade-off between latency and transmit power for delivering the aggregated traffic. These works, however, considered either a single aggregator or a single base station (BS) scenario and ignored the coverage nature of wireless transmission.…”

Section: Introductionmentioning

confidence: 99%

Massive Machine Type Communication With Data Aggregation and Resource Scheduling

Guo

Durrani

Zhou

et al. 2017

IEEE Trans. Commun.

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To enable massive machine type communication (mMTC), data aggregation is a promising approach to reduce the congestion caused by a massive number of machine type devices (MTDs). In this work, we consider a two-phase cellular-based mMTC network where MTDs transmit to aggregators (i.e., aggregation phase) and the aggregated data is then relayed to base stations (i.e., relaying phase). Due to the limited resources, the aggregators not only aggregate data, but also schedule resources among MTDs. We consider two scheduling schemes: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). By leveraging the stochastic geometry, we present a tractable analytical framework to investigate the signal-to-interference ratio (SIR) for each phase, thereby computing the MTD success probability, the average number of successful MTDs and probability of successful channel utilization, which are the key metrics characterizing the overall mMTC performance. Our numerical results show that, although the CRS outperforms the RRS in terms of SIR at the aggregation phase, the simpler RRS has almost the same performance as the CRS for most cases with regards to the overall mMTC performance. Furthermore, the provision of more resources at the aggregation phase is not always beneficial to the mMTC performance.

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“…Thus, cellular UEs can serve as ideal candidates for D2D enabled aggregators due to their abundance and high computation capabilities. A single cell, single UE framework for the aggregation and trunking of M2M traffic via D2D links with the UEs is provided in [7]. However, the analysis is only limited to a single cell and is not scalable as it does not take into account the physical locations of the MTDs and the UEs and more importantly, it does not consider the impact of interference from MTDs and UEs transmitting in other cells in aggregation and trunking phases respectively.…”

Section: Introductionmentioning

confidence: 99%