P2P Caching Schemes for Jointly Minimizing Memory Cost and Transmission Delay over Information-Centric Networks

Zhang, Xi; Zhu, Quanxin

doi:10.1109/glocom.2016.7842121

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Moreover, the gains of the proposed scheme will be increased in more diverse and heavier load traffics. In [204], the aim of the work is to minimize the data transmission delay for the P2P caching system while considering the effect of cache size, all mobiles in a cell are considered as several P2P caching groups. Then, the problem is formulated as a stochastic optimization problem and solved using Markov decision process (MDP) to obtain the optimal solution.…”

Section: Existing Caching Solutions For 5gmentioning

confidence: 99%

“…Centralized caching [196]- [198], [201], [203], [205]- [211], [213]- [217] Various centralized caching is investigated with assumption that a coordinator with access to almost all the information about the storage capacities of different BSs, the connectivity of the users and BSs, and etc. Distributed caching [199], [200], [202], [204], [212], [215], [218] Various aspects of distributed caching has been investigated in order to minimize the communication overhead among SBSs and the central scheduler.…”

Section: Aspectmentioning

confidence: 99%

“…As defined in Table XIX, from an information theoretic point of view, authors employed the metrics such as normalized delivery time (NDT), fractional delivery time (FDT), and delivery time per bit (DTB) for investigation of the latency storage trade-off in caching networks. In most of these works [199], [200], [202], [204], [212], [215], [218], for a given scenario, an upper bound or lower bound for the considered metric is derived in order to get useful insights of this trade-off. The summary of latency storage trade-off works is presented in Table XX.…”

Section: B Fundamental Latency-storage Trade-off In Cachingmentioning

confidence: 99%

See 2 more Smart Citations

A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions

Parvez

Rahmati

Güvenç

et al. 2018

IEEE Commun. Surv. Tutorials

769

395

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The fifth generation (5G) wireless network technology is to be standardized by 2020, where main goals are to improve capacity, reliability, and energy efficiency, while reducing latency and massively increasing connection density. An integral part of 5G is the capability to transmit touch perception type real-time communication empowered by applicable robotics and haptics equipment at the network edge. In this regard, we need drastic changes in network architecture including core and radio access network (RAN) for achieving end-to-end latency on the order of 1 ms. In this paper, we present a detailed survey on the emerging technologies to achieve low latency communications considering three different solution domains: RAN, core network, and caching. We also present a general overview of 5G cellular networks composed of software defined network (SDN), network function virtualization (NFV), caching, and mobile edge computing (MEC) capable of meeting latency and other 5G requirements.

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Section: Existing Caching Solutions For 5gmentioning

confidence: 99%

Section: Aspectmentioning

confidence: 99%

Section: B Fundamental Latency-storage Trade-off In Cachingmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions

Parvez

Rahmati

Güvenç

et al. 2018

IEEE Commun. Surv. Tutorials

769

395

View full text Add to dashboard Cite

show abstract

“…In [27], in order to solve the challenge of providing scalable video streaming for adaptive requests with different bit rates, Li et al propose a heuristic strategy which optimizes cache placement decisions. In [28], Zhang et al divide users into several P2P cache groups, where a mobile user can obtain his requested data content from a peer mobile user in the same group. In this paper, we extend this setting by assuming users are divided into disjoint regions and considering user mobility.…”

Section: Related Workmentioning

confidence: 99%

Cache Replacement Strategy With Limited Service Capacity in Heterogeneous Networks

Jiang

Zhang

2020

IEEE Access

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Recently, cellular networks face a huge challenge to satisfy large increment of user demands for higher-speed and lower-latency communication service. One promising solution is to apply the cache technology in edge cache networks to reduce redundant data transmission. The cache technology is effective, but the cache capacity is limited. Researchers have proposed various cache strategies to efficiently utilize the limited cache capacity. However, most existing solutions have not taken into account the service capacity limitation of mobile devices. In this paper, we propose a cache replacement strategy for heterogeneous networks considering the limitation of service capacity and user mobility. In the cache replacement strategy, we utilize the user characteristics, such as user mobility and file popularity, to estimate the user demands, and then define the system cost. We formulate the cache strategy design as a mixed integer linear programming problem to minimize the system cost, and use Lagrangian relaxation and hierarchical primal-dual decomposition method to solve this problem. Numerical results show that the proposed cache strategy can significantly reduce the system cost and increase the cache hit ratio compared to the cache strategy that does not consider the limitation of user service capacity.

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