1,359 research outputs found
Incentive Mechanism Design for Cache-Assisted D2D Communications: A Mobility-Aware Approach
Caching popular contents at mobile devices, assisted by device-to-device
(D2D) communications, is considered as a promising technique for mobile content
delivery. It can effectively reduce backhaul traffic and service cost, as well
as improving the spectrum efficiency. However, due to the selfishness of mobile
users, incentive mechanisms will be needed to motivate device caching. In this
paper, we investigate incentive mechanism design in cache-assisted D2D
networks, taking advantage of the user mobility information. An inter-contact
model is adopted to capture the average time between two consecutive contacts
of each device pair. A Stackelberg game is formulated, where each user plays as
a follower aiming at maximizing its own utility and the mobile network operator
(MNO) plays as a leader aiming at minimizing the cost. Assuming that user
responses can be predicted by the MNO, a cost minimization problem is
formulated. Since this problem is NP-hard, we reformulate it as a non-negative
submodular maximization problem and develop
-approximation local search algorithm to solve it. In
the simulation, we demonstrate that the local search algorithm provides near
optimal performance. By comparing with other caching strategies, we validate
the effectiveness of the proposed incentive-based mobility-aware caching
strategy.Comment: 5 pages, 3 figures, accepted to IEEE SPAWC, Sapporo, Japan, July 201
Fog Computing based Radio Access Networks: Issues and Challenges
A fog computing based radio access network (F-RAN) is presented in this
article as a promising paradigm for the fifth generation (5G) wireless
communication system to provide high spectral and energy efficiency. The core
idea is to take full advantages of local radio signal processing, cooperative
radio resource management, and distributed storing capabilities in edge
devices, which can decrease the heavy burden on fronthaul and avoid large-scale
radio signal processing in the centralized baseband unit pool. This article
comprehensively presents the system architecture and key techniques of F-RANs.
In particular, key techniques and their corresponding solutions, including
transmission mode selection and interference suppression, are discussed. Open
issues in terms of edge caching, software-defined networking, and network
function virtualization, are also identified.Comment: 21 pages, 7 figures, accepted by IEEE Networks Magazin
Analysis on Cache-enabled Wireless Heterogeneous Networks
Caching the popular multimedia content is a promising way to unleash the
ultimate potential of wireless networks. In this paper, we contribute to
proposing and analyzing the cache-based content delivery in a three-tier
heterogeneous network (HetNet), where base stations (BSs), relays and
device-to-device (D2D) pairs are included. We advocate to proactively cache the
popular contents in the relays and parts of the users with caching ability when
the network is off-peak. The cached contents can be reused for frequent access
to offload the cellular network traffic. The node locations are first modeled
as mutually independent Poisson Point Processes (PPPs) and the corresponding
content access protocol is developed. The average ergodic rate and outage
probability in the downlink are then analyzed theoretically. We further derive
the throughput and the delay based on the \emph{multiclass processor-sharing
queue} model and the continuous-time Markov process. According to the critical
condition of the steady state in the HetNet, the maximum traffic load and the
global throughput gain are investigated. Moreover, impacts of some key network
characteristics, e.g., the heterogeneity of multimedia contents, node densities
and the limited caching capacities, on the system performance are elaborated to
provide a valuable insight
Recent Advances in Fog Radio Access Networks: Performance Analysis and Radio Resource Allocation
As a promising paradigm for the fifth generation wireless communication (5G)
system, the fog radio access network (F-RAN) has been proposed as an advanced
socially-aware mobile networking architecture to provide high spectral
efficiency (SE) while maintaining high energy efficiency (EE) and low latency.
Recent advents are advocated to the performance analysis and radio resource
allocation, both of which are fundamental issues to make F-RANs successfully
rollout. This article comprehensively summarizes the recent advances of the
performance analysis and radio resource allocation in F-RANs. Particularly, the
advanced edge cache and adaptive model selection schemes are presented to
improve SE and EE under maintaining a low latency level. The radio resource
allocation strategies to optimize SE and EE in F-RANs are respectively
proposed. A few open issues in terms of the F-RAN based 5G architecture and the
social-awareness technique are identified as well
Individual Preference Aware Caching Policy Design in Wireless D2D Networks
Cache-aided wireless device-to-device (D2D) networks allow significant
throughput increase, depending on the concentration of the popularity
distribution of files. Many studies assume that all users have the same
preference distribution; however, this may not be true in practice. This work
investigates whether and how the information about individual preferences can
benefit cache-aided D2D networks. We examine a clustered network and derive a
network utility that considers both the user distribution and channel fading
effects into the analysis. We also formulate a utility maximization problem for
designing caching policies. This maximization problem can be applied to
optimize several important quantities, including throughput, energy efficiency
(EE), cost, and hit-rate, and to solve different tradeoff problems. We provide
a general approach that can solve the proposed problem under the assumption
that users coordinate, then prove that the proposed approach can obtain the
stationary point under a mild assumption. Using simulations of practical
setups, we show that performance can improve significantly with proper
exploitation of individual preferences. We also show that different types of
tradeoffs exist between different performance metrics and that they can be
managed through caching policy and cooperation distance designs.Comment: Accepted by IEEE Transactions on Wireless Communication
Cloud Computing - Architecture and Applications
In the era of Internet of Things and with the explosive worldwide growth of
electronic data volume, and associated need of processing, analysis, and
storage of such humongous volume of data, it has now become mandatory to
exploit the power of massively parallel architecture for fast computation.
Cloud computing provides a cheap source of such computing framework for large
volume of data for real-time applications. It is, therefore, not surprising to
see that cloud computing has become a buzzword in the computing fraternity over
the last decade. This book presents some critical applications in cloud
frameworks along with some innovation design of algorithms and architecture for
deployment in cloud environment. It is a valuable source of knowledge for
researchers, engineers, practitioners, and graduate and doctoral students
working in the field of cloud computing. It will also be useful for faculty
members of graduate schools and universities.Comment: Edited Volume published by Intech Publishers, Croatia, June 2017. 138
pages. ISBN 978-953-51-3244-8, Print ISBN 978-953-51-3243-1. Link:
https://www.intechopen.com/books/cloud-computing-architecture-and-application
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
Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey
This paper presents a comprehensive literature review on applications of
economic and pricing theory for resource management in the evolving fifth
generation (5G) wireless networks. The 5G wireless networks are envisioned to
overcome existing limitations of cellular networks in terms of data rate,
capacity, latency, energy efficiency, spectrum efficiency, coverage,
reliability, and cost per information transfer. To achieve the goals, the 5G
systems will adopt emerging technologies such as massive Multiple-Input
Multiple-Output (MIMO), mmWave communications, and dense Heterogeneous Networks
(HetNets). However, 5G involves multiple entities and stakeholders that may
have different objectives, e.g., high data rate, low latency, utility
maximization, and revenue/profit maximization. This poses a number of
challenges to resource management designs of 5G. While the traditional
solutions may neither efficient nor applicable, economic and pricing models
have been recently developed and adopted as useful tools to achieve the
objectives. In this paper, we review economic and pricing approaches proposed
to address resource management issues in the 5G wireless networks including
user association, spectrum allocation, and interference and power management.
Furthermore, we present applications of economic and pricing models for
wireless caching and mobile data offloading. Finally, we highlight important
challenges, open issues and future research directions of applying economic and
pricing models to the 5G wireless networks
Fundamentals of Cluster-Centric Content Placement in Cache-Enabled Device-to-Device Networks
This paper develops a comprehensive analytical framework with foundations in
stochastic geometry to characterize the performance of cluster-centric content
placement in a cache-enabled device-to-device (D2D) network. Different from
device-centric content placement, cluster-centric placement focuses on placing
content in each cluster such that the collective performance of all the devices
in each cluster is optimized. Modeling the locations of the devices by a
Poisson cluster process, we define and analyze the performance for three
general cases: (i)-Tx case: receiver of interest is chosen uniformly at
random in a cluster and its content of interest is available at the
closest device to the cluster center, (ii) -Rx case: receiver of interest
is the closest device to the cluster center and its content of
interest is available at a device chosen uniformly at random from the same
cluster, and (iii) baseline case: the receiver of interest is chosen uniformly
at random in a cluster and its content of interest is available at a device
chosen independently and uniformly at random from the same cluster. Easy-to-use
expressions for the key performance metrics, such as coverage probability and
area spectral efficiency (ASE) of the whole network, are derived for all three
cases. Our analysis concretely demonstrates significant improvement in the
network performance when the device on which content is cached or device
requesting content from cache is biased to lie closer to the cluster center
compared to baseline case. Based on this insight, we develop and analyze a new
generative model for cluster-centric D2D networks that allows to study the
effect of intra-cluster interfering devices that are more likely to lie closer
to the cluster center.Comment: 16 pages, 10 figures. Submitted to IEEE Transactions on
Communication
Caching Policy Optimization for D2D Communications by Learning User Preference
Cache-enabled device-to-device (D2D) communications can boost network
throughput. By pre-downloading contents to local caches of users, the content
requested by a user can be transmitted via D2D links by other users in
proximity. Prior works optimize the caching policy at users with the knowledge
of content popularity, defined as the probability distribution of request for
every file in a library from by all users. However, content popularity can not
reflect the interest of each individual user and thus popularity-based caching
policy may not fully capture the performance gain introduced by caching. In
this paper, we optimize caching policy for cache-enabled D2D by learning user
preference, defined as the conditional probability distribution of a user's
request for a file given that the user sends a request. We first formulate an
optimization problem with given user preference to maximize the offloading
probability, which is proved as NP-hard, and then provide a greedy algorithm to
find the solution. In order to predict the preference of each individual user,
we model the user request behavior by probabilistic latent semantic analysis
(pLSA), and then apply expectation maximization (EM) algorithm to estimate the
model parameters. Simulation results show that the user preference can be
learnt quickly. Compared to the popularity-based caching policy, the offloading
gain achieved by the proposed policy can be remarkably improved even with
predicted user preference.Comment: Accepted by VTC Spring 201
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