Improving Content Delivery Efficiency through Multi-Layer Mobile Edge Adaptation

This paper presents a novel architecture for optimizing the HTTP-based multimedia delivery in multi-user mobile networks. This proposal combines the usual client-driven dynamic adaptation scheme DASH-3GPP with network-assisted adaptation capabilities, in order to maximize the overall Quality of Experience. The foundation of this combined adaptation scheme is based on two state of the art technologies. On one hand, adaptive HTTP streaming with multi-layer encoding allows efficient media delivery and improves the experienced media quality in highly dynamic channels. Additionally, it enables the possibility to implement network-level adaptations for better coping with multi-user scenarios. On the other hand, mobile edge computing facilitates the deployment of mobile services close to the user. This approach brings new possibilities in modern and future mobile networks, such as close to zero delays and awareness of the radio status. The proposal in this paper introduces a novel element, denoted as Mobile Edge-DASH Adaptation Function, which combines all these advantages to support efficient media delivery in mobile multi-user scenarios. Furthermore, we evaluate the performance enhancements of this content- and user context-aware scheme through simulations of a mobile multimedia scenario.European Union H2020 programme: Grant Agreement H2020-ICT-671596. Spanish Ministerio de Economia y Competitividad (MINECO): grant TEC2013-46766-R

A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.The research leading to these results has been supported by the EU funded H2020 5G-PPP Project SESAME (Grant Agreement 671596) and the Spanish MINECO Project 5GRANVIR (TEC2016-80090-C2-2-R)

QoE-Oriented Mobile Edge Service Management Leveraging SDN and NFV

5G envisages a "hyperconnected society" where trillions of diverse entities could communicate with each other anywhere and at any time, some of which will demand extremely challenging performance requirements such as submillisecond low latency. Mobile Edge Computing (MEC) concept where application computing resources are deployed at the edge of the mobile network in proximity of an end user is a promising solution to improve quality of online experience. To make MEC more flexible and cost-effective Network Functions Virtualisation (NFV) and Software-Defined Networking (SDN) technologies are widely adopted. It leads to significant CAPEX and OPEX reduction with the help of a joint radio-cloud management and orchestration logic. In this paper we discuss and develop a reference architecture for the orchestration and management of the MEC ecosystem. Along with the lifecycle management flows of MEC services, indicating the interactions among the functional modules inside the Orchestrator and with external elements, QoS management with a focus on the channel state information technique is presented.The research leading to these results has been supported by the EU funded H2020 5G-PPP project SESAME under the Grant Agreement no. 671596 and National Spanish Projects QoEverage (no. TEC2013-46766-R) and ONOFRE (no. TEC2014-53071-C3-1-P)

Analysis of channel quality reporting mechanisms and their impact into 4G and beyond technologies

206 p.Modern broadband mobile networks such as 4G LTE are designed to cope with stringent performance levels, i.e. considerable peak data rates and low latencies. With the wide-spreading of LTE networks all over the world, the access to Internet services through mobile connections is increasing considerably, leading to a plethora of mobile services. However, the inherent characteristics of the radio interface results in variable service performance. First, radio resources are shared among the different mobile users and thus the eNB scheduling functions determine the assigned share of resources for each user in a dynamic way. Moreover, the channel quality of each individual user fluctuates over time due to propagation and fading effects. These aspects introduce new issues in the tasks of performance evaluation and adaptive traffic management at different layers of the protocol stack. Currently, there is a gap between advanced research proposals and the actual network and service performance experienced in commercial mobile networks. Although it is generally assumed that the radio channel may introduce considerable quality fluctuations, there is little evidence of the quality dynamics experienced in live LTE networks at different temporal scales. This PhD work aims at providing some insights of these quality variations by analyzing the Channel State Information generated by UEs. Specifically, the document focuses on the downlink direction and on the effects of using spatial multiplexing techniques. From field testing, the main characteristics of the channel quality are studied at the scale of one second. Besides, LTE emulation tests allow evaluating the characteristics of the reported channel quality at the scale of milliseconds. Therefore, valuable information is captured for different layers of the protocol stack. Finally, the impact of the dynamics of these Channel State Information values into different adaptive traffic management schemes is evaluated. For a comprehensive analysis, different mobile network architectures are considered including classical LTE systems and novel proposals such as centralized radio access networks and mobile edge computing.Spanish Ministerio de Economia y Competitividad (MINECO): grant TEC2013-46766-R. European Union H2020 programme: Grant Agreement H2020-ICT-671596

Dealing with Energy-QoE Trade-Offs in Mobile Video

Scalable video coding allows an efficient provision of video services at different quality levels with different energy demands. According to the specific type of service and network scenario, end users and/or operators may decide to choose among different energy versus quality combinations. In order to deal with the resulting trade-off, in this paper we analyze the number of video layers that are worth to be received taking into account the energy constraints. A single-objective optimization is proposed based on dynamically selecting the number of layers, which is able to minimize the energy consumption with the constraint of a minimal quality threshold to be reached. However, this approach cannot reflect the fact that the same increment of energy consumption may result in different increments of visual quality. Thus, a multiobjective optimization is proposed and a utility function is defined in order to weight the energy consumption and the visual quality criteria. Finally, since the optimization solving mechanism is computationally expensive to be implemented in mobile devices, a heuristic algorithm is proposed. This way, significant energy consumption reduction will be achieved while keeping reasonable quality levels.European Union Seventh Framework Programme (FP7/2007–2013) under Grant agreement 284863 (FP7 SEC GERYON) and from the Basque Country under BASAJAUN Project

Improving Content Delivery Efficiency through Multi-Layer Mobile Edge Adaptation

This paper presents a novel architecture for optimizing the HTTP-based multimedia delivery in multi-user mobile networks. This proposal combines the usual client-driven dynamic adaptation scheme DASH-3GPP with network-assisted adaptation capabilities, in order to maximize the overall Quality of Experience. The foundation of this combined adaptation scheme is based on two state of the art technologies. On one hand, adaptive HTTP streaming with multi-layer encoding allows efficient media delivery and improves the experienced media quality in highly dynamic channels. Additionally, it enables the possibility to implement network-level adaptations for better coping with multi-user scenarios. On the other hand, mobile edge computing facilitates the deployment of mobile services close to the user. This approach brings new possibilities in modern and future mobile networks, such as close to zero delays and awareness of the radio status. The proposal in this paper introduces a novel element, denoted as Mobile Edge-DASH Adaptation Function, which combines all these advantages to support efficient media delivery in mobile multi-user scenarios. Furthermore, we evaluate the performance enhancements of this content- and user context-aware scheme through simulations of a mobile multimedia scenario.European Union H2020 programme: Grant Agreement H2020-ICT-671596. Spanish Ministerio de Economia y Competitividad (MINECO): grant TEC2013-46766-R