182 research outputs found
Edge-Caching Wireless Networks: Performance Analysis and Optimization
Edge-caching has received much attention as an efficient technique to reduce
delivery latency and network congestion during peak-traffic times by bringing
data closer to end users. Existing works usually design caching algorithms
separately from physical layer design. In this paper, we analyse edge-caching
wireless networks by taking into account the caching capability when designing
the signal transmission. Particularly, we investigate multi-layer caching where
both base station (BS) and users are capable of storing content data in their
local cache and analyse the performance of edge-caching wireless networks under
two notable uncoded and coded caching strategies. Firstly, we propose a coded
caching strategy that is applied to arbitrary values of cache size. The
required backhaul and access rates are derived as a function of the BS and user
cache size. Secondly, closed-form expressions for the system energy efficiency
(EE) corresponding to the two caching methods are derived. Based on the derived
formulas, the system EE is maximized via precoding vectors design and
optimization while satisfying a predefined user request rate. Thirdly, two
optimization problems are proposed to minimize the content delivery time for
the two caching strategies. Finally, numerical results are presented to verify
the effectiveness of the two caching methods.Comment: to appear in IEEE Trans. Wireless Commu
Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks
This article explores one of the key enablers of beyond G wireless
networks leveraging small cell network deployments, namely proactive caching.
Endowed with predictive capabilities and harnessing recent developments in
storage, context-awareness and social networks, peak traffic demands can be
substantially reduced by proactively serving predictable user demands, via
caching at base stations and users' devices. In order to show the effectiveness
of proactive caching, we examine two case studies which exploit the spatial and
social structure of the network, where proactive caching plays a crucial role.
Firstly, in order to alleviate backhaul congestion, we propose a mechanism
whereby files are proactively cached during off-peak demands based on file
popularity and correlations among users and files patterns. Secondly,
leveraging social networks and device-to-device (D2D) communications, we
propose a procedure that exploits the social structure of the network by
predicting the set of influential users to (proactively) cache strategic
contents and disseminate them to their social ties via D2D communications.
Exploiting this proactive caching paradigm, numerical results show that
important gains can be obtained for each case study, with backhaul savings and
a higher ratio of satisfied users of up to and , respectively.
Higher gains can be further obtained by increasing the storage capability at
the network edge.Comment: accepted for publication in IEEE Communications Magazin
Breaking the Economic Barrier of Caching in Cellular Networks: Incentives and Contracts
In this paper, a novel approach for providing incentives for caching in small
cell networks (SCNs) is proposed based on the economics framework of contract
theory. In this model, a mobile network operator (MNO) designs contracts that
will be offered to a number of content providers (CPs) to motivate them to
cache their content at the MNO's small base stations (SBSs). A practical model
in which information about the traffic generated by the CPs' users is not known
to the MNO is considered. Under such asymmetric information, the incentive
contract between the MNO and each CP is properly designed so as to determine
the amount of allocated storage to the CP and the charged price by the MNO. The
contracts are derived by the MNO in a way to maximize the global benefit of the
CPs and prevent them from using their private information to manipulate the
outcome of the caching process. For this interdependent contract model, the
closed-form expressions of the price and the allocated storage space to each CP
are derived. This proposed mechanism is shown to satisfy the sufficient and
necessary conditions for the feasibility of a contract. Moreover, it is shown
that the proposed pricing model is budget balanced, enabling the MNO to cover
all the caching expenses via the prices charged to the CPs. Simulation results
show that none of the CPs will have an incentive to choose a contract designed
for CPs with different traffic loads.Comment: Accepted for publication at Globecom 201
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