Device-to-device data storage for mobile cellular systems

Pääkkönen, Joonas; Hollanti, Camilla; Tirkkonen, Olav

doi:10.1109/glocomw.2013.6825065

Cited by 54 publications

(10 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the context of distributed storage systems and coding, the performance of simple caching, replication and regenerating codes is studied in a D2D scenario in [66], in which a simple decision rule for choosing simple caching and replication is derived for minimizing the expected total cost in terms of energy consumption. On the other hand, the study of the physical layer functionality of wireless distributed storage systems is given in [67] from point of space-time storage codes.…”

Section: Coded Caching Gainsmentioning

confidence: 99%

Proactive Caching in 5G Small Cell Networks

2016

View full text Add to dashboard Cite

Massive deployment of small-cell base stations (SBSs) is going to play a key role for capacity and coverage enhancements in 5G networks. However, the backhaul for these networks remains one of the important issue to solve. Ideally, the capacity of backhaul has to be in the same order of wireless links in order to avoid bottlenecks in the delivery and sustain huge traffic generated by mobile users, especially due to video streaming and content sharing in social networks. In reality, the deployment of such high-speed backhauls is not straightforward due to its costly nature. Thus, one promising way of tackling this backhaul bottleneck and satisfying users' demand is to cache the strategic contents at the edge of the network, namely at the SBSs and user terminals (UTs). So far, most of the existing solutions are based on the reactive networking paradigm in which users' content requests are served immediately upon their arrival or causing outages otherwise. In this chapter, we first provide an overview for recent research in small cell networks (SCNs), and then we explore the novel paradigm of proactive caching in SCNs that leverages the latest developments in storage, context-awareness, and social networking. With this approach, we show that important gains can be obtained, with backhaul offloadings and higher ratios of satisfied users reaching up to 22% and 26%, respectively. I. SMALL CELL NETWORKS: PAST, PRESENT AND FUTURE TRENDS Smartphones have exponentially increased the traffic load in current cellular networks showing no signs of slowing down [1], [2]. It is now well understood that a very effective way to increase network capacity is making cells smaller by reducing the distance to the users [3]. Indeed, cell densification has gone from the order of hundreds of square kilometers (back in the eighties) to a fraction of a square meter or less with the advent of hotspots. There has been recently a great interest to deploy relays, distributed antennas and small cellular access points (such as micro/pico/femto cells) in residential homes, subways, enterprises, and hot-spot areas. These network architectures, which are either operator-deployed or user-deployed are referred to heterogeneous networks (HetNets) or small cell networks (SCNs) [3], [4]. By deploying additional network nodes within local-area range and making the network closer to end-users, small cells can significantly improve spatial reuse and coverage, boost capacity, and offload traffic more efficiently [4].

show abstract

Section: Coded Caching Gainsmentioning

confidence: 99%

Proactive Caching in 5G Small Cell Networks

2016

View full text Add to dashboard Cite

show abstract

“…There have been a few existing works on caching policies for determining the distribution of data files in mobile nodes with the aim of data traffic offloading. In [4], D2D communications and data redundancy are used to decrease the overall energy consumption of mobile cellular systems on the assumption that mobile nodes have infinite storage capacities, in which the caching policy is not necessary to be taken into account. In [5], the probabilities of data files cached at mobile nodes are adjusted to minimize the average caching failure rate.…”

Section: Introductionmentioning

confidence: 99%

Device-to-Device Offloading with Proactive Caching in Mobile Cellular Networks

Lan¹,

Wang²,

Huang³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

View full text Add to dashboard Cite

In this paper, we study the data offloading via device-to-device (D2D) communications with proactive caching in mobile cellular networks. The problem is formulated as the optimal data caching problem, where mobile nodes have different mobility and limited cache capacities and data files have different popularity and content sizes, and is proved to be NP-hard. To deal with the problem, the contacts between mobile nodes are used to adjust the cached data files with a well-designed (1 + α)-approximation algorithm. Based on the analysis, we first propose a distributed infrastructure-assisted data offloading algorithm (IADOA), where the base station (BS) needs to provide information to mobile nodes. To further increase the flexibility, a fully-distributed data offloading algorithm (FDDOA) is designed, where mobile nodes exchange control information via D2D communications and make parameter estimations. Finally, simulation results show that our proposed algorithms have significant performance gains compared with two conventional baseline algorithms.

show abstract

“…For example, by assuming that D2D UE with common interests constructs a cluster for D2D content sharing, the average number of served requests per cluster and optimal cluster size are analyzed in [9,10]. A tractable closed-form equation to find when redundant caching should be used in order to minimize the expected energy consumption was derived in [11]. With the consideration of D2D interference and fading, some works analyze the D2D content delivery performance in [12,13].…”

Section: Introductionmentioning

confidence: 99%

A Device-to-Device Multicast Scheme for Delay-Constraint Content Delivery

Xu¹

2017

Mobile Information Systems

View full text Add to dashboard Cite

Motivated by the explosive increase of mobile traffic, study on the device-to-device (D2D) communication is kicked off for content delivery through proximal transmission among users. D2D multicast has advantage on serving multiple users simultaneously with less resource cost. However, when D2D multicast is appropriate for content delivery and how to make it serve delay-constraint traffic are still unclear. In this paper, parameters impacting on D2D multicast content delivery is investigated to find good chances for utilizing D2D multicast. Furthermore, some rules to be obeyed are proposed for the content caching and delivery of D2D multicast to satisfy delay constraints. Based on these analyses, a delay-aware multicast scheme is proposed to maximize the network performance utility while satisfying delay constraints of contents. Simulations results verify our analyses and show that the proposed scheme can significantly improve multicast efficiency with guaranteed delay.

show abstract

Device-to-device data storage for mobile cellular systems

Cited by 54 publications

References 13 publications

Proactive Caching in 5G Small Cell Networks

Proactive Caching in 5G Small Cell Networks

Device-to-Device Offloading with Proactive Caching in Mobile Cellular Networks

A Device-to-Device Multicast Scheme for Delay-Constraint Content Delivery

Contact Info

Product

Resources

About