BAT: A Balanced Alternating Technique for M2M Uplink Scheduling over LTE

Elhamy, A.; Gadallah, Yasser

doi:10.1109/vtcspring.2015.7145714

Cited by 28 publications

(10 citation statements)

References 12 publications

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“…Many studies have addressed radio resource allocation for M2M devices in LTE/LTE-A technology [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Related Workmentioning

confidence: 99%

“…Elhamy et al, in [27], proposed M2M uplink scheduling which aims at achieving a balance between satisfying system deadline and throughput maximisation. Depending on the network operating conditions and priorities, scheduling metric is adjusted; it can be channel quality based, delay based or a combination of them.…”

Section: Related Workmentioning

confidence: 99%

“…The scheduler considers only event-driven applications and does not take into account other types of M2M applications. Besides, these studies [25][26][27][28] do not consider the coexistence of M2M and H2H devices.…”

Section: Related Workmentioning

confidence: 99%

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Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Rekhissa

Belleudy

Bessaguet³

2019

Sensors

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Machine-to-machine (M2M) communication consists of the communication between intelligent devices without human intervention. Long term evolution (LTE) and Long-term evolution-advanced (LTE-A) cellular networks technologies are excellent candidates to support M2M communication as they offer high data rates, low latencies, high capacities and more flexibility. However, M2M communication over LTE/LTE-A networks faces some challenges. One of these challenges is the management of resource radios especially on the uplink. LTE schedulers should be able to meet the needs of M2M devices, such as power management and the support of large number of devices, in addition to handling both human-to-human (H2H) and M2M communications. Motivated by the fundamental requirement of extending the battery lives of M2M devices and managing an LTE network system, including both M2M devices and H2H users, in this paper, two channel-aware scheduling algorithms on the uplink are proposed. Both of them consider the coexistence of H2H and M2M communications and aim to reduce energy consumption in M2M devices. The first algorithm, called FDPS-carrier-by-carrier modified (CBC-M), takes into account channel quality and power consumption while allocating radio resources. Our second algorithm, recursive maximum expansion modified (RME-M), offers a balance between delay requirement and energy consumption. Depending on the system requirements, RME-M considers both channel quality and system deadlines in an adjustable manner according to M2M devices needs. Simulation results show that the proposed schedulers outperform the round-robin scheduler in terms of energy efficiency and have better cell spectral efficiency.

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“…Many studies have addressed radio resource allocation for M2M devices in LTE/LTE-A technology [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Rekhissa

Belleudy

Bessaguet³

2019

Sensors

View full text Add to dashboard Cite

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“…Such a universal scheduling mechanism is proposed in [7] for LTE downlink transmissions combining the core features of other scheduling strategies respecting each buffer's queue size and Head-of-Line (HOL) delay, the maximum probability that the HOL packet exceeds its deadline, and the ratio of channel quality and achieved average data rate. Considering MTC uplink data traffic scenarios, different approaches are presented in [8] and [9] posing to be spectral-efficient or buffer-aware realtime scheduling strategies, respectively. The use of different application types in the context of mobile networks causes interdependences of different data traffic types, which is evaluated for time-critical H2H and time-tolerant MTC data traffic in [10].…”

Section: Related Workmentioning

confidence: 99%

Payload-Size and Deadline-Aware Scheduling for Upcoming 5G Networks: Experimental Validation in High-Load Scenarios

Monhof

Haferkamp

Sliwa

et al. 2018

2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)

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High data rates, low latencies, and a widespread availability are the key properties why current cellular network technologies are used for many different applications. However, the coexistence of different data traffic types in the same 4G/5Gbased public mobile network results in a significant growth of interfering data traffic competing for transmission. Particularly in the context of time-critical and highly dynamic Cyber Physical Systems (CPS) and Vehicle-to-Everything (V2X) applications, the compliance with deadlines and therefore the efficient allocation of scarce mobile radio resources is of high importance. Hence, scheduling solutions are required offering a good trade-off between the compliance with deadlines and a spectrum-efficient allocation of resources in mobile networks. In this paper, we present the results of an experimental validation of the Payloadsize and Deadline-aware (PayDA) scheduling algorithm using a Software-Defined Radio (SDR)-based eNodeB. The results of the experimental validation prove the high efficiency of the proposed PayDA scheduling algorithm for time-critical applications in both miscellaneous and homogeneous data traffic scenarios.

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“…A comprehensive analysis of the effects due to interdependences of time-critical H2H and non-real-time Machine-to-Machine (M2M) data traffic on QoS is given in [4]. With respect to Throughput no yes no no no yes Proportional Fair partial partial no no no partial Earliest Deadline First no no yes yes no no Proposed PayDA partial partial yes yes yes no M2M communication, in [5] a scheduler is proposed that aims to be a trade-off between throughput maximization and satisfying deadlines. There is also a suggestion for M2M uplink transmissions respecting deadlines and the buffer size of M2M users in [6].…”

Section: Introductionmentioning

confidence: 99%

Payload-Size and Deadline-Aware scheduling for time-critical Cyber Physical Systems

Haferkamp¹,

Sliwa²,

Ide³

et al. 2017

2017 Wireless Days

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High transfer speeds, low latencies and a widespread availability qualify Long Term Evolution (LTE) for various applications and services in the field of Human-to-Human (H2H) as well as fast growing Vehicle-To-X (V2X) and Cyber Physical Systems (CPS) communications. As a result, a steady growth of mobile data traffic causing an increasing interaction of different traffic classes can be observed. In order to ensure timely transmissions of time-critical data in the future, we propose the novel Payload-Size and Deadline-Aware (PayDA) scheduling approach and compare its performance regarding the compliance with deadlines with those of other common packet scheduling mechanisms. The performance analysis is done with the complex and open-source LTE simulation environment LTE-Sim. The results show that the average latency can be reduced by the factor of 20 and the mean goodput can be enhanced by a factor of about 3.5 for a high miscellaneous data traffic. In case of a heavy homogeneous and time-critical data traffic the mean Deadline-Miss-Ratio (DMR) can be decreased by about 35%.

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BAT: A Balanced Alternating Technique for M2M Uplink Scheduling over LTE

Cited by 28 publications

References 12 publications

Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Payload-Size and Deadline-Aware Scheduling for Upcoming 5G Networks: Experimental Validation in High-Load Scenarios

Payload-Size and Deadline-Aware scheduling for time-critical Cyber Physical Systems

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