Individual Tariffs for Mobile Communication Services

This paper introduces a conceptual framework and a computational model for individual tariffs for mobile communication services. The purpose is to provide guidance for implementation by communication service suppliers or user groups alike. The paper first examines the sociological and economic incentives for personalized services and individual tariffs. Then it introduces a framework for individual tariffs which is centered on user and supplier behaviours. The user, instead of being fully rational, has "bounded rationality" and his behaviours are subject to economic constraints and influenced by social needs. The supplier can belong to different types of entities such as firms and communities; each has his own goals which lead to different behaviors. Individual tariffs are decided through interactions between the user and the supplier and can be analyzed in a structured way using game theory. A numerical case in mobile music training is developed to illustrate the concepts.risks;mobile communication services;Individual tariffs;computational games

Individual Tariffs for Mobile Communication Services

This paper introduces a conceptual framework and a computational model for individual tariffs for mobile communication services. The purpose is to provide guidance for implementation by communication service suppliers or user groups alike. The paper first examines the sociological and economic incentives for personalized services and individual tariffs. Then it introduces a framework for individual tariffs which is centered on user and supplier behaviours. The user, instead of being fully rational, has "bounded rationality" and his behaviours are subject to economic constraints and influenced by social needs. The supplier can belong to different types of entities such as firms and communities; each has his own goals which lead to different behaviors. Individual tariffs are decided through interactions between the user and the supplier and can be analyzed in a structured way using game theory. A numerical case in mobile music training is developed to illustrate the concepts

Experimentation and Characterization of Mobile Broadband Networks

The Internet has brought substantial changes to our life as the main tool to access a large variety of services and applications. Internet distributed nature and technological improvements lead to new challenges for researchers, service providers, and network administrators. Internet traffic measurement and analysis is one of the most trivial and powerful tools to study such a complex environment from different aspects. Mobile BroadBand (MBB) networks have become one of the main means to access the Internet. MBB networks are evolving at a rapid pace with technology enhancements that promise drastic improvements in capacity, connectivity, and coverage, i.e., better performance in general. Open experimentation with operational MBB networks in the wild is currently a fundamental requirement of the research community in its endeavor to address the need for innovative solutions for mobile communications. There is a strong need for objective data relating to stability and performance of MBB (e.g., 2G, 3G, 4G, and soon-to-come 5G) networks and for tools that rigorously and scientifically assess their performance. Thus, measuring end user performance in such an environment is a challenge that calls for large-scale measurements and profound analysis of the collected data. The intertwining of technologies, protocols, and setups makes it even more complicated to design scientifically sound and robust measurement campaigns. In such a complex scenario, the randomness of the wireless access channel coupled with the often unknown operator configurations makes this scenario even more challenging. In this thesis, we introduce the MONROE measurement platform: an open access and flexible hardware-based platform for measurements on operational MBB networks. The MONROE platform enables accurate, realistic, and meaningful assessment of the performance and reliability of MBB networks. We detail the challenges we overcame while building and testing the MONROE testbed and argue our design and implementation choices accordingly. Measurements are designed to stress performance of MBB networks at different network layers by proposing scalable experiments and methodologies. We study: (i) Network layer performance, characterizing and possibly estimating the download speed offered by commercial MBB networks; (ii) End users’ Quality of Experience (QoE), specifically targeting the web performance of HTTP1.1/TLS and HTTP2 on various popular web sites; (iii) Implication of roaming in Europe, understanding the roaming ecosystem in Europe after the "Roam like Home" initiative; and (iv) A novel adaptive scheduler family with deadline is proposed for multihomed devices that only require a very coarse knowledge of the wireless bandwidth. Our results comprise different contributions in the scope of each research topic. To put it in a nutshell, we pinpoint the impact of different network configurations that further complicate the picture and hopefully contribute to the debate about performance assessment in MBB networks. The MBB users web performance shows that HTTP1.1/TLS is very similar to HTTP2 in our large-scale measurements. Furthermore, we observe that roaming is well supported for the monitored operators and the operators using the same approach for routing roaming traffic. The proposed adaptive schedulers for content upload in multihomed devices are evaluated in both numerical simulations and real mobile nodes. Simulation results show that the adaptive solutions can effectively leverage the fundamental tradeoff between the upload cost and completion time, despite unpredictable variations in available bandwidth of wireless interfaces. Experiments in the real mobile nodes provided by the MONROE platform confirm the findings

An approach for the design of infrastructure mode indoor WLAN based on ray tracing and a binary optimizer

This paper presents an approach that combines a ray tracing tool with a binary version of the particle swarm optimization method (BPSO) for the design of infrastructure mode indoor wireless local area networks (WLAN). The approach uses the power levels of a set of candidate access point (AP) locations obtained with the ray tracing tool at a mesh of potential receiver locations or test points to allow the BPSO optimizer to carry out the design of the WLAN. For this purpose, several restrictions are imposed through a fitness function that drives the search towards the selection of a reduced number of AP locations and their channel assignments, keeping at the same time low transmission power levels. During the design, different coverage priority areas can be defined and the signal to interference ratio (SIR) levels are kept as high as possible in order to comply with the Quality of Service (QoS) requirements imposed. The performance of this approach in a real scenario at the author´s premises is reported, showing its usefulness.This work was supported by the Spanish Ministry of Science and Innovation (TEC2008-02730) and the Spanish Ministry of Economy and Competitiveness (TEC2012-33321)

(So) Big Data and the transformation of the city

The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders in building knowledge discovery pipelines over such data sources. At the same time, this widespread data availability also raises privacy issues that must be considered by both industrial and academic stakeholders. In this paper, we provide a wide perspective on the role that big data have in reshaping cities. The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media. In discussing these aspects, we leverage, as concrete examples and case studies of urban data science tools, the results obtained in the “City of Citizens” thematic area of the Horizon 2020 SoBigData initiative, which includes a virtual research environment with mobility datasets and urban analytics methods developed by several institutions around Europe. We conclude the paper outlining the main research challenges that urban data science has yet to address in order to help make the smart city vision a reality

An Energy-Efficient and Reliable Data Transmission Scheme for Transmitter-based Energy Harvesting Networks

Energy harvesting technology has been studied to overcome a limited power resource problem for a sensor network. This paper proposes a new data transmission period control and reliable data transmission algorithm for energy harvesting based sensor networks. Although previous studies proposed a communication protocol for energy harvesting based sensor networks, it still needs additional discussion. Proposed algorithm control a data transmission period and the number of data transmission dynamically based on environment information. Through this, energy consumption is reduced and transmission reliability is improved. The simulation result shows that the proposed algorithm is more efficient when compared with previous energy harvesting based communication standard, Enocean in terms of transmission success rate and residual energy.This research was supported by Basic Science Research Program through the National Research Foundation by Korea (NRF) funded by the Ministry of Education, Science and Technology(2012R1A1A3012227)

Towards Viable Large Scale Heterogeneous Wireless Networks

We explore radio resource allocation and management issues related to a large-scale heterogeneous (hetnet) wireless system made up of several Radio Access Technologies (RATs) that collectively provide a unified wireless network to a diverse set of users through co-ordination managed by a centralized Global Resource Controller (GRC). We incorporate 3G cellular technologies HSPA and EVDO, 4G cellular technologies WiMAX and LTE, and WLAN technology Wi-Fi as the RATs in our hetnet wireless system. We assume that the user devices are either multi-modal or have one or more reconfigurable radios which makes it possible for each device to use any available RAT at any given time subject to resource-sharing agreements. For such a hetnet system where resource allocation is coordinated at a global level, characterizing the network performance in terms of various conflicting network efficiency objectives that takes costs associated with a network re-association operation into account largely remains an open problem. Also, all the studies to-date that try to characterize the network performance of a hetnet system do not account for RAT-specific implementation details and the management overhead associated with setting up a centralized control. We study the radio resource allocation problem and the implementation/management overhead issues associated with a hetnet system in two research phases. In the first phase, we develop cost models associated with network re-association in terms of increased power consumption and communication downtime taking into account various user device assumptions. Using these cost models in our problem formulations, the first phase focuses on resource allocation strategies where we use a high-level system modeling approach to study the achievable performance in terms of conflicting network efficiency measures of spectral efficiency, overall power consumption, and instantaneous and long-term fairness for each user in the hetnet system. Our main result from this phase of study suggests that the gain in spectral efficiency due to multi-access network diversity results in a tremendous increase in overall power consumption due to frequent re-associations required by user devices. We then develop a utility function-based optimization algorithm to characterize and achieve a desired tradeoff in terms of all four network efficiency measures of spectral efficiency, overall power consumption and instantaneous and long-term fairness. We show an increase in a multi-attribute system utility measure of up to 56.7% for our algorithm compared to other widely studied resource allocation algorithms including max-sum rate, proportional fairness, max-min fairness and min power. The second phase of our research study focuses on practical implementation issues including the overhead required to implement a centralized GRC solution in a hetnet system. Through detailed protocol level simulations performed in ns-2, we show an increase in spectral efficiency of up to 99% and an increase in instantaneous fairness of up to 28.5% for two sort-based user device-to-Access Point (AP)/Base Station (BS) association algorithms implemented at the GRC that aim to maximize system spectral efficiency and instantaneous fairness performance metrics respectively compared to a distributed solution where each user makes his/her own association decision. The efficiency increase for each respective attribute again results in a tremendous increase in power consumption of up to 650% and 794% for each respective algorithm implemented at the GRC compared to a distributed solution because of frequent re-associations