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Journal articles on the topic 'Goodput'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Vora, Ankur, and Kyoung-Don Kang. "Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems." Technologies 6, no. 4 (November 15, 2018): 105. http://dx.doi.org/10.3390/technologies6040105.

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In emerging Cyber-Physical Systems (CPS), the demand for higher communication performance and enhanced wireless connectivity is increasing fast. To address the issue, in our recent work, we proposed a dynamic programming algorithm with polynomial time complexity for effective cross-layer downlink Scheduling and Resource Allocation (SRA) considering the channel and queue state, while supporting fairness. In this paper, we extend the SRA algorithm to consider 5G use-cases, namely enhanced Machine Type Communication (eMTC), Ultra-Reliable Low Latency Communication (URLLC) and enhanced Mobile BroadBand (eMBB). In a simulation study, we evaluate the performance of our SRA algorithm in comparison to an advanced greedy cross-layer algorithm for eMTC, URLLC and LTE (long-term evolution). For eMTC and URLLC, our SRA method outperforms the greedy approach by up to 17.24%, 18.1%, 2.5% and 1.5% in terms of average goodput, correlation impact, goodput fairness and delay fairness, respectively. In the case of LTE, our approach outperforms the greedy method by 60%, 2.6% and 1.6% in terms of goodput, goodput fairness and delay fairness compared with tested baseline.

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2

Kaisina, I. "Modeling Goodput for Data Transmission in FANET." Proceedings of Telecommunication Universities 6, no. 1 (2020): 100–108. http://dx.doi.org/10.31854/1813-324x-2020-6-1-100-108.

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This paper investigates the process of multi-stream data transmission from several unmanned aerial vehicles (UAV) to a ground station. We can observe a mathematical model of the data transfer process at the application level of the OSI model (from flying nodes to a ground station). The Poisson – Pareto packet process is used to describe the multi-stream data traffic. The results of simulation are obtained using the network simulator NS-3. It is considered a system for emulating the process of multi-stream data transmission from UAV to a ground station. Acording to the results of studies for multi-stream data transmission it is clear that the increase of the UAV source nodes which simultaneously transmit data to a ground station needs higher requirements for Goodput.

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3

Huo, Dao An, and Qiang Cao. "Traffic Throttling to Improve TCP Incast Throughput." Advanced Materials Research 424-425 (January 2012): 227–31. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.227.

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Cluster-based storage systems are widely used by many large data centers because of the manageability, low cost and other advantages. However, typical cluster-based storage systems rely on the standard TCP/IP Ethernet for clients to access data. Clients would experience the TCP effective throughput (called goodput) collapse which is termed as Incast problem. The main reason of Incast is TCP retransmit timeout which is caused by unfairness between the competing flows. In this paper, we analyze the TCP Incast dynamics from the fairness aspect and propose a method to make the competing flows share the network resource fairly by throttling the traffic. The simulation results show that our method is able to improve the TCP Incast goodput by 10% comparing to the high-timer-resolution

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4

Basney, Jim, and Miron Livny. "Improving Goodput by Coscheduling CPU and Network Capacity." International Journal of High Performance Computing Applications 13, no. 3 (August 1999): 220–30. http://dx.doi.org/10.1177/109434209901300305.

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5

Yang, Tao, Gjergji Mino, Leonard Barolli, Makoto Ikeda, Fatos Xhafa, and Arjan Durresi. "Performance of Wireless Sensor Networks for Different Mobile Event Path Scenarios." International Journal of Distributed Systems and Technologies 2, no. 3 (July 2011): 49–63. http://dx.doi.org/10.4018/jdst.2011070104.

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In this paper, the authors investigate how the sensor network performs when the event moves with special movement path. Simulation results are compared with four scenarios: when the event is stationary, moving randomly, moving with simple 4 path, and boids path. The simulation results show that for the case when the event is moving randomly, the performance is the worst in the four scenarios. The characteristic of goodput decreases with the increase of number of sensor nodes. In the case of the boids model, the goodput is unstable when the is lower than 10 pps. The consumed energy characteristic increases with the increase of . Simulation results show that the consumed energy of random movement is the worst among the four scenarios. The consumed energy of boids model is the lowest in four cases. This shows that the event movement with boids model can decrease the consumed energy in large scale WSNs.

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6

Kaysina, I. A., D. S. Vasiliev, and A. V. Abilov. "Multi-Stream Simulated Scenario in FANET Based on Poisson Pareto Burst Process in NS-3." Bulletin of Kalashnikov ISTU 22, no. 3 (October 9, 2019): 56. http://dx.doi.org/10.22213/2413-1172-2019-3-56-62.

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Исследовано влияние трафика потоковых данных с нескольких летающих узлов-источников в самоорганизующейся сети беспилотных летательных аппаратов (Flying Ad Hoc Network – FANET) на метрику качества обслуживания (Quality of Service – QoS). В качестве метрики используется полезная пропускная способность (Goodput) сети.Для описания трафика с высокой пачечностью данных от множества источников в сетевом симуляторе Network Simulation 3 (NS-3) была применена модель Пуассона – Парето (PPBP). PPBP служит для описания пакетных систем и является наиболее реалистичной моделью для описания интернет-трафика. Согласно этой модели пачки данных (например, файлы) генерируются в соответствии с процессом Пуассона с параметром l, а размер каждой пачки имеет распределение Парето.Модель была применена в следующем сценарии: летающий узел-шлюз передавал трафик от сети беспилотных летательных аппаратов, сгенерированный согласно модели Пуассона – Парето, на наземный узел-получатель. В ходе исследований был сделан вывод, что увеличение параметра lp и наличие самоподобного трафика повышает требование к метрике QoS – Goodput, что может вызвать ухудшение коэффициента доставки пакетов и увеличить задержки. Решением данной проблемы может являться добавление узлов-ретрансляторов, на которых будет выполняться балансировка нагрузки.

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7

Dong, Pingping, Jianxin Wang, Jiawei Huang, Haodong Wang, and Yi Pan. "Improving Performance of QoS Applications for Wireless Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/385935.

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The contention based medium access method of 802.11 standards is a fundamental cause of poor downlink goodput and high latency over wireless networks, which makes it impossible to provide QoS guarantees. The intensive channel contention leads to the performance degradation. The problem exacerbates when the traffic asymmetry between the uplink and the downlink is present. While prior research works proposed various mechanisms to alleviate the issue, little was done to specifically address the appropriate parameter setting in a real world network. This study presents a way to obtain the appropriate access parameters that improves the performance of QoS applications over wireless networks. In particular, we propose AQEDCA, a traffic-aware minimum contention window adjustment algorithm. We validate our scheme by the extensive real world network tests and the results show that our scheme improves the downlink goodput up to 199.13%, decreases the latency up to 54.77%, and can achieve tight QoS guarantees as compared to the existing schemes.

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8

Chang, Yusun, Christopher P. Lee, and John A. Copeland. "Goodput Enhancement of VANETs in Noisy CSMA/CA Channels." IEEE Journal on Selected Areas in Communications 29, no. 1 (January 2011): 236–49. http://dx.doi.org/10.1109/jsac.2011.110122.

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9

Rajbhandari, Samyam, Yuxiong He, Olatunji Ruwase, Michael Carbin, and Trishul Chilimbi. "Optimizing CNNs on Multicores for Scalability, Performance and Goodput." ACM SIGOPS Operating Systems Review 51, no. 2 (April 4, 2017): 267–80. http://dx.doi.org/10.1145/3093315.3037745.

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10

Rajbhandari, Samyam, Yuxiong He, Olatunji Ruwase, Michael Carbin, and Trishul Chilimbi. "Optimizing CNNs on Multicores for Scalability, Performance and Goodput." ACM SIGPLAN Notices 52, no. 4 (May 12, 2017): 267–80. http://dx.doi.org/10.1145/3093336.3037745.

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11

Rajbhandari, Samyam, Yuxiong He, Olatunji Ruwase, Michael Carbin, and Trishul Chilimbi. "Optimizing CNNs on Multicores for Scalability, Performance and Goodput." ACM SIGARCH Computer Architecture News 45, no. 1 (May 11, 2017): 267–80. http://dx.doi.org/10.1145/3093337.3037745.

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12

Pentikousis, K., M. Palola, M. Jurvansuu, and P. Perala. "Active goodput measurements from a public 3G/UMTS network." IEEE Communications Letters 9, no. 9 (September 2005): 802–4. http://dx.doi.org/10.1109/lcomm.2005.1506708.

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13

Seetharam, Anand, and Arti Ramesh. "On the goodput of flows in heterogeneous mobile networks." Computer Networks 130 (January 2018): 134–44. http://dx.doi.org/10.1016/j.comnet.2017.11.008.

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14

Ahmad, Sarfraz, and Muhammad Junaid Arshad. "Enhanced Multistream Fast TCP: Rapid Bandwidth Utilization after Fast-Recovery Phase." Applied Sciences 9, no. 21 (November 4, 2019): 4698. http://dx.doi.org/10.3390/app9214698.

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The purpose of this study is to enhance the performance of Multistream Fast Transmission Control Protocol (TCP) keeping in view the recent web-based applications that are being deployed on long-range, high-speed, and high-bandwidth networks. To achieve the objective of the research study, a congestion control after fast-recovery module for congestion control scheme of Multistream Fast TCP is proposed. The module optimized the performance of the protocol by reducing the time that is required to consume the available bandwidth after a fast-recovery phase. The module is designed after studying additive-increase, multiplicative-decrease and rate-based congestion window management schemes of related transport protocols. The module adjusts the congestion window on receipt of each individual acknowledgment instead of each round trip time after the fast-recovery phase until it consumes vacant bandwidth of the network link. The module is implemented by using Network Simulator 2. Convergence time, throughput, fairness index, and goodput are the parameters used to assess the performance of proposed module. The results indicate that Enhanced Multistream Fast TCP with congestion control after fast recovery recovers its congestion window in a shorter time period as compared to multistream Fast TCP, Fast TCP, TCP New Reno, and Stream Control Transmission Protocol. Consequently, Enhanced Multistream Fast TCP consumes the available network bandwidth in lesser time and increases the throughput and goodput. The proposed module enhanced the performance of the transport layer protocol. Our findings demonstrate the performance impact in the form of a decrease in the convergence time to consume the available network bandwidth and the increase in the throughput and the goodput.

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15

Shendokar, Kishori, and R. M. Goudar. "Improved Goodput for Real-Time Traffic over Multipath Wireless Network." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 5 (May 30, 2017): 89–93. http://dx.doi.org/10.23956/ijarcsse/sv7i5/0201.

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16

Fortin-Parisi, Sophie, and Bruno Sericola. "A Markov model of TCP throughput, goodput and slow start." Performance Evaluation 58, no. 2-3 (November 2004): 89–108. http://dx.doi.org/10.1016/j.peva.2004.07.016.

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17

Kuang-Hao Liu, H. Rutagemwa, Xuemin Shen, and J. W. Mark. "Efficiency and Goodput Analysis of Dly-ACK in IEEE 802.15.3." IEEE Transactions on Vehicular Technology 56, no. 6 (November 2007): 3888–98. http://dx.doi.org/10.1109/tvt.2007.904547.

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18

Daji Qiao, Sunghyun Choi, and K. G. Shin. "Goodput analysis and link adaptation for IEEE 802.11a wireless LANs." IEEE Transactions on Mobile Computing 1, no. 4 (October 2002): 278–92. http://dx.doi.org/10.1109/tmc.2002.1175541.

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19

Celandroni, Nedo, and Francesco Potortì. "Maximizing single connection TCP goodput by trading bandwidth for BER." International Journal of Communication Systems 16, no. 1 (February 2003): 63–79. http://dx.doi.org/10.1002/dac.580.

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20

Donatiello, Lorenzo, and Gustavo Marfia. "Models and performance evaluation of event goodput in sensor platforms." Computer Networks 123 (August 2017): 119–36. http://dx.doi.org/10.1016/j.comnet.2017.05.015.

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21

Sgardoni, Victoria, David R. Bull, and Andrew R. Nix. "ARQ-Aware Scheduling and Link Adaptation for Video Transmission over Mobile Broadband Networks." Journal of Computer Networks and Communications 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/369803.

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This paper studies the effect of ARQ retransmissions on packet error rate, delay, and jitter at the application layer for a real-time video transmission at 1.03 Mbps over a mobile broadband network. The effect of time-correlated channel errors for various Mobile Station (MS) velocities is evaluated. In the context of mobile WiMAX, the role of the ARQ Retry Timeout parameter and the maximum number of ARQ retransmissions is taken into account. ARQ-aware and channel-aware scheduling is assumed in order to allocate adequate resources according to the level of packet error rate and the number of ARQ retransmissions required. A novel metric, namely,goodput per frame, is proposed as a measure of transmission efficiency. Results show that to attain quasi error free transmission and low jitter (for real-time video QoS), only QPSK 1/2 can be used at mean channel SNR values between 12 dB and 16 dB, while 16QAM 1/2 can be used below 20 dB at walking speeds. However, these modes are shown to result in low transmission efficiency, attaining, for example, a total goodput of 3 Mbps at an SNR of 14 dB, for a block lifetime of 90 ms. It is shown that ARQ retransmissions are more effective at higher MS speeds.

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22

Andreotti, Riccardo, Tao Wang, Vincenzo Lottici, Filippo Giannetti, and Luc Vandendorpe. "Resource Allocation via Max–Min Goodput Optimization for BIC-OFDMA Systems." IEEE Transactions on Communications 64, no. 6 (June 2016): 2412–26. http://dx.doi.org/10.1109/tcomm.2016.2555311.

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23

Wu, Jiyan, Chau Yuen, Bo Cheng, Yanlei Shang, and Junliang Chen. "Goodput-Aware Load Distribution for Real-Time Traffic over Multipath Networks." IEEE Transactions on Parallel and Distributed Systems 26, no. 8 (August 1, 2015): 2286–99. http://dx.doi.org/10.1109/tpds.2014.2347031.

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24

Qiu, Shuwei, Yi-Hua Zhu, Xianzhong Tian, and Kaikai Chi. "Goodput-maximised data delivery scheme for battery-free wireless sensor network." IET Communications 14, no. 4 (March 3, 2020): 665–73. http://dx.doi.org/10.1049/iet-com.2018.6215.

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25

Juan, Li, and Edward Mutafungwa. "Rate adaptation of convolutional coded optical CDMA systems for improved goodput." Optics Communications 240, no. 4-6 (October 2004): 315–27. http://dx.doi.org/10.1016/j.optcom.2004.06.038.

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26

Shi, Zheng, Liyang Wang, Shaodan Ma, Guanghua Yang, and Yao Yao. "Goodput Maximization of HARQ-IR Over Arbitrarily Correlated Rician Fading Channels." IEEE Access 6 (2018): 28903–11. http://dx.doi.org/10.1109/access.2018.2839615.

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27

Escudero-Garzas, Jose Joaquin, Bertrand Devillers, and Ana Garcia-Armada. "Fairness-Adaptive Goodput-Based Resource Allocation in OFDMA Downlink with ARQ." IEEE Transactions on Vehicular Technology 63, no. 3 (March 2014): 1178–92. http://dx.doi.org/10.1109/tvt.2013.2281367.

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28

Li, Yang, Rui Wang, and Zezhong Zhang. "Massive MIMO Downlink Goodput Analysis With Soft Pilot or Frequency Reuse." IEEE Wireless Communications Letters 7, no. 3 (June 2018): 448–51. http://dx.doi.org/10.1109/lwc.2017.2783336.

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29

Tao, Yang, and Zhijun Yan. "Goodput Improvement for MPTCP Based on Controlling the Difference of Delay." International Journal of Hybrid Information Technology 10, no. 4 (April 30, 2017): 1–10. http://dx.doi.org/10.14257/ijhit.2017.10.4.01.

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30

Giambene, Giovanni. "Satellite-3G Hybrid Networks: Impact of ACM and ARQ on TCP Performance." Journal of Communications Software and Systems 3, no. 3 (September 22, 2007): 177. http://dx.doi.org/10.24138/jcomss.v3i3.252.

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The adoption of satellite systems in providing broadband transmissions to mobile users such as trains, buses and vans is expected to be an interesting solution. The scenariowe considered refers to a hybrid network architecture, where a geostationary satellite forward link and a terrestrial 3G return link are used in order to exploit both the high bandwidth of a satellite channel and the lower propagation delay of a terrestrial path. The resulting round-trip delay is much shorter than that one experienced by using both the forward and return link via satellite. This is particularly appealing for overcoming the TCP efficiency degradation in high delay-bandwidth product and error prone channels. In this hybrid scenario, we used simulation results to compare the goodput of four of the most popular TCP variants, in the presence of a GOOD-BAD satellite channel, as the one experienced by mobile users. We applied an AdaptiveCoding and Modulation (ACM) technique as well, and studied its impact on TCP efficiency, when used both alone and in cooperation with an Automatic Repeat reQuest (ARQ) scheme of the Selective Repeat (SR) type with low persistency. Results obtained indicate that this hybrid architecture is advantageous for TCP transmissions in terms of average goodput, and that ACM is effective only if it is jointly used with ARQ schemes.

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31

Qu, Ying, Bryan Ng, and Michael Homer. "A goodput distribution model for planning IEEE 802.11 WBNs in built environments." Journal of Network and Computer Applications 99 (December 2017): 28–46. http://dx.doi.org/10.1016/j.jnca.2017.10.005.

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32

Biagi, Mauro, Valentina Polli, and Tatiana Patriarca. "Power-Constrained Physical-Layer Goodput Maximization for Broadband Power Line Communication Links." IEEE Transactions on Communications 59, no. 3 (March 2011): 695–700. http://dx.doi.org/10.1109/tcomm.2011.122110.090426.

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33

Sharon, Oran, and Yaron Alpert. "Coupled IEEE 802.11ac and TCP Goodput Improvement Using Aggregation and Reverse Direction." Wireless Sensor Network 08, no. 07 (2016): 107–36. http://dx.doi.org/10.4236/wsn.2016.87011.

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34

Mudassir, Mumajjed Ul, and M. Iram Baig. "MFVL HCCA: A Modified Fast-Vegas-LIA Hybrid Congestion Control Algorithm for MPTCP Traffic Flows in Multihomed Smart Gas IoT Networks." Electronics 10, no. 6 (March 18, 2021): 711. http://dx.doi.org/10.3390/electronics10060711.

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Multihomed smart gas meters are Internet of Things (IoT) devices that transmit information wirelessly to a cloud or remote database via multiple network paths. The information is utilized by the smart gas grid for accurate load forecasting and several other important tasks. With the rapid growth in such smart IoT networks and data rates, reliable transport layer protocols with efficient congestion control algorithms are required. The small Transmission Control Protocol/Internet Protocol (TCP/IP) stacks designed for IoT devices still lack efficient congestion control schemes. Multipath transmission control protocol (MPTCP) based congestion control algorithms are among the recent research topics. Many coupled and uncoupled congestion control algorithms have been proposed by researchers. The default congestion control algorithm for MPTCP is coupled congestion control by using the linked-increases algorithm (LIA). In battery powered smart meters, packet retransmissions consume extra power and low goodput results in poor system performance. In this study, we propose a modified Fast-Vegas-LIA hybrid congestion control algorithm (MFVL HCCA) for MPTCP by considering the requirements of a smart gas grid. Our novel algorithm operates in uncoupled congestion control mode as long as there is no shared bottleneck and switches to coupled congestion control mode otherwise. We have presented the details of our proposed model and compared the simulation results with the default coupled congestion control for MPTCP. Our proposed algorithm in uncoupled mode shows a decrease in packet loss up to 50% and increase in average goodput up to 30%.

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35

López-Vilos, Nicolás, Claudio Valencia-Cordero, Cesar Azurdia-Meza, Samuel Montejo-Sánchez, and Samuel Baraldi Mafra. "Performance Analysis of the IEEE 802.15.4 Protocol for Smart Environments under Jamming Attacks." Sensors 21, no. 12 (June 13, 2021): 4079. http://dx.doi.org/10.3390/s21124079.

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Jamming attacks in wireless sensor networks (WSNs) scenarios are detrimental to the performance of these networks and affect the security and stability of the service perceived by users. Therefore, the evaluation of the effectiveness of smart environment platforms based on WSNs has to consider the system performance when data collection is executed under jamming attacks. In this work, we propose an experimental testbed to analyze the performance of a WSN using the IEEE 802.15.4 CSMA/CA unslotted mode under jamming attacks in terms of goodput, packet receive rate (PRR), and energy consumption to assess the risk for users and the network in the smart scenario. The experimental results show that constant and reactive jamming strategies severely impact the evaluated performance metrics and the variance’ of the received signal strength (RSS) for some signal-to-interference-plus-noise ratio (SINR) ranges. The measurements obtained using the experimental testbed were correlated with analytical models. The results show that in the presence of one interferer, for SINR values higher than 4.5 dB, the PRR is almost 0.99, and the goodput 3.05 Kbps, but the system performance is significantly degraded when the amount of interferers increases. Additionally, the energy efficiency associated with reactive strategies is superior to the constant attack strategy. Finally, based on the evaluated metrics and with the proposed experimental testbed, our findings offer a better understanding of jamming attacks on the sensor devices in real smart scenarios.

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36

Prasad Joshi, Gyanendra, Seung Yeob Nam, Sung Won Kim, and Byung-Seo Kim. "Adaptive Window Size-Based Medium Access Control Protocol for Cognitive Radio Wireless Sensor Networks." Journal of Sensors 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/2049859.

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Many existing medium access control protocols for cognitive radio wireless sensor networks waste bandwidth and suffer from delay because of the fixed channel negotiation period in the common control channel. In this paper, we propose a medium access control protocol for cognitive radio wireless sensor networks that adjusts the channel negotiation period based on network density. We simulate the proposed approach and compare it to the performance of the fixed channel negotiation period based approaches. The results show that the proposed approach efficiently utilizes white spaces and increases the aggregated goodput.

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37

YE, Hao, Kaiping XUE, Peilin HONG, and Hancheng LU. "A Framework for Goodput Optimization in P2P Streaming over Wireless Ad-Hoc Networks." IEICE Transactions on Communications E94-B, no. 9 (2011): 2511–20. http://dx.doi.org/10.1587/transcom.e94.b.2511.

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38

Hernández Marcano, Néstor, Chres Sørensen, Juan Cabrera G., Simon Wunderlich, Daniel Lucani, and Frank Fitzek. "On Goodput and Energy Measurements of Network Coding Schemes in the Raspberry Pi." Electronics 5, no. 4 (October 13, 2016): 66. http://dx.doi.org/10.3390/electronics5040066.

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39

Devillers, B., J. Louveaux, and L. Vandendorpe. "Bit and Power Allocation for Goodput Optimization in Coded Parallel Subchannels With ARQ." IEEE Transactions on Signal Processing 56, no. 8 (August 2008): 3652–61. http://dx.doi.org/10.1109/tsp.2008.925929.

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40

Zhou, Dizhi, Peijian Ju, and Wei Song. "Goodput improvement for multipath transport control protocol in cooperative relay-based wireless networks." IET Communications 8, no. 9 (June 12, 2014): 1541–50. http://dx.doi.org/10.1049/iet-com.2013.0480.

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41

Alfa, Attahiru Sule, and Haitham Abu Ghazaleh. "Goodput Analysis Using Terminating MAP for a Class of Discrete-Time Queueing Models." Stochastic Models 27, no. 4 (October 2011): 615–28. http://dx.doi.org/10.1080/15326349.2011.614187.

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42

CI, SONG, HAMID SHARIF, and GUEVARA NOUBIR. "IMPROVING GOODPUT OF THE IEEE 802.11 MAC PROTOCOL BY USING CONGESTION CONTROL METHODS." International Journal on Wireless & Optical Communications 01, no. 02 (December 2003): 165–77. http://dx.doi.org/10.1142/s021979950300015x.

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43

Yang, Jin, Jae Kwon, Ho Hwang, and Dan Sung. "Goodput analysis of a WLAN with hidden nodes under a non-saturated condition." IEEE Transactions on Wireless Communications 8, no. 5 (May 2009): 2259–64. http://dx.doi.org/10.1109/twc.2009.080632.

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44

Jung, Hyungsoo, Shin-Gyu Kim, Heon Young Yeom, and Sooyong Kang. "TCP-GT: A new approach to congestion control based on goodput and throughput." Journal of Communications and Networks 12, no. 5 (October 2010): 499–509. http://dx.doi.org/10.1109/jcn.2010.6388496.

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45

Amini, Mohammad Reza, and Mohammed W. Baidas. "GoodPut, Collision Probability and Network Stability of Energy-Harvesting Cognitive-Radio IoT Networks." IEEE Transactions on Cognitive Communications and Networking 6, no. 4 (December 2020): 1283–96. http://dx.doi.org/10.1109/tccn.2020.2982874.

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Li, Yanjun, Lingkun Fu, You Ying, Yong Sun, Kaikai Chi, and Yi-hua Zhu. "Goodput optimization via dynamic frame length and charging time adaptation for backscatter communication." Peer-to-Peer Networking and Applications 10, no. 3 (July 26, 2016): 440–52. http://dx.doi.org/10.1007/s12083-016-0480-1.

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Grote, Walter, Alex Grote, and Isabel Delgado. "IEEE 802.11 goodput analysis for mixed real-time and data traffic for home networks." annals of telecommunications - annales des télécommunications 63, no. 9-10 (August 1, 2008): 463–71. http://dx.doi.org/10.1007/s12243-008-0044-3.

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Aggarwal, R., P. Schniter, and C. Koksal. "Rate adaptation via link-layer feedback for goodput maximization over a time-varying channel." IEEE Transactions on Wireless Communications 8, no. 8 (August 2009): 4276–85. http://dx.doi.org/10.1109/twc.2009.081132.

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MOON, SangKwon, Jong-Woon YOO, Jaesub KIM, and Kyu-Ho PARK. "MAC Protocol for Energy Efficiency and Service Differentiation with High Goodput in Wireless Sensor Networks." IEICE Transactions on Communications E96.B, no. 6 (2013): 1444–58. http://dx.doi.org/10.1587/transcom.e96.b.1444.

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Andreotti, Riccardo, Ivan Stupia, Vincenzo Lottici, Filippo Giannetti, and Luc Vandendorpe. "Goodput-Based Link Resource Adaptation for Reliable Packet Transmissions in BIC-OFDM Cognitive Radio Networks." IEEE Transactions on Signal Processing 61, no. 9 (May 2013): 2267–81. http://dx.doi.org/10.1109/tsp.2013.2250970.

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