1,959 research outputs found
A Transfer Learning Approach for Cache-Enabled Wireless Networks
Locally caching contents at the network edge constitutes one of the most
disruptive approaches in G wireless networks. Reaping the benefits of edge
caching hinges on solving a myriad of challenges such as how, what and when to
strategically cache contents subject to storage constraints, traffic load,
unknown spatio-temporal traffic demands and data sparsity. Motivated by this,
we propose a novel transfer learning-based caching procedure carried out at
each small cell base station. This is done by exploiting the rich contextual
information (i.e., users' content viewing history, social ties, etc.) extracted
from device-to-device (D2D) interactions, referred to as source domain. This
prior information is incorporated in the so-called target domain where the goal
is to optimally cache strategic contents at the small cells as a function of
storage, estimated content popularity, traffic load and backhaul capacity. It
is shown that the proposed approach overcomes the notorious data sparsity and
cold-start problems, yielding significant gains in terms of users'
quality-of-experience (QoE) and backhaul offloading, with gains reaching up to
in a setting consisting of four small cell base stations.Comment: some small fixes in notatio
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Recommended from our members
Economic issues in distributed computing
textOn the Internet, one of the essential characteristics of electronic commerce is the integration of large-scale computer networks and business practices. Commercial servers are connected through open and complex communication technologies, and online consumers access the services with virtually unpredictable behavior. Both of them as well as the e-Commerce infrastructure are vulnerable to cyber attacks. Among the various network security problems, the Distributed Denial-of-Service (DDoS) attack is a unique example to illustrate the risk of commercial network applications. Using a massive junk traffic, literally anyone on the Internet can launch a DDoS attack to flood and shutdown an eCommerce website. Cooperative technological solutions for Distributed Denial-of-Service (DDoS) attacks are already available, yet organizations in the best position to implement them lack incentive to do so, and the victims of DDoS attacks cannot find effective methods to motivate the organizations. Chapter 1 discusses two components of the technological solutions to DDoS attacks: cooperative filtering and cooperative traffic smoothing by caching, and then analyzes the broken incentive chain in each of these technological solutions. As a remedy, I propose usage-based pricing and Capacity Provision Networks, which enable victims to disseminate enough incentive along attack paths to stimulate cooperation against DDoS attacks. Chapter 2 addresses possible Distributed Denial-of-Service (DDoS) attacks toward the wireless Internet including the Wireless Extended Internet, the Wireless Portal Network, and the Wireless Ad Hoc network. I propose a conceptual model for defending against DDoS attacks on the wireless Internet, which incorporates both cooperative technological solutions and economic incentive mechanisms built on usage-based fees. Cost-effectiveness is also addressed through an illustrative implementation scheme using Policy Based Networking (PBN). By investigating both technological and economic difficulties in defense of DDoS attacks which have plagued the wired Internet, our aim here is to foster further development of wireless Internet infrastructure as a more secure and efficient platform for mobile commerce. To avoid centralized resources and performance bottlenecks, online peer-to-peer communities and online social network have become increasingly popular. In particular, the recent boost of online peer-to-peer communities has led to exponential growth in sharing of user-contributed content which has brought profound changes to business and economic practices. Understanding the dynamics and sustainability of such peer-to-peer communities has important implications for business managers. In Chapter 3, I explore the structure of online sharing communities from a dynamic process perspective. I build an evolutionary game model to capture the dynamics of online peer-to-peer communities. Using online music sharing data collected from one of the IRC Channels for over five years, I empirically investigate the model which underlies the dynamics of the music sharing community. Our empirical results show strong support for the evolutionary process of the community. I find that the two major parties in the community, namely sharers and downloaders, are influencing each other in their dynamics of evolvement in the community. These dynamics reveal the mechanism through which peer-to-peer communities sustain and thrive in a constant changing environment.Information, Risk, and Operations Management (IROM
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
A Learning-Based Approach to Caching in Heterogenous Small Cell Networks
A heterogenous network with base stations (BSs), small base stations (SBSs)
and users distributed according to independent Poisson point processes is
considered. SBS nodes are assumed to possess high storage capacity and to form
a distributed caching network. Popular files are stored in local caches of
SBSs, so that a user can download the desired files from one of the SBSs in its
vicinity. The offloading-loss is captured via a cost function that depends on
the random caching strategy proposed here. The popularity profile of cached
content is unknown and estimated using instantaneous demands from users within
a specified time interval. An estimate of the cost function is obtained from
which an optimal random caching strategy is devised. The training time to
achieve an difference between the achieved and optimal costs is
finite provided the user density is greater than a predefined threshold, and
scales as , where is the support of the popularity profile. A transfer
learning-based approach to improve this estimate is proposed. The training time
is reduced when the popularity profile is modeled using a parametric family of
distributions; the delay is independent of and scales linearly with the
dimension of the distribution parameter.Comment: 12 pages, 5 figures, published in IEEE Transactions on
Communications, 2016. arXiv admin note: text overlap with arXiv:1504.0363
- …