Time dependent pricing in wireless data networks: Flat-rate vs. usage-based schemes

With the advances of bandwidth-intensive mobile devices, we see severe congestion problems in wireless data networks. Recently, research emerges to solve this problem from a pricing point of view. Time dependent pricing has been introduced, and initial investigations have shown its advantages over the conventional time independent pricing. Nevertheless, much is unknown in how a practical and effective time dependent pricing scheme can be designed. In this paper, we explore the design space of time dependent pricing. In particular, we focus on a number of schemes, e.g., the usage-based scheme, the flat-rate scheme, and a mixture of them which we called a cap scheme. Our findings include: 1) the ISP obtains a higher profit with usage-based (or flat-rate) scheme if the capacity is insufficient (or sufficient); 2) the usage-based scheme usually achieves a higher consumer surplus and more efficient traffic utilization than the flat-rate scheme; and 3) the cap scheme is strongly preferred by the ISP to further increase its revenue. We believe our findings provide important insights for ISPs to design effective pricing schemes.Department of ComputingRefereed conference pape

Doctor of Philosophy

dissertationThe next generation mobile network (i.e., 5G network) is expected to host emerging use cases that have a wide range of requirements; from Internet of Things (IoT) devices that prefer low-overhead and scalable network to remote machine operation or remote healthcare services that require reliable end-to-end communications. Improving scalability and reliability is among the most important challenges of designing the next generation mobile architecture. The current (4G) mobile core network heavily relies on hardware-based proprietary components. The core networks are expensive and therefore are available in limited locations in the country. This leads to a high end-to-end latency due to the long latency between base stations and the mobile core, and limitations in having innovations and an evolvable network. Moreover, at the protocol level the current mobile network architecture was designed for a limited number of smart-phones streaming a large amount of high quality traffic but not a massive number of low-capability devices sending small and sporadic traffic. This results in high-overhead control and data planes in the mobile core network that are not suitable for a massive number of future Internet-of-Things (IoT) devices. In terms of reliability, network operators already deployed multiple monitoring sys- tems to detect service disruptions and fix problems when they occur. However, detecting all service disruptions is challenging. First, there is a complex relationship between the network status and user-perceived service experience. Second, service disruptions could happen because of reasons that are beyond the network itself. With technology advancements in Software-defined Network (SDN) and Network Func- tion Virtualization (NFV), the next generation mobile network is expected to be NFV-based and deployed on NFV platforms. However, in contrast to telecom-grade hardware with built-in redundancy, commodity off-the-shell (COTS) hardware in NFV platforms often can't be comparable in term of reliability. Availability of Telecom-grade mobile core network hardwares is typically 99.999% (i.e., "five-9s" availability) while most NFV platforms only guarantee "three-9s" availability - orders of magnitude less reliable. Therefore, an NFV-based mobile core network needs extra mechanisms to guarantee its availability. This Ph.D. dissertation focuses on using SDN/NFV, data analytics and distributed system techniques to enhance scalability and reliability of the next generation mobile core network. The dissertation makes the following contributions. First, it presents SMORE, a practical offloading architecture that reduces end-to-end latency and enables new functionalities in mobile networks. It then presents SIMECA, a light-weight and scalable mobile core network designed for a massive number of future IoT devices. Second, it presents ABSENCE, a passive service monitoring system using customer usage and data analytics to detect silent failures in an operational mobile network. Lastly, it presents ECHO, a distributed mobile core network architecture to improve availability of NFV-based mobile core network in public clouds

Three Essays on Broadband Adoption

This dissertation focuses on three issues surrounding broadband internet adoption. The first study examines the recent shift to mobile-only internet connections. The percentage of mobile-only households increased from 9% in 2011 to 20% in 2015, more than doubling in only four years. As this shift continues, it leads to the question of what factors are driving the rise in mobile-only adoption. Using nationally representative data, this study uses logistic regressions and a decomposition technique to understand the trend. The decomposition reveals that a significant portion of the growth was due to an increase in the download speeds of mobile networks. An increased acceptance of mobile-only access by households aged 55 and older was also partly responsible. Understanding (and developing a response to) the trend towards mobile-only adoption will be important as organizations and governments continue to work to close the digital divide.The second study examines the effectiveness of a well-known grassroots broadband adoption oriented program, Connected Nation. While a large number of studies have examined policies and programs aimed at increasing infrastructure, little analysis to date has focused on evaluating efforts to increase adoption. This analysis focuses on the effectiveness of Connected Nation's efforts by evaluating its impact on adoption rates using a generalized difference-in-difference methodology. While the results indicate there was no significant initial impact, there is evidence of a linear effect resulting in increased adoption 2 to 4 years after the program began. This paper represents a rigorous evaluation of one of the most well-known adoption-oriented programs, and emphasizes that effective use of broadband funds should include empirical analysis of what woks.The third study examines the need for a measure of inequality for broadband adoption. Broadband adoption is primarily measured as the percentage of a population with a connection, regardless of the modality used (i.e. fixed, mobile, or both). This results in a binary measurement that distinguishes between two groups: the percentage that have the defined level of access and those that do not. However, this measure fails to capture differences that may exists in ow users connect – for example, those who use both mobile and fixed versus those use mobile only. This article proposes the use of the absolute value index (AVI) as a measure to study broadband adoption inequality. Using nationally representative data, adoption is broken into four types of connections (none, mobile, fixed, both) to compile the AVI. This measure of inequality may better represent the disparities associated with broadband use across the country, particularly as mobile internet use rises. The results indicate that the AVI can be useful in differentiating adoption patterns (i.e. mobile vs. fixed) in states with similar aggregate levels of adoption. Two nonnested hypothesis tests formally explore the explanatory power of the two measures in explaining economic relationships commonly associated with broadband adoption, and conclude that the AVI does not capture any additional information.Agricultural Economic

Cellular data network infrastructure characterization and implication on mobile content placement

Despite the tremendous growth in the cellular data network usage due to the popularity of smartphones, so far there is rather limited understanding of the network infrastructure of various cellular carriers. Understanding the infrastructure characteristics such as the network topology, routing design, address allocation, and DNS service configuration is essential for predicting, diagnosing, and improving cellular network services, as well as for delivering content to the growing population of mobile wireless users. In this work, we propose a novel approach for discovering cellular infrastructure by intelligently combining several data sources, i.e., server logs from a popular location search application, active measurements results collected from smartphone users, DNS request logs from a DNS authoritative server, and publicly available routing updates. We perform the first comprehensive analysis to characteriz

Optimizing Mobile Application Performance through Network Infrastructure Aware Adaptation.

Encouraged by the fast adoption of mobile devices and the widespread deployment of mobile networks, mobile applications are becoming the preferred “gateways” connecting users to networking services. Although the CPU capability of mobile devices is approaching that of off-the-shelf PCs, the performance of mobile networking applications is still far behind. One of the fundamental reasons is that most mobile applications are unaware of the mobile network specific characteristics, leading to inefficient network and device resource utilization. Thus, in order to improve the user experience for most mobile applications, it is essential to dive into the critical network components along network connections including mobile networks, smartphone platforms, mobile applications, and content partners. We aim to optimize the performance of mobile network applications through network-aware resource adaptation approaches. Our techniques consist of the following four aspects: (i) revealing the fundamental infrastructure characteristics of cellular networks that are distinctive from wireline networks; (ii) isolating the impact of important factors on user perceived performance in mobile network applications; (iii) determining the particular usage patterns of mobile applications; and (iv) improving the performance of mobile applications through network aware adaptations.PhDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99829/1/qiangxu_1.pd

Rethinking Wireless: Building Next-Generation Networks

We face a growing challenge to the design, deployment and management of wireless networks that largely stems from the need to operate in an increasingly spectrum-sparse environment, the need for greater concurrency among devices and the need for greater coordination between heterogeneous wireless protocols. Unfortunately, our current wireless networks lack interoperability, are deployed with fixed functions, and omit easy programmability and extensibility from their key design requirements. In this dissertation, we study the design of next-generation wireless networks and analyze the individual components required to build such an infrastructure. Re-designing a wireless architecture must be undertaken carefully to balance new and coordinated multipoint (CoMP) techniques with the backward compatibility necessary to support the large number of existing devices. These next-generation wireless networks will be predominantly software-defined and will have three components: (a) a wireless component that consists of software-defined radio resource units (RRUs) or access points (APs); (b) a software-defined backhaul control plane that manages the transfer of RF data between the RRUs and the centralized processing resource; and (c) a centralized datacenter/cloud compute resource that processes RF signal data from all attached RRUs. The dissertation addresses the following four key problems in next-generation networks: (1) Making Existing Wireless Devices Spectrum-Agile, (2) Cooperative Compression of the Wireless Backhaul, (3) Spectrum Coordination and (4) Spectrum Coordination.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102341/1/zontar_1.pd