Energy-Efficient Mobility-Aware Caching Algorithms for Clustered Small Cells in Ultra-Dense Networks

Keshavarzian, Iman; Zeinalpour-Yazdi, Zolfa; Tadaion, Aliakbar

doi:10.1109/tvt.2019.2918712

Cited by 20 publications

(20 citation statements)

References 32 publications

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“…B. Rengarajan et al [22] and M. Di Renzo et al [23] propose novelty models for the optimization of energy efficiency at the physical layer. On the other hand, works related to the network layer are, for example, the work of Keshavarzian et al [24]. They have introduced several algorithms to minimize the energy consumption taking into account the mobility-aware capability.…”

Section: Introductionmentioning

confidence: 99%

Multilayer Network Optimization for 5G & 6G

et al. 2020

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Section: Introductionmentioning

confidence: 99%

Multilayer Network Optimization for 5G & 6G

et al. 2020

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“…Cluster-based selection of the caching nodes also reduces overall energy requirements [117], [118]. A framework for MEC clustering and cache space allotment was introduced in [2].…”

Section: A Network Planning and Caching Node Selectionmentioning

confidence: 99%

“…vated SBSs and allocated them to different clusters. In [118], the authors clustered a number of SBSs in an ultra-dense network (UDN) and exploited user mobility to reduce energy consumption.…”

Section: A Network Planning and Caching Node Selectionmentioning

confidence: 99%

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A Review on Green Caching Strategies for Next Generation Communication Networks

et al. 2020

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In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching.

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“…In [39], the user-centric cooperative interference mitigation strategy is proposed, where dense SBSs are able to store contents. In [42], the small cells are grouped into disjoint clusters. However, there are no results investigating the clustering scheme for the cache-enabled mmWave SCN and UDN, to our knowledge.…”

Section: Introductionmentioning

confidence: 99%

Cache-Enabled Millimeter Wave Cellular Networks With Clusters

Huang

Xiao

et al. 2020

IEEE Trans. Commun.

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Wireless content caching in cellular networks is an efficient way to reduce the service delay and alleviate backhaul pressure. For the benefits of sharing spectral and storage resources, clustering in cached networks has recently attracted significant research interests. Meanwhile, since the multimedia content (e. g.., video) of caching networks may require a huge transmission rates, millimeter wave (mmWave) communication is considered to be an efficient transmission scheme for cacheenabled networks. We investigate the ergodic rate and average service delay for typical user terminal (UT) in the clustered cacheenabled small cell networks (SCN) and ultra dense networks (UDN) with mmWave channels. In SCN, each cluster consists of cache-enabled UTs, and in the UDN a cluster is formed by cacheenabled UTs and small base stations (SBSs) with non-uniform caching capacity. The clusters are assumed to be discs and content sharing is only possible within clusters through mmWave device-to-device (D2D) tier and SBS tier communications. With stochastic geometry methods, the distributions of content sharing distance and signal-to-interference-noise-ratio (SINR) of typical UT in a cluster are derived for both SCN and UDN scenarios. To minimize the average service delay in high SINR region, we provide an algorithm to jointly optimize caching scheme for SBSs and UTs. By simulations, we validate our theoretical analysis and the performance of proposed caching scheme. The numerical results also show that there exists best radius in the design of cluster for UDNs.

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Energy-Efficient Mobility-Aware Caching Algorithms for Clustered Small Cells in Ultra-Dense Networks

Cited by 20 publications

References 32 publications

Multilayer Network Optimization for 5G & 6G

Multilayer Network Optimization for 5G & 6G

A Review on Green Caching Strategies for Next Generation Communication Networks

Cache-Enabled Millimeter Wave Cellular Networks With Clusters

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