785 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
Cooperative Multi-Bitrate Video Caching and Transcoding in Multicarrier NOMA-Assisted Heterogeneous Virtualized MEC Networks
Cooperative video caching and transcoding in mobile edge computing (MEC)
networks is a new paradigm for future wireless networks, e.g., 5G and 5G
beyond, to reduce scarce and expensive backhaul resource usage by prefetching
video files within radio access networks (RANs). Integration of this technique
with other advent technologies, such as wireless network virtualization and
multicarrier non-orthogonal multiple access (MC-NOMA), provides more flexible
video delivery opportunities, which leads to enhancements both for the
network's revenue and for the end-users' service experience. In this regard, we
propose a two-phase RAF for a parallel cooperative joint multi-bitrate video
caching and transcoding in heterogeneous virtualized MEC networks. In the cache
placement phase, we propose novel proactive delivery-aware cache placement
strategies (DACPSs) by jointly allocating physical and radio resources based on
network stochastic information to exploit flexible delivery opportunities.
Then, for the delivery phase, we propose a delivery policy based on the user
requests and network channel conditions. The optimization problems
corresponding to both phases aim to maximize the total revenue of network
slices, i.e., virtual networks. Both problems are non-convex and suffer from
high-computational complexities. For each phase, we show how the problem can be
solved efficiently. We also propose a low-complexity RAF in which the
complexity of the delivery algorithm is significantly reduced. A Delivery-aware
cache refreshment strategy (DACRS) in the delivery phase is also proposed to
tackle the dynamically changes of network stochastic information. Extensive
numerical assessments demonstrate a performance improvement of up to 30% for
our proposed DACPSs and DACRS over traditional approaches.Comment: 53 pages, 24 figure
Offloading Content with Self-organizing Mobile Fogs
Mobile users in an urban environment access content on the internet from
different locations. It is challenging for the current service providers to
cope with the increasing content demand from a large number of collocated
mobile users. In-network caching to offload content at nodes closer to users
alleviate the issue, though efficient cache management is required to find out
who should cache what, when and where in an urban environment, given nodes
limited computing, communication and caching resources. To address this, we
first define a novel relation between content popularity and availability in
the network and investigate a node's eligibility to cache content based on its
urban reachability. We then allow nodes to self-organize into mobile fogs to
increase the distributed cache and maximize content availability in a
cost-effective manner. However, to cater rational nodes, we propose a coalition
game for the nodes to offer a maximum "virtual cache" assuming a monetary
reward is paid to them by the service/content provider. Nodes are allowed to
merge into different spatio-temporal coalitions in order to increase the
distributed cache size at the network edge. Results obtained through
simulations using realistic urban mobility trace validate the performance of
our caching system showing a ratio of 60-85% of cache hits compared to the
30-40% obtained by the existing schemes and 10% in case of no coalition
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