Cross-user subsidy in residential broadband service

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 38-40).The rapid growth of Internet traffic has made Internet Service Providers (ISP) struggle to upgrade network capacity and to maintain service quality. The increase in the broadband usage impacts the cost of an ISP through usage-associated costs such as incremental usage cost, cost for expanding the network capacity, and cost from subscriber churns. This paper attempts to understand the relation between broadband usage and incremental usage cost. This thesis addresses issues on connecting the broadband usage to the usage-sensitive costs. How much do the light users spend to support the heavy users by paying the equal usage fee? To answer the question, it should be investigated how much incremental cost is generated by using networks and how the traffic load is distributed over the users. The research is based on the commercial broadband usage data sample and the published financial statements from a major broadband service provider in Korea, Korea Telecom. Analyzing the broadband usage reveals to us what the usage distribution looks like and how the distribution evolves over time.(cont.) By examining the published financial data, the cost directly associated with the broadband usage is estimated. The usage distribution and the estimated cost is incorporated to find an answer to how much burden the light users are carrying to subsidize the heavy users on the network under the current flat usage fee system.by Jungwon Min.S.M

Pricing Sponsored Data Plans in Two-Sided Markets

This thesis shows that a monopoly Internet Service Provider will never offer zero-rated mobile data plans for homogenous consumers if it cannot ask content providers to pay for the traffic increase caused by to zero-rating. Increasing the data allowance will result in similar utility gains for the customers than zero-rating some content, with lower or identical costs for the Internet Service Provider. When a monopoly Internet Service Provider is allowed to collect payments from content providers, prices to both sides of the market are determined by the size of the data allowance. Opposing effects of distorted consumption towards the zero-rated content and increased total consumption of data mean that total welfare effects remain ambiguous and depend on the parameter values

An Analysis Of Open-Source Smart Phone Market: Preload Apps And Co-Competition

Free open-source operating system (OS) has driven both ad revenue and Internet traffic from smartphones to the historically high levels. Though achieving huge market share, there is no record showing that the profit of a handset maker from the smartphone market can surpass the firm implementing vertical integration ever since the first smartphone has been launched in the market. In this study, we consider that an open-source OS provider free offers its operating system but gain mobile advertising revenue by demanding the hardware maker to install preload apps. After trading off between homogenizing each open-source smartphone but gaining more “eyeball shares” on advertising via handsets due to more preload apps, we examine how the OS provider’s optimal agreement with hardware makers changes with market factors. In addition, we also compare and analyze the profit of the OS provider between launching its own brand of smartphones and receiving advertising revenue only. Our results suggest that the OS provider should enhance the quality of its own product when entering the smartphone market. Moreover, if outsourcing the production work to a hardware maker can achieve the economies of scale and increase its profit, our analytic results suggest that the OS provider shouldn’t partner with the hardware maker dominating the smartphone market

Resource management for virtualized networks

Network Virtualization has emerged as a promising approach that can be employed to efficiently enhance the resource management technologies. In this work, the goal is to study how to automate the bandwidth resource management, while deploying a virtual partitioning scheme for the network bandwidth resources. Works that addressed the resource management in Virtual Networks are many, however, each has some limitations. Resource overwhelming, poor bandwidth utilization, low profits, exaggeration, and collusion are types of such sort of limitations. Indeed, the lack of adequate bandwidth allocation schemes encourages resource overwhelming, where one customer may overwhelm the resources that supposed to serve others. Static resource partitioning can resist overwhelming but at the same time it may result in poor bandwidth utilization, which means less profit rates for the Internet Service Providers (ISPs). However, deploying the technology of autonomic management can enhance the resource utilization, and maximize the customers’ satisfaction rates. It also provides the customers with a kind of privilege that should be somehow controlled as customers, always eager to maximize their payoffs, can use such a privilege to cheat. Hence, cheating actions like exaggeration and collusion can be expected. Solving the aforementioned limitations is addressed in this work. In the first part, the work deals with overcoming the problems of low profits, poor utilization, and high blocking ratios of the traditional First Ask First Allocate (FAFA) algorithm. The proposed solution is based on an Autonomic Resource Management Mechanism (ARMM). This solution deploys a smarter allocation algorithm based on the auction mechanism. At this level, to reduce the tendency of exaggeration, the Vickrey-Clarke-Groves (VCG) is proposed to provide a threat model that penalizes the exaggerating customers, based on the inconvenience they cause to others in the system. To resist the collusion, the state-dependent shadow price is calculated, based on the Markov decision theory, to represent a selling price threshold for the bandwidth units at a given state. Part two of the work solves an expanded version of the bandwidth allocation problem, but through a different methodology. In this part, the bandwidth allocation problem is expanded to a bandwidth partitioning problem. Such expansion allows dividing the link’s bandwidth resources based on the provided Quality of Service (QoS) classes, which provides better bandwidth utilization. In order to find the optimal management metrics, the problem is solved through Linear Programming (LP). A dynamic bandwidth partitioning scheme is also proposed to overcome the problems related to the static partitioning schemes, such as the poor bandwidth utilization, which can result in having under-utilized partitions. This dynamic partitioning model is deployed in a periodic manner. Periodic partitioning provides a new way to reduce the reasoning of exaggeration, when compared to the threat model, and eliminates the need of the further computational overhead. The third part of this work proposes a decentralized management scheme to solve aforementioned problems in the context of networks that are managed by Virtual Network Operators (VNOs). Such decentralization allows deploying a higher level of autonomic management, through which, the management responsibilities are distributed over the network nodes, each responsible for managing its outgoing links. Compared to the centralized schemes, such distribution provides higher reliability and easier bandwidth dimensioning. Moreover, it creates a form of two-sided competition framework that allows a double-auction environment among the network players, both customers and node controllers. Such competing environment provides a new way to reduce the exaggeration beside the periodic and threat models mentioned before. More important, it can deliver better utilization rates, lower blocking, and consequently higher profits. Finally, numerical experiments and empirical results are presented to support the proposed solutions, and to provide a comparison with other works from the literature

Modeling the relationship between network operators and venue owners in public Wi-Fi deployment using non-cooperative game theory

Wireless data demands keep rising at a fast rate. In 2016, Cisco measured a global mobile data traffic volume of 7.2 Exabytes per month and projected a growth to 49 Exabytes per month in 2021. Wi-Fi plays an important role in this as well. Up to 60% of the total mobile traffic was off-loaded via Wi-Fi (and femtocells) in 2016. This is further expected to increase to 63% in 2021. In this publication, we look into the roll-out of public Wi-Fi networks, public meaning in a public or semi-public place (pubs, restaurants, sport stadiums, etc.). More concretely we look into the collaboration between two parties, a technical party and a venue owner, for the roll-out of a new Wi-Fi network. The technical party is interested in reducing load on its mobile network and generating additional direct revenues, while the venue owner wants to improve the attractiveness of the venue and consequentially generate additional indirect revenues. Three Wi-Fi pricing models are considered: entirely free, slow access with ads or fast access via paid access (freemium), and paid access only (premium). The technical party prefers a premium model with high direct revenues, the venue owner a free/freemium model which is attractive to its customers, meaning both parties have conflicting interests. This conflict has been modeled using non-cooperative game theory incorporating detailed cost and revenue models for all three Wi-Fi pricing models. The initial outcome of the game is a premium Wi-Fi network, which is not the optimal solution from an outsider's perspective as a freemium network yields highest total payoffs. By introducing an additional compensation scheme which corresponds with negotiation in real life, the outcome of the game is steered toward a freemium solution