1,823 research outputs found
Network Slicing: Market Mechanism and Competitive Equilibria
Towards addressing spectral scarcity and enhancing resource utilization in 5G
networks, network slicing is a promising technology to establish end-to-end
virtual networks without requiring additional infrastructure investments. By
leveraging Software Defined Networks (SDN) and Network Function Virtualization
(NFV), we can realize slices completely isolated and dedicated to satisfy the
users' diverse Quality of Service (QoS) prerequisites and Service Level
Agreements (SLAs). This paper focuses on the technical and economic challenges
that emerge from the application of the network slicing architecture to
real-world scenarios. We consider a market where multiple Network Providers
(NPs) own the physical infrastructure and offer their resources to multiple
Service Providers (SPs). Then, the SPs offer those resources as slices to their
associated users. We propose a holistic iterative model for the network slicing
market along with a clock auction that converges to a robust
-competitive equilibrium. At the end of each cycle of the market, the
slices are reconfigured and the SPs aim to learn the private parameters of
their users. Numerical results are provided that validate and evaluate the
convergence of the clock auction and the capability of the proposed market
architecture to express the incentives of the different entities of the system
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)
The edge cloud: A holistic view of communication, computation and caching
The evolution of communication networks shows a clear shift of focus from
just improving the communications aspects to enabling new important services,
from Industry 4.0 to automated driving, virtual/augmented reality, Internet of
Things (IoT), and so on. This trend is evident in the roadmap planned for the
deployment of the fifth generation (5G) communication networks. This ambitious
goal requires a paradigm shift towards a vision that looks at communication,
computation and caching (3C) resources as three components of a single holistic
system. The further step is to bring these 3C resources closer to the mobile
user, at the edge of the network, to enable very low latency and high
reliability services. The scope of this chapter is to show that signal
processing techniques can play a key role in this new vision. In particular, we
motivate the joint optimization of 3C resources. Then we show how graph-based
representations can play a key role in building effective learning methods and
devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing:
Principles and Applications", P. Djuric and C. Richard Eds., Academic Press,
Elsevier, 201
Getting the Most Out of Your VNFs: Flexible Assignment of Service Priorities in 5G
Through their computational and forwarding capabilities, 5G networks can
support multiple vertical services. Such services may include several common
virtual (network) functions (VNFs), which could be shared to increase resource
efficiency. In this paper, we focus on the seldom studied VNF-sharing problem,
and decide (i) whether sharing a VNF instance is possible/beneficial or not,
(ii) how to scale virtual machines hosting the VNFs to share, and (iii) the
priorities of the different services sharing the same VNF. These decisions are
made with the aim to minimize the mobile operator's costs while meeting the
verticals' performance requirements. Importantly, we show that the
aforementioned priorities should not be determined a priori on a per-service
basis, rather they should change across VNFs since such additional flexibility
allows for more efficient solutions. We then present an effective methodology
called FlexShare, enabling near-optimal VNF-sharing decisions in polynomial
time. Our performance evaluation, using real-world VNF graphs, confirms the
effectiveness of our approach, which consistently outperforms baseline
solutions using per-service priorities
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