The effects of mobility on the hit performance of cached D2D networks

Jarray, Chedia; Giovanidis, Anastasios

doi:10.1109/wiopt.2016.7492958

Cited by 36 publications

(24 citation statements)

References 27 publications

(43 reference statements)

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“…In [106], the mobility pattern of users is considered and the mobility aware caching problem is formulated as an optimization problem aiming at maximize the caching utility and the authors propose a polynomial-time heuristic solution to solve the problem. The impact of user mobility on the hit performance of edge caching is analyzed in [107]. The user mobility is modeled as a discrete time Markov chain in [108].…”

Section: E Mobility Awarenessmentioning

confidence: 99%

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

et al. 2017

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As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on the backhaul links and long latency. Therefore, new architectures which bring network functions and contents to the network edge are proposed, i.e., mobile edge computing and caching. Mobile edge networks provide cloud computing and caching capabilities at the edge of cellular networks. In this survey, we make an exhaustive review on the state-of-the-art research efforts on mobile edge networks. We first give an overview of mobile edge networks including definition, architecture and advantages. Next, a comprehensive survey of issues on computing, caching and communication techniques at the network edge is presented respectively. The applications and use cases of mobile edge networks are discussed. Subsequently, the key enablers of mobile edge networks such as cloud technology, SDN/NFV and smart devices are discussed. Finally, open research challenges and future directions are presented as well.Index Terms-Mobile edge computing, mobile edge caching, D2D, SDN, NFV, content delivery, computational offloading.

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Section: E Mobility Awarenessmentioning

confidence: 99%

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

et al. 2017

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“…It is well known that mathematical methods play a significant role in system modeling and optimization analysis [29][30][31]. To get the probability that a typical mobile user is able to achieve some threshold SINR, the random spatial positions of mobile users need to be modeled by stochastic geometry rather than Monte Carlo methods.…”

Section: Related Workmentioning

confidence: 99%

“…To get the probability that a typical mobile user is able to achieve some threshold SINR, the random spatial positions of mobile users need to be modeled by stochastic geometry rather than Monte Carlo methods. In [29], the authors introduced the service success probability to capture the mobility of users and the activeness of communication links in a cache-enabled D2D cellular network. Simulation results revealed the influence of file size distributions on performance metrics.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of D2D Communication with Retransmission Mechanism in Cellular Networks

et al. 2020

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In this paper, we focus on the performance analysis of device-to-device (D2D) underlay communication in cellular networks. First, we develop a spatiotemporal traffic model to model a retransmission mechanism for D2D underlay communication. The D2D users in backlogged statuses are modeled as a thinned Poisson point process (PPP). To capture the characteristics of sporadic wireless data generation and limited buffer, we adopt queuing theory to analyze the performance of dynamic traffic. Furthermore, a feedback queuing model is adopted to analyze the performance with retransmission strategy. With the consideration of interference and channel fading, the service probability of the queue departure process is determined by the received signal-to-interference-plus-noise ratio (SINR). Then, the embedded Markov chain is employed to depict the queuing status in the D2D user buffer. We compute its steady-state distribution and derive the closed-form expressions of performance metrics, namely the average queue length, average throughput, average delay, and dropping probability. Simulation results show the validity and rationality of the theoretical analysis with different channel parameters and D2D densities. In addition, the simulation explores the dropping probability of a D2D user with and without the retransmission strategy for different D2D links in the system. When the arrival rate is comparatively high, the optimal throughput is reached after fewer retransmission attempts as a result of the limited buffer.

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“…In this work, we hence study the effect of retransmissions on the network performance for both static (same user location during all retransmission attempts) and mobile user scenarios. For the analysis of mobile users, we consider the popular infinite mobility model [9]- [11] in which a user is assumed to experience an independent realization of the point process for each transmission. This model is quite relevant for ultra dense networks where even a small displacement of a user may take it to a completely new local neighborhood of SCBSs.…”

Section: System Modelmentioning

confidence: 99%

Effect of Retransmissions on Optimal Caching in Cache-Enabled Small Cell Networks

Krishnan

Afshang

Dhillon

2017

IEEE Trans. Veh. Technol.

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Caching popular content in the storage of small cells is being considered as an efficient technique to complement limited backhaul of small cells in ultra-dense heterogeneous cellular networks. Limited storage capacity of the small cells renders it important to determine the optimal set of files (cache) to be placed on each small cell. In contrast to prior works on optimal caching, in this work we study the effect of retransmissions on the optimal cache placement policy for both static and mobile user scenarios. With the popularity of files modeled as a Zipf distribution and a maximum n transmissions, i.e., n − 1 retransmissions, allowed to receive each file, we determine the optimal caching probability of the files that maximizes the hit probability. Our closed-form optimal solutions concretely demonstrate that the optimal caching probabilities are very sensitive to the number of retransmissions.

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The effects of mobility on the hit performance of cached D2D networks

Cited by 36 publications

References 27 publications

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications

Performance Analysis of D2D Communication with Retransmission Mechanism in Cellular Networks

Effect of Retransmissions on Optimal Caching in Cache-Enabled Small Cell Networks

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