Design of power and resource management in OFDMA networks using sleep mode selection technique

Alostad, Jasem M.

doi:10.1016/j.comnet.2020.107411

Cited by 5 publications

(2 citation statements)

References 22 publications

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“…"Load balancing and energy" activation or optimization are related to each other and make an impact on the cost of providing services in an immensely effective manner. It has been assumed that a little percentage of the budget for IT enterprise infrastructure has been rose which would be spent on energy resources in an effective manner [6]. The basic meaning of the term balancing is that evenly providing the load to determine a bunch of servers within a system.…”

Section: Theme 1: Types Of "Resource Management Techniques" In Cloud ...mentioning

confidence: 99%

A Study on Resource Management Techniques in Cloud Computing

Shrawankar¹

2022

2583-0805

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This study is based on the “resource management techniques” in cloud computing and this study has been filled with valid and authentic insights which have been collected to evaluate the subject matter. At the beginning of this study, the concept of cloud counting has been clarified and then its importance has been shown within a proper manner. By showcasing the concept of cloud computing, a generic awareness has been developed that to retain all types of crucial files, it is important to develop cloud storage within any sort of system. Also, there are several types of “resource management techniques” that have been depicted with the help of collecting crucial insights which are related with the help of gathering valid and authentic insights. Also, there are some important materials and methods and in this study, secondary data has been collected by following an inductive approach and also, qualitative research design has been chosen and implemented to bring betterment in the study. The resources have been collected from peer reviewed journals which consist of the information based on cloud computing, “resource management techniques” and cloud resource management. Also, several challenges of using resources management techniques within cloud computing with the help of crucial and effective insights have been depicted. Keyword : Cloud computing, resource management, techniques.

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Section: Theme 1: Types Of "Resource Management Techniques" In Cloud ...mentioning

confidence: 99%

A Study on Resource Management Techniques in Cloud Computing

Shrawankar¹

2022

2583-0805

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“…There is a tradeoff between network performance and energy‐saving when base station sleeping mode is implemented. In a study, 7 the measured call blocking probability was used to estimate the tradeoff between network performance and energy savings in sleep mode capable cellular networks. The researchers proposed an information exchange surrogate approximation for cellular networks to extensively approximate the tradeoff between network performance and energy savings in cellular networks.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the stochastic deployment of small base stations in an interleave division multiple access‐based heterogeneous cellular networks

Noma‐Osaghae

Misra

Koyuncu

2022

Int J Communication

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The use of small base stations (SBSs) to improve the throughput of cellular networks gave rise to the advent of heterogeneous cellular networks (HCNs). Still, the interleave division multiple access (IDMA) performance in sleep mode active HCNs has not been studied in the existing literature.This research examines the 24-h throughput, spectral efficiency (SE), and energy efficiency (EE) of an IDMA-based HCN and compares the result with orthogonal frequency division multiple access (OFDMA). An energyspectral-efficiency (ESE) model of a two-tier HCN was developed. A weighted sum modified particle swarm optimization (PSO) algorithm simultaneously maximized the SE and EE of the IDMA-based HCN. The result obtained showed that the IDMA performs at least 68% better than the OFDMA on the throughput metric. The result also showed that the particle swarm optimization algorithm produced the Pareto optimal front at moderate traffic levels for all varied network parameters of SINR threshold, SBS density, and sleep mode technique. The IDMA-based HCN can improve the throughput, SE, and EE via sleep mode techniques. Still, the combination of network parameters that simultaneously maximize the SE and EE is interference limited. In sleep mode, the performance of the HCN is better if the SBSs can adapt to spatial and temporal variations in network traffic.

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