Dragonfly-Based Joint Delay/Energy LTE Downlink Scheduling Algorithm

Nashaat, Heba; Refaat, Osama; Zaki, Fayez W.; Shaalan, Islam E.

doi:10.1109/access.2020.2974856

Cited by 16 publications

(8 citation statements)

References 32 publications

(58 reference statements)

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“…The new dragonfly algorithm will optimizes resource assignment for QoS requirements with higher level of energy efficiency. 5,6 Experimental results prove that the proposed scheme improves overall system performance along with users QoS satisfaction.…”

mentioning

confidence: 77%

“…In Reference 4 the delay based and QoS aware scheduling scheme exhibits efficient solutions for the heterogeneous traffic RT and NRT services to maintain the balance between delay and throughput. The new dragonfly algorithm will optimizes resource assignment for QoS requirements with higher level of energy efficiency 5,6 . Experimental results prove that the proposed scheme improves overall system performance along with users QoS satisfaction.…”

Section: Introductionmentioning

confidence: 93%

“…On demand service request of UE is satisfied with available RBs, by the assimilation of minimal energy consumption algorithm in discontinuous reception switching. 3,6 This algorithm achieves increased QoS request along with reduced overall energy consumption in the LTE-A system. However, this method does not guarantee all the traffic class users of the system.…”

Section: Related Workmentioning

confidence: 99%

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Bidirectional resource scheduling algorithm for advanced long term evolution system

Gatti

Shankar

2020

Engineering Reports

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The 5G long term evolution-advanced (LTE-A) system aims to offer unprecedent data rates, user experience, and minimal latency amongst the end users with the introduction of carrier aggregation (CA) technology. Radio resource management (RRM) with scheduler is responsible for satisfying the user quality of service (QoS) requirements through resource allocation. Due to the need for an uninterrupted bidirectional communication between the eNodeB and user equipment (UE) in LTE-A, the joint scheduling algorithm is acknowledged as a central research prospect. In this article, a modified joint uplink/downlink (UL/DL) user carrier scheduling algorithm satisfying demand service requests UE, is proposed. The joint optimization of the subcarrier assignment in an orthogonal frequency-division multiplexing-based network is utilized to balance the resource coupling between the UL/DL directions. CA is used to determine the weight factors required for the bandwidth allocation within the mobile users based on the QoS class identifier. These weight factors are employed as probability functions for resource allocation. The proposed algorithm will reduce the computational complexity arised in the conventional joint UL/DL scheduling algorithm based on the suboptimal solutions via probability functions. The simulation results show that the packet loss rate and packet delay among the mobile users are substantially reduced for both real-time and nonreal-time services.

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mentioning

confidence: 77%

Section: Introductionmentioning

confidence: 93%

Section: Related Workmentioning

confidence: 99%

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Bidirectional resource scheduling algorithm for advanced long term evolution system

Gatti

Shankar

2020

Engineering Reports

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“…where h is the sum of all virtual machine resource requirements mapped to any physical LUT-based FPGA, which cannot be greater than the corresponding host LUTbased FPGA resources. In theory, the network delay optimization of the data center is to find out a set of optimized virtual machine mapping functions, that is, to reduce the network transmission within the data center by optimizing the mapping of the virtual machine, not only to reduce the data transmission between LUT-based FPGAs but also to optimize the network transmission path, that is, to reduce the number of switches or routers that need to pass in the process of network transmission number [25]. Based on the virtual machine delay matrix, find virtual machines that are in high demand for network communication and map these virtual machines to the same physical LUT-based FPGA as much as possible or between multiple LUT-based FPGAs in the same switch.…”

Section: Process Mapping Transformation Algorithmmentioning

confidence: 99%

FPGA Delay-Oriented Process Mapping Algorithm of Xiangxi Minority Based on LUT

Yun

Zeng

Zhang

2022

Mathematical Problems in Engineering

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At present, FPGA (field-programmable gate array) architecture has made great progress in the requirements of hardware volume, which can meet common needs. However, for the increasing number of resources, it is difficult to significantly reduce the delay of process mapping. Therefore, this paper proposes FDMAP (fit descending map) algorithm from the perspective of the LUT number to reduce the delay. This paper proposes a method of FPGA mapping and debugging for heterogeneous multicore high-performance processors based on isomorphic symmetric FPGA architecture, which effectively utilizes the architectural features of heterogeneous multicore processors and the symmetric features of isomorphic FPGA, divides FPGA functions from top to bottom in a hierarchical way, and constructs FPGA architecture from bottom to top. Using differential bridge and adaptive delay adjustment sampling technology, combined with the embedded virtual logic analyzer debugging tool, FPGA architecture can be lightened and deployed quickly. Multicore complementary core-to-core replacement simulation mapping methods such as debug shells can be used to effectively complete the mapping of the target’s high-performance heterogeneous multicore processor to the entire SOC (system on-ship) chip system-level FPGA. In the aspect of algorithm, the fdmap algorithm is mainly implemented, and the low latency mapping of resources is realized with FPGA architecture. In order to verify the effectiveness of mapping the fdmap algorithm, this paper compares the fdmap algorithm with the vector VM algorithm. The research shows that when the wavelength resolution is 7 pm and the temperature error is less than 1°C, the shell is debugged, and 10 mapping examples are simulated with the fdmap algorithm. In the experiment, the LUT with the most critical 20% is selected, and the closed value of the LUT search type is set to 0.86. Compared with the original data, the number of LUTs increased by 15.2%, and the criticality decreased by 35.21%. Compared with the vector VM algorithm with the biggest gap, the number of LUTs decreased by 14.25%, the criticality improved by 14.21%, and the overall delay decreased by 65%. Therefore, the isomorphic symmetric FPGA architecture proposed in this paper can improve the structural criticality and significantly reduce the latency while reducing the number of LUTs.

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“…Therefore, the total bandwidth for each PRB is 180 kHz. However, for the time domain, the allocation time is 1 ms. 6 So, the available downlink bandwidth in LTE-A systems is divided into a number of PRBs, and each has an allocation time of 1 ms. 7 Continuing with the time-domain description, the LTE/LTE-A frame has a 10 ms length, and it is constructed by 10 subframes. Each subframe has two slots to carry 14 OFDM symbols, with the length of each slot as 0.5 ms.…”

mentioning

confidence: 99%

Optimized two‐level scheduler for video traffic in LTE downlink framework

Elhadad

El‐Shafai

El‐Rabaie

et al. 2021

Int J Communication

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The most challenging issue in long-term evolution (LTE) mobile networks is the design of an optimal scheduler. The main target of the LTE scheduling strategy is to guarantee a certain level of quality of service (QoS) in order to satisfy users' needs. In this work, a novel queue-optimized two-level scheduling strategy is introduced. The queue-optimized scheduler has the ability to support both real-time (RT) and non-RT (NRT) services in the LTE downlink framework. The first level of the proposed scheduler depends on an optimized queue length threshold that is dynamically adapted to adjust the assigned resources for the video traffic to maintain the throughput around its average value. The proposed scheduling strategy is utilized to efficiently enhance the radio resource allocation process for video traffic by minimizing the allocation of any excess unwanted resources, which consequently facilitates the support of more video connections and enhances the overall network spectral efficiency. The distribution of the resources among users for RT and NRT applications is actually performed at the second level of the scheduling process. The physical resource blocks (PRBs) are assigned according to the enhanced earliest due date first (EEDDF) mechanism. The proposed scheduling strategy prioritizes users according to their service requirements, to improve the QoS provision. The proposed scheduler maximizes the video applications throughput, and generally, minimizes the packet delay and the packet loss rate (PLR) for RT applications.

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Dragonfly-Based Joint Delay/Energy LTE Downlink Scheduling Algorithm

Cited by 16 publications

References 32 publications

Bidirectional resource scheduling algorithm for advanced long term evolution system

Bidirectional resource scheduling algorithm for advanced long term evolution system

FPGA Delay-Oriented Process Mapping Algorithm of Xiangxi Minority Based on LUT

Optimized two‐level scheduler for video traffic in LTE downlink framework

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