Dynamic buffer sizing for wireless devices via maximum entropy

Vázquez-Rodas, Andrés; Llopis, Luis J. de la Cruz; Igartua, Mónica Aguilar; Gargallo, Emilio Sanvicente

doi:10.1016/j.comcom.2014.03.003

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…The buffer size refers to the total amount of data that each user cannot transmit to the base station per round. The delay time was defined as either the inability to transfer a certain amount of data to the base station within each round or it took a long time to complete the transfer to the base station [36,37]. Figure 10 provides a diagram illustrating the definition of buffer size and delay time.…”

Section: Network Performancesmentioning

confidence: 99%

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Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

et al. 2023

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The rapid development of mobile devices and wireless network technologies have made them indispensable. This has created a demand for faster networks and longer battery life. The assurance of a stable network service and the enhancement of network experiences for mobile devices is equally crucial to meeting these demands. To address these challenges, mobile devices employ various techniques to decrease power consumption when they connect to wireless networks. Moreover, enhancing the endurance of mobile devices to maintain stable network services is critical when using wireless networks. In this paper, we propose a dual-radio opportunistic network for energy efficiency (DRONEE)–exponential weight with priority-based on rate control (WPRC) method which can extend and enhance the DRONEE hybrid network. By leveraging fuzzy logic control (FLC) and quality of service (QoS), our proposed method effectively solves the weighting problem in the DRONEE–weight (DRONEE–W) method. Through efficient allocation of network resources within each cluster, we minimize resource wastage and maximize resource utilization. Simulation results demonstrate the superior performance of our DRONEE–WPRC method in terms of throughput, buffer size, delay time, and power consumption compared to other methods. Therefore, our proposed method achieves optimal network resource allocation and energy efficiency.

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Section: Network Performancesmentioning

confidence: 99%

“…base station within each round or it took a long time to complete the transfer to the base station [36,37]. Figure 10 provides a diagram illustrating the definition of buffer size and delay time.…”

Section: Network Performancesmentioning

confidence: 99%

Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

et al. 2023

View full text Add to dashboard Cite

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“…In general, while many aspects of the communication systems performance analysis have been evaluated, e.g., [11]- [16], analytical models based on system information and system entropy analysis are largely absent. Thus, there exists only the famous and commonly used informationtheoretic approach, based on maximizing entropy, given certain constraints (see, e.g., [17]- [25]). Furthermore, the nonextensive entropy has been also employed to a variety of systems having multifractal structures [26].…”

Section: Introductionmentioning

confidence: 99%

Entropy Analysis of Broadband Wireless Access Systems

Lazov

2017

IEEE Systems Journal

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A Broadband Wireless Access (BWA) system consists of a base station and a set of M users within its antenna sector, with N simultaneously active users, 0 ≤ N ≤ M , working in Point-to-Multipoint (PMP) mode. We model this system as family of Birth-Death Processes (BDPs), with size M + 1, in equilibrium, indexed by system utilization parameter ρ, ratio of its primary birth and death rates. Relying on the fundamental concepts of system information i and system entropy S = E(i), we develop an entropy analysis of BWA systems. Thereby, by definition, the system entropy, as the mean value of system information, is the uncertainty, related to the system. Taking system information as loss function, we identify risk and uncertainty, related to the system. Using the maximization of entropy, given the average number N of active users, we promote belt-zone of deviation from maximum uncertainty and a function of relative risk, regarding N , for a BWA system. This analysis is illustrated on BWA systems with finite user population, such as the binomial M -server BWA systems, modeled by the family of BDPs with binomial distribution, and the delay single-server BWA systems, modeled by the corresponding family of BDPs; both systems represent private networks.Index Terms-Absolute and relative risks, Broadband Wireless Access (BWA) system, information linearity, system information and entropy, system utilization and size, uncertainty.

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A methodology for information and capacity analysis of broadband wireless access systems

Lazov

2015

Telecommun Syst

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Dynamic buffer sizing for wireless devices via maximum entropy

Cited by 6 publications

References 25 publications

Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

Energy Efficiency of Mobile Devices Using Fuzzy Logic Control by Exponential Weight with Priority-Based Rate Control in Multi-Radio Opportunistic Networks

Entropy Analysis of Broadband Wireless Access Systems

A methodology for information and capacity analysis of broadband wireless access systems

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