Evaluating the Raw Potential for Device-to-Device Caching via Co-location

Hu, Xueheng; Meng, Lei; Striegel, Aaron

doi:10.1016/j.procs.2014.07.042

Cited by 8 publications

(4 citation statements)

References 17 publications

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“…For such D2D caching networks, PPP is an appealing arXiv:2003.10809v1 [cs.IT] 24 Mar 2020 analytical framework due to its simplicity and tractability [15] and [16]. However, a realistic model for D2D caching networks needs to capture the notion of device clustering, which is fundamental to the D2D network architecture [17] and [18]. Clustered D2D models imply that a given device typically has multiple proximate devices, where any of them can act as a serving device.…”

Section: A State Of the Art And Prior Workmentioning

confidence: 99%

Optimized Caching and Spectrum Partitioning for D2D Enabled Cellular Systems With Clustered Devices

Amer

ElSawy

Butt

et al. 2020

IEEE Trans. Commun.

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Caching at mobile devices and leveraging deviceto-device (D2D) communication are two promising approaches to support massive content delivery over wireless networks. The analysis of cache-enabled wireless networks is usually carried out by assuming that devices are uniformly distributed, however, in social networks, mobile devices are intrinsically grouped into disjoint clusters. In this regards, this paper proposes a spatiotemporal mathematical model that tracks the service requests arrivals and account for the clustered devices geometry. Two kinds of devices are assumed, particularly, content clients and content providers. Content providers are assumed to have a surplus memory which is exploited to proactively cache contents from a known library, following a random probabilistic caching scheme. Content clients can retrieve a requested content from the nearest content provider in their proximity (cluster), or, as a last resort, the base station (BS). The developed spatiotemporal model is leveraged to formulate a joint optimization problem of the content caching and spectrum partitioning in order to minimize the average service delay. Due to the high complexity of the optimization problem, the caching and spectrum partitioning problems are decoupled and solved iteratively using the block coordinate descent (BCD) optimization technique. To this end, an optimal and suboptimal solutions are obtained for the bandwidth partitioning and probabilistic caching subproblems, respectively. Numerical results highlight the superiority of the proposed scheme over conventional caching schemes under equal and optimized bandwidth allocations. Particularly, it is shown that the average service delay is reduced by nearly 100% and 350%, compared to the Zipf and uniform caching schemes under equal bandwidth allocations, respectively.

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Section: A State Of the Art And Prior Workmentioning

confidence: 99%

Optimized Caching and Spectrum Partitioning for D2D Enabled Cellular Systems With Clustered Devices

Amer

ElSawy

Butt

et al. 2020

IEEE Trans. Commun.

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show abstract

“…Similar data collection strategies and the use of Bluetooth proximity for finding real-world group gatherings were used and validated by others in 8,[24][25][26][27][28] . Table 1 lists the details about the groups identified from the Bluetooth data.…”

Section: Resultsmentioning

confidence: 99%

Creation, evolution, and dissolution of social groups

Flamino

Szymański

Bahulkar

et al. 2021

Sci Rep

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Understanding why people join, stay, or leave social groups is a central question in the social sciences, including computational social systems, while modeling these processes is a challenge in complex networks. Yet, the current empirical studies rarely focus on group dynamics for lack of data relating opinions to group membership. In the NetSense data, we find hundreds of face-to-face groups whose members make thousands of changes of memberships and opinions. We also observe two trends: opinion homogeneity grows over time, and individuals holding unpopular opinions frequently change groups. These observations and data provide us with the basis on which we model the underlying dynamics of human behavior. We formally define the utility that members gain from ingroup interactions as a function of the levels of homophily of opinions of group members with opinions of a given individual in this group. We demonstrate that so-defined utility applied to our empirical data increases after each observed change. We then introduce an analytical model and show that it accurately recreates the trends observed in the NetSense data.

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“…While interesting, the works in [17]- [19] did not consider the notion of device clustering, which is quite fundamental to the D2D network architecture [20] and [21]. In this regard, the authors in [22] developed a stochastic geometry-based model to characterize the performance of content delivery in a clustered D2D network whose devices are distributed according to a Poisson cluster process (PCP).…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis and Optimization of Cache-Assisted CoMP for Clustered D2D Networks

Amer¹,

ElSawy²,

Kibiłda³

et al. 2020

Preprint

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Caching at mobile devices and leveraging cooperative device-to-device (D2D) communications are two promising approaches to support massive content delivery over wireless networks while mitigating the effects of interference. To show the impact of cooperative communication on the performance of cache-enabled D2D networks, the notion of device clustering must be factored in to convey a realistic description of the network performance. In this regard, this paper develops a novel mathematical model, based on stochastic geometry and an optimization framework for cache-assisted coordinated multi-point (CoMP) transmissions with clustered devices. Devices are spatially distributed into disjoint clusters and are assumed to have a surplus memory to cache files from a known library, following a random probabilistic caching scheme. Desired contents that are not self-cached can be obtained via D2D CoMP transmissions from neighboring devices or, as a last resort, from the network. For this model, we analytically characterize the offloading gain and rate coverage probability as functions of the system parameters. An optimal caching strategy is then defined as the content placement scheme that maximizes the offloading gain. For a tractable optimization framework, we pursue two separate approaches to obtain a lower bound and a provably accurate approximation of the offloading gain, which allows us to obtain optimized caching strategies. Remarkably, if we replace the obtained expression for offloading gain with its lower bound, we can find a suboptimal caching strategy that is not only described via analytical formulas but can also show an improvement over the state-of-the-art caching schemes. Results reveal that cooperative transmission becomes more appealing in denser D2D caching networks and adverse interference conditions, which is the case of the imminent internet of things (IoT) and massive machine type communications era.

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Evaluating the Raw Potential for Device-to-Device Caching via Co-location

Cited by 8 publications

References 17 publications

Optimized Caching and Spectrum Partitioning for D2D Enabled Cellular Systems With Clustered Devices

Optimized Caching and Spectrum Partitioning for D2D Enabled Cellular Systems With Clustered Devices

Creation, evolution, and dissolution of social groups

Performance Analysis and Optimization of Cache-Assisted CoMP for Clustered D2D Networks

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