2,718 research outputs found
Cellular-Broadcast Service Convergence through Caching for CoMP Cloud RANs
Cellular and Broadcast services have been traditionally treated independently
due to the different market requirements, thus resulting in different business
models and orthogonal frequency allocations. However, with the advent of cheap
memory and smart caching, this traditional paradigm can converge into a single
system which can provide both services in an efficient manner. This paper
focuses on multimedia delivery through an integrated network, including both a
cellular (also known as unicast or broadband) and a broadcast last mile
operating over shared spectrum. The subscribers of the network are equipped
with a cache which can effectively create zero perceived latency for multimedia
delivery, assuming that the content has been proactively and intelligently
cached. The main objective of this work is to establish analytically the
optimal content popularity threshold, based on a intuitive cost function. In
other words, the aim is to derive which content should be broadcasted and which
content should be unicasted. To facilitate this, Cooperative Multi- Point
(CoMP) joint processing algorithms are employed for the uni and broad-cast PHY
transmissions. To practically implement this, the integrated network controller
is assumed to have access to traffic statistics in terms of content popularity.
Simulation results are provided to assess the gain in terms of total spectral
efficiency. A conventional system, where the two networks operate
independently, is used as benchmark.Comment: Submitted to IEEE PIMRC 201
Elastic Highly Available Cloud Computing
High availability and elasticity are two the cloud computing services technical features. Elasticity is a key feature of cloud computing where provisioning of resources is closely tied to the runtime demand. High availability assure that cloud applications are resilient to failures. Existing cloud solutions focus on providing both features at the level of the virtual resource through virtual machines by managing their restart, addition, and removal as needed. These existing solutions map applications to a specific design, which is not suitable for many applications especially virtualized telecommunication applications that are required to meet carrier grade standards. Carrier grade applications typically rely on the underlying platform to manage their availability by monitoring heartbeats, executing recoveries, and attempting repairs to bring the system back to normal. Migrating such applications to the cloud can be particularly challenging, especially if the elasticity policies target the application only, without considering the underlying platform contributing to its high availability (HA). In this thesis, a Network Function Virtualization (NFV) framework is introduced; the challenges and requirements of its use in mobile networks are discussed. In particular, an architecture for NFV framework entities in the virtual environment is proposed. In order to reduce signaling traffic congestion and achieve better performance, a criterion to bundle multiple functions of virtualized evolved packet-core in a single physical device or a group of adjacent devices is proposed. The analysis shows that the proposed grouping can reduce the network control traffic by 70 percent. Moreover, a comprehensive framework for the elasticity of highly available applications that considers the elastic deployment of the platform and the HA placement of the applicationâs components is proposed. The approach is applied to an internet protocol multimedia subsystem (IMS) application and demonstrate how, within a matter of seconds, the IMS application can be scaled up while maintaining its HA status
Design and Evaluation of a Session-Aware Admission Control Framework for Improving Service Providers' Profitability
International audienceService-aware network management is a key issue for the current and next generation service-oriented networks. In this work, we focus on improving the QoS user experience (QoE) of Internet subscribers connecting to heavily loaded servers. Firstly, we advocate an innovative architecture for fine-grained admission-control of Internet servers subjected to multiple flow-based sessions. The proposed architecture is based on original concepts which meet the constraints of multiple-flow based sessions by explicitly identifying the flows pertaining to a single subscriber's session. Secondly, based on an economically-justified service model, we investigate novel session-aware admission-control for improving providers' profitability. Our fundamental observation is that it is sometimes desirable to reject some customers' new sessions so that others may be completed and thereby generate some revenue for the service provider. We evaluate the performance of the advocated model by conducting advanced simulations where we consider realistic CBR voice traffic. Results demonstrate that responsive session-aware admission-control improves service provider's benefits. For a satisfactory operator's revenue, session-aware admission-control improves the success rate by more than 69 %, compared to standard request-aware admission-control
Optimal Resource Allocation with Delay Guarantees for Network Slicing in Disaggregated RAN
In this article, we propose a novel formulation for the resource allocation
problem of a sliced and disaggregated Radio Access Network (RAN) and its
transport network. Our proposal assures an end-to-end delay bound for the
Ultra-Reliable and Low-Latency Communication (URLLC) use case while jointly
considering the number of admitted users, the transmission rate allocation per
slice, the functional split of RAN nodes and the routing paths in the transport
network. We use deterministic network calculus theory to calculate delay along
the transport network connecting disaggregated RANs deploying network functions
at the Radio Unit (RU), Distributed Unit (DU), and Central Unit (CU) nodes. The
maximum end-to-end delay is a constraint in the optimization-based formulation
that aims to maximize Mobile Network Operator (MNO) profit, considering a cash
flow analysis to model revenue and operational costs using data from one of the
world's leading MNOs. The optimization model leverages a Flexible Functional
Split (FFS) approach to provide a new degree of freedom to the resource
allocation strategy. Simulation results reveal that, due to its non-linear
nature, there is no trivial solution to the proposed optimization problem
formulation. Our proposal guarantees a maximum delay for URLLC services while
satisfying minimal bandwidth requirements for enhanced Mobile BroadBand (eMBB)
services and maximizing the MNO's profit.Comment: 21 pages, 10 figures. For the associated GitHub repository, see
https://github.com/LABORA-INF-UFG/paper-FGKCJ-202
QoE-centric service delivery: A collaborative approach among OTTs and ISPs
The provisioning of the quality to end users is a major objective for the successful deployment of multimedia services over the Internet. It is more and more evident from past research and service deployments that such an objective often requires a collaboration among the different parties that are involved in the delivery of the service. This paper specifically focuses on the cooperation between the Over-The-Top (OTTs) and the Internet Service Providers (ISPs) and proposes a novel service delivery approach that is purely driven by the Quality of Experience (QoE) provided to the final common users. Initially, we identify the need of the collaboration among the OTTs and the ISPs where we not only highlight some of the enterprise level motivations (revenue generation) but also the technical aspects which require collaboration. Later, we provide a reference architecture with the required modules and vertical interfaces for the interaction among the OTTs and the ISPs. Then, we provide a collaboration model where we focus on the modeling of the revenue, whose maximization drives the collaboration. The revenue is considered to be dependent on the user churn, which in turn is affected by the QoE and is modeled using the Sigmoid function. We illustrate simulation results based on our proposed collaboration approach which highlight how the proposed strategy increases the revenue generation and QoE for the OTTs and the ISPs hence providing a ground for ISP to join the loop of revenue generation between OTTs and users
Congestion control in multi-serviced heterogeneous wireless networks using dynamic pricing
Includes bibliographical references.Service providers, (or operators) employ pricing schemes to help provide desired QoS to subscribers and to maintain profitability among competitors. An economically efficient pricing scheme, which will seamlessly integrate usersâ preferences as well as service providersâ preferences, is therefore needed. Else, pricing schemes can be viewed as promoting social unfairness in the dynamically priced network. However, earlier investigations have shown that the existing dynamic pricing schemes do not consider the usersâ willingness to pay (WTP) before the price of services is determined. WTP is the amount a user is willing to pay based on the worth attached to the service requested. There are different WTP levels for different subscribers due to the differences in the value attached to the services requested and demographics. This research has addressed congestion control in the heterogeneous wireless network (HWN) by developing a dynamic pricing scheme that efficiently incentivises users to utilize radio resources. The proposed Collaborative Dynamic Pricing Scheme (CDPS), which identifies the users and operatorsâ preference in determining the price of services, uses an intelligent approach for controlling congestion and enhancing both the usersâ and operatorsâ utility. Thus, the CDPS addresses the congestion problem by firstly obtaining the users WTP from usersâ historical response to price changes and incorporating the WTP factor to evaluate the service price. Secondly, it uses a reinforcement learning technique to illustrate how a price policy can be obtained for the enhancement of both users and operatorsâ utility, as total utility reward obtained increases towards a defined âgoal stateâ
Spectrum Leasing as an Incentive towards Uplink Macrocell and Femtocell Cooperation
The concept of femtocell access points underlaying existing communication
infrastructure has recently emerged as a key technology that can significantly
improve the coverage and performance of next-generation wireless networks. In
this paper, we propose a framework for macrocell-femtocell cooperation under a
closed access policy, in which a femtocell user may act as a relay for
macrocell users. In return, each cooperative macrocell user grants the
femtocell user a fraction of its superframe. We formulate a coalitional game
with macrocell and femtocell users being the players, which can take individual
and distributed decisions on whether to cooperate or not, while maximizing a
utility function that captures the cooperative gains, in terms of throughput
and delay.We show that the network can selforganize into a partition composed
of disjoint coalitions which constitutes the recursive core of the game
representing a key solution concept for coalition formation games in partition
form. Simulation results show that the proposed coalition formation algorithm
yields significant gains in terms of average rate per macrocell user, reaching
up to 239%, relative to the non-cooperative case. Moreover, the proposed
approach shows an improvement in terms of femtocell users' rate of up to 21%
when compared to the traditional closed access policy.Comment: 29 pages, 11 figures, accepted at the IEEE JSAC on Femtocell Network
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