63,887 research outputs found
NOMA based resource allocation and mobility enhancement framework for IoT in next generation cellular networks
With the unprecedented technological advances witnessed in the last two decades, more devices are connected to the internet, forming what is called internet of things (IoT). IoT devices with heterogeneous characteristics and quality of experience (QoE) requirements may engage in dynamic spectrum market due to scarcity of radio resources. We propose a framework to efficiently quantify and supply radio resources to the IoT devices by developing intelligent systems. The primary goal of the paper is to study the characteristics of the next generation of cellular networks with non-orthogonal multiple access (NOMA) to enable connectivity to clustered IoT devices. First, we demonstrate how the distribution and QoE requirements of IoT devices impact the required number of radio resources in real time. Second, we prove that using an extended auction algorithm by implementing a series of complementary functions, enhance the radio resource utilization efficiency. The results show substantial reduction in the number of sub-carriers required when compared to conventional orthogonal multiple access (OMA) and the intelligent clustering is scalable and adaptable to the cellular environment. Ability to move spectrum usages from one cluster to other clusters after borrowing when a cluster has less user or move out of the boundary is another soft feature that contributes to the reported radio resource utilization efficiency. Moreover, the proposed framework provides IoT service providers cost estimation to control their spectrum acquisition to achieve required quality of service (QoS) with guaranteed bit rate (GBR) and non-guaranteed bit rate (Non-GBR)
A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing
Edge computing is promoted to meet increasing performance needs of
data-driven services using computational and storage resources close to the end
devices, at the edge of the current network. To achieve higher performance in
this new paradigm one has to consider how to combine the efficiency of resource
usage at all three layers of architecture: end devices, edge devices, and the
cloud. While cloud capacity is elastically extendable, end devices and edge
devices are to various degrees resource-constrained. Hence, an efficient
resource management is essential to make edge computing a reality. In this
work, we first present terminology and architectures to characterize current
works within the field of edge computing. Then, we review a wide range of
recent articles and categorize relevant aspects in terms of 4 perspectives:
resource type, resource management objective, resource location, and resource
use. This taxonomy and the ensuing analysis is used to identify some gaps in
the existing research. Among several research gaps, we found that research is
less prevalent on data, storage, and energy as a resource, and less extensive
towards the estimation, discovery and sharing objectives. As for resource
types, the most well-studied resources are computation and communication
resources. Our analysis shows that resource management at the edge requires a
deeper understanding of how methods applied at different levels and geared
towards different resource types interact. Specifically, the impact of mobility
and collaboration schemes requiring incentives are expected to be different in
edge architectures compared to the classic cloud solutions. Finally, we find
that fewer works are dedicated to the study of non-functional properties or to
quantifying the footprint of resource management techniques, including
edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless
Communications and Mobile Computing journa
Spectrum sharing models in cognitive radio networks
Spectrum scarcity demands thinking new ways to
manage the distribution of radio frequency bands so that its use is more effective. The emerging technology that can enable this paradigm shift is the cognitive radio. Different models for
organizing and managing cognitive radios have emerged, all with specific strategic purposes. In this article we review the allocation spectrum patterns of cognitive radio networks and
analyse which are the common basis of each model.We expose the vulnerabilities and open challenges that still threaten the adoption
and exploitation of cognitive radios for open civil networks.L'escassetat de demandes d'espectre fan pensar en noves formes de gestionar la distribució de les bandes de freqüència de ràdio perquè el seu ús sigui més efectiu. La tecnologia emergent que pot permetre aquest canvi de paradigma és la ràdio cognitiva. Han sorgit diferents models d'organització i gestió de les ràdios cognitives, tots amb determinats fins estratègics. En aquest article es revisen els patrons d'assignació de l'espectre de les xarxes de ràdio cognitiva i s'analitzen quals són la base comuna de cada model. S'exposen les vulnerabilitats i els desafiaments oberts que segueixen amenaçant l'adopció i l'explotació de les ràdios cognitives per obrir les xarxes civils.La escasez de demandas de espectro hacen pensar en nuevas formas de gestionar la distribución de las bandas de frecuencia de radio para que su uso sea más efectivo. La tecnología emergente que puede permitir este cambio de paradigma es la radio cognitiva. Han surgido diferentes modelos de organización y gestión de las radios cognitivas, todos con determinados fines estratégicos. En este artículo se revisan los patrones de asignación del espectro de las redes de radio cognitiva y se analizan cuales son la base común de cada modelo. Se exponen las vulnerabilidades y los desafíos abiertos que siguen amenazando la adopción y la explotación de las radios cognitivas para abrir las redes civiles
InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services
Cloud computing providers have setup several data centers at different
geographical locations over the Internet in order to optimally serve needs of
their customers around the world. However, existing systems do not support
mechanisms and policies for dynamically coordinating load distribution among
different Cloud-based data centers in order to determine optimal location for
hosting application services to achieve reasonable QoS levels. Further, the
Cloud computing providers are unable to predict geographic distribution of
users consuming their services, hence the load coordination must happen
automatically, and distribution of services must change in response to changes
in the load. To counter this problem, we advocate creation of federated Cloud
computing environment (InterCloud) that facilitates just-in-time,
opportunistic, and scalable provisioning of application services, consistently
achieving QoS targets under variable workload, resource and network conditions.
The overall goal is to create a computing environment that supports dynamic
expansion or contraction of capabilities (VMs, services, storage, and database)
for handling sudden variations in service demands.
This paper presents vision, challenges, and architectural elements of
InterCloud for utility-oriented federation of Cloud computing environments. The
proposed InterCloud environment supports scaling of applications across
multiple vendor clouds. We have validated our approach by conducting a set of
rigorous performance evaluation study using the CloudSim toolkit. The results
demonstrate that federated Cloud computing model has immense potential as it
offers significant performance gains as regards to response time and cost
saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape
A Case for Cooperative and Incentive-Based Coupling of Distributed Clusters
Research interest in Grid computing has grown significantly over the past
five years. Management of distributed resources is one of the key issues in
Grid computing. Central to management of resources is the effectiveness of
resource allocation as it determines the overall utility of the system. The
current approaches to superscheduling in a grid environment are non-coordinated
since application level schedulers or brokers make scheduling decisions
independently of the others in the system. Clearly, this can exacerbate the
load sharing and utilization problems of distributed resources due to
suboptimal schedules that are likely to occur. To overcome these limitations,
we propose a mechanism for coordinated sharing of distributed clusters based on
computational economy. The resulting environment, called
\emph{Grid-Federation}, allows the transparent use of resources from the
federation when local resources are insufficient to meet its users'
requirements. The use of computational economy methodology in coordinating
resource allocation not only facilitates the QoS based scheduling, but also
enhances utility delivered by resources.Comment: 22 pages, extended version of the conference paper published at IEEE
Cluster'05, Boston, M
Scalable RAN Virtualization in Multi-Tenant LTE-A Heterogeneous Networks (Extended version)
Cellular communications are evolving to facilitate the current and expected
increasing needs of Quality of Service (QoS), high data rates and diversity of
offered services. Towards this direction, Radio Access Network (RAN)
virtualization aims at providing solutions of mapping virtual network elements
onto radio resources of the existing physical network. This paper proposes the
Resources nEgotiation for NEtwork Virtualization (RENEV) algorithm, suitable
for application in Heterogeneous Networks (HetNets) in Long Term
Evolution-Advanced (LTE-A) environments, consisting of a macro evolved NodeB
(eNB) overlaid with small cells. By exploiting Radio Resource Management (RRM)
principles, RENEV achieves slicing and on demand delivery of resources.
Leveraging the multi-tenancy approach, radio resources are transferred in terms
of physical radio Resource Blocks (RBs) among multiple heterogeneous base
stations, interconnected via the X2 interface. The main target is to deal with
traffic variations in geographical dimension. All signaling design
considerations under the current Third Generation Partnership Project (3GPP)
LTE-A architecture are also investigated. Analytical studies and simulation
experiments are conducted to evaluate RENEV in terms of network's throughput as
well as its additional signaling overhead. Moreover we show that RENEV can be
applied independently on top of already proposed schemes for RAN virtualization
to improve their performance. The results indicate that significant merits are
achieved both from network's and users' perspective as well as that it is a
scalable solution for different number of small cells.Comment: 40 pages (including Appendices), Accepted for publication in the IEEE
Transactions on Vehicular Technolog
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