3,253 research outputs found
Stochastic Content-Centric Multicast Scheduling for Cache-Enabled Heterogeneous Cellular Networks
Caching at small base stations (SBSs) has demonstrated significant benefits
in alleviating the backhaul requirement in heterogeneous cellular networks
(HetNets). While many existing works focus on what contents to cache at each
SBS, an equally important problem is what contents to deliver so as to satisfy
dynamic user demands given the cache status. In this paper, we study optimal
content delivery in cache-enabled HetNets by taking into account the inherent
multicast capability of wireless medium. We consider stochastic content
multicast scheduling to jointly minimize the average network delay and power
costs under a multiple access constraint. We establish a content-centric
request queue model and formulate this stochastic optimization problem as an
infinite horizon average cost Markov decision process (MDP). By using
\emph{relative value iteration} and special properties of the request queue
dynamics, we characterize some properties of the value function of the MDP.
Based on these properties, we show that the optimal multicast scheduling policy
is of threshold type. Then, we propose a structure-aware optimal algorithm to
obtain the optimal policy. We also propose a low-complexity suboptimal policy,
which possesses similar structural properties to the optimal policy, and
develop a low-complexity algorithm to obtain this policy.Comment: Accepted to IEEE Trans. on Wireless Communications (June 6, 2016).
Conference version appears in ACM CoNEXT 2015 Workshop on Content Caching and
Delivery in Wireless Networks (CCDWN
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications
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
Joint Frequency Reuse and Cache Optimization in Backhaul-Limited Small-Cell Wireless Networks
Caching at base stations (BSs) is a promising approach for supporting the
tremendous traffic growth of content delivery over future small-cell wireless
networks with limited backhaul. This paper considers exploiting spatial caching
diversity (i.e., caching different subsets of popular content files at
neighboring BSs) that can greatly improve the cache hit probability, thereby
leading to a better overall system performance. A key issue in exploiting
spatial caching diversity is that the cached content may not be located at the
nearest BS, which means that to access such content, a user needs to overcome
strong interference from the nearby BSs; this significantly limits the gain of
spatial caching diversity. In this paper, we consider a joint design of
frequency reuse and caching, such that the benefit of an improved cache hit
probability induced by spatial caching diversity and the benefit of
interference coordination induced by frequency reuse can be achieved
simultaneously. We obtain a closed-form characterization of the approximate
successful transmission probability for the proposed scheme and analyze the
impact of key operating parameters on the performance. We design a
low-complexity algorithm to optimize the frequency reuse factor and the cache
storage allocation. Simulations show that the proposed scheme achieves a higher
successful transmission probability than existing caching schemes
Joint Caching and Resource Allocation in D2D-Assisted Wireless HetNet
5G networks are required to provide very fast and reliable communications
while dealing with the increase of users traffic. In Heterogeneous Networks
(HetNets) assisted with Device-to-Device (D2D) communication, traffic can be
offloaded to Small Base Stations or to users to improve the network's
successful data delivery rate. In this paper, we aim at maximizing the average
number of files that are successfully delivered to users, by jointly optimizing
caching placement and channel allocation in cache-enabled D2D-assisted HetNets.
At first, an analytical upper-bound on the average content delivery delay is
derived. Then, the joint optimization problem is formulated. The non-convexity
of the problem is alleviated, and the optimal solution is determined. Due to
the high time complexity of the obtained solution, a low-complex sub-optimal
approach is proposed. Numerical results illustrate the efficacy of the proposed
solutions and compare them to conventional approaches. Finally, by
investigating the impact of key parameters, e.g. power, caching capacity, QoS
requirements, etc., guidelines to design these networks are obtained.Comment: 24 pages, 5 figures, submitted to IEEE Transactions on Wireless
Communications (12-Feb-2019
Cooperative Hierarchical Caching in 5G Cloud Radio Access Networks (C-RANs)
Over the last few years, Cloud Radio Access Network (C-RAN) has arisen as a
transformative architecture for 5G cellular networks that brings the
flexibility and agility of cloud computing to wireless communications. At the
same time, content caching in wireless networks has become an essential
solution to lower the content-access latency and backhaul traffic loading,
which translate into user Quality of Experience (QoE) improvement and network
cost reduction. In this article, a novel Cooperative Hierarchical Caching (CHC)
framework in C-RAN is introduced where contents are jointly cached at the
BaseBand Unit (BBU) and at the Radio Remote Heads (RRHs). Unlike in traditional
approaches, the cache at the BBU, cloud cache, presents a new layer in the
cache hierarchy, bridging the latency/capacity gap between the traditional
edge-based and core-based caching schemes. Trace-driven simulations reveal that
CHC yields up to 80% improvement in cache hit ratio, 21% decrease in average
content-access latency, and 20% reduction in backhaul traffic load compared to
the edge-only caching scheme with the same total cache capacity. Before closing
the article, several challenges and promising opportunities for deploying
content caching in C-RAN are highlighted towards a content-centric mobile
wireless network.Comment: to appear on IEEE Network, July 201
Wireless Video Caching and Dynamic Streaming under Differentiated Quality Requirements
This paper considers one-hop device-to-device (D2D)-assisted wireless caching
networks that cache video files of varying quality levels, with the assumption
that the base station can control the video quality but cache-enabled devices
cannot. Two problems arise in such a caching network: file placement problem
and node association problem. This paper suggests a method to cache videos of
different qualities, and thus of varying file sizes, by maximizing the sum of
video quality measures that users can enjoy. There exists an interesting
trade-off between video quality and video diversity, i.e., the ability to
provision diverse video files. By caching high-quality files, the cache-enabled
devices can provide high-quality video, but cannot cache a variety of files.
Conversely, when the device caches various files, it cannot provide a good
quality for file-requesting users. In addition, when multiple devices cache the
same file but their qualities are different, advanced node association is
required for file delivery. This paper proposes a node association algorithm
that maximizes time-averaged video quality for multiple users under a playback
delay constraint. In this algorithm, we also consider request collision, the
situation where several users request files from the same device at the same
time, and we propose two ways to cope with the collision: scheduling of one
user and non-orthogonal multiple access. Simulation results verify that the
proposed caching method and the node association algorithm work reliably.Comment: 13 pages, 11 figures, accepted for publication in IEEE Journal on
Selected Areas in Communication
Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges and Opportunities
The ever-increasing mobile data demands have posed significant challenges in
the current radio access networks, while the emerging computation-heavy
Internet of things (IoT) applications with varied requirements demand more
flexibility and resilience from the cloud/edge computing architecture. In this
article, to address the issues, we propose a novel air-ground integrated mobile
edge network (AGMEN), where UAVs are flexibly deployed and scheduled, and
assist the communication, caching, and computing of the edge network. In
specific, we present the detailed architecture of AGMEN, and investigate the
benefits and application scenarios of drone-cells, and UAV-assisted edge
caching and computing. Furthermore, the challenging issues in AGMEN are
discussed, and potential research directions are highlighted.Comment: Accepted by IEEE Communications Magazine. 5 figure
A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions
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.Comment: Accepted in IEEE Communications Surveys and Tutorial
Single or Multiple Frames Content Delivery for Next-Generation Networks?
This paper addresses the four enabling technologies, namely multi-user sparse
code multiple access (SCMA), content caching, energy harvesting, and physical
layer security for proposing an energy and spectral efficient resource
allocation algorithm for the access and backhaul links in heterogeneous
cellular networks. Although each of the above mentioned issues could be a topic
of research, in a real situation, we would face a complicated scenario where
they should be considered jointly, and hence, our target is to consider these
technologies jointly in a unified framework. Moreover, we propose two novel
content delivery scenarios: 1) single frame content delivery (SFCD), and 2)
multiple frames content delivery (MFCD), where the time duration of serving
user requests is divided into several frames. In the first scenario, the
requested content by each user is served over one frame. However, in the second
scenario, the requested content by each user can be delivered over several
frames. We formulate the resource allocation for the proposed scenarios as
optimization problems where our main aim is to maximize the energy efficiency
of access links subject to the transmit power and rate constraints of access
and backhaul links, caching and energy harvesting constraints, and SCMA
codebook allocation limitations. Due to the practical limitations, we assume
that the channel state information values between eavesdroppers and base
stations are uncertain and design the network for the worst case scenario.
Since the corresponding optimization problems are mixed integer non-linear and
nonconvex programming, NP-hard, and intractable, we propose an iterative
algorithm based on the well-known alternate and successive convex approximation
methods
Machine Intelligence Techniques for Next-Generation Context-Aware Wireless Networks
The next generation wireless networks (i.e. 5G and beyond), which would be
extremely dynamic and complex due to the ultra-dense deployment of
heterogeneous networks (HetNets), poses many critical challenges for network
planning, operation, management and troubleshooting. At the same time,
generation and consumption of wireless data are becoming increasingly
distributed with ongoing paradigm shift from people-centric to machine-oriented
communications, making the operation of future wireless networks even more
complex. In mitigating the complexity of future network operation, new
approaches of intelligently utilizing distributed computational resources with
improved context-awareness becomes extremely important. In this regard, the
emerging fog (edge) computing architecture aiming to distribute computing,
storage, control, communication, and networking functions closer to end users,
have a great potential for enabling efficient operation of future wireless
networks. These promising architectures make the adoption of artificial
intelligence (AI) principles which incorporate learning, reasoning and
decision-making mechanism, as natural choices for designing a tightly
integrated network. Towards this end, this article provides a comprehensive
survey on the utilization of AI integrating machine learning, data analytics
and natural language processing (NLP) techniques for enhancing the efficiency
of wireless network operation. In particular, we provide comprehensive
discussion on the utilization of these techniques for efficient data
acquisition, knowledge discovery, network planning, operation and management of
the next generation wireless networks. A brief case study utilizing the AI
techniques for this network has also been provided.Comment: ITU Special Issue N.1 The impact of Artificial Intelligence (AI) on
communication networks and services, (To appear
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