This thesis presents a complete alternative service composition model named Service Trading Marketplace Network (STAMP-Net). The primary concept is to improve overall system scalability and introduce a fair business scheme for customers and providers. STAPM-Net focuses on designing an architecture based on both technical and business aspect. In STAMP-NET, users remain the ability to choose their preference service providers from potential-provider lists, and service providers are able to compete for the requested services that they can handle. For these purposes, STAMP-Net introduce a concept of 'Service Trading Marketplace Mechanism' which facilitates a problem of 'conflict of interest'; 'Indirect Service Discovery' which allows service providers to the learn existing of services being offered by other service providers; and 'Service Subcontract System' which allows service providers to subcontract any missing service to other potential service providers. In addition, this thesis also present monitor techniques, which are used to ensure the quality of services.

Google Inc. struggles arduously on the digital battlefield in China’s Internet search engine market. In China, Baidu.com has been described as China’s Google for years and challenged Google’s expansion. This study provides an overview of the Internet service development in China, an illustration of the search engines’ profitability models, and an evaluation of Guge (Google China) and Baidu’s service designs. Overall, the research shows an attempt to understand the possible advantages and disadvantages when a multinational Internet service company enters China. Two notions emerge. First, standardization and adaptation may need to be nicely balanced for the subsidiary company in order to profit in China’s Internet market. Second, Google’s operation in China, Guge, stands strong on the service design end, especially in the area of “ease of use,” “informativeness,” and “fulfillment/reliability.” However, Guge’s major rival, Baidu, shows its advantage on a wider selection of online services. Therefore, in the long run, which company will win at the finishing line is still too early to tell / Google in China -- Google, Baidu and Guge -- Search engine's revenue model in China. / Department of Telecommunications

Thesis (Ph. D.)--University of New South Wales, 2003. / Also available online.

Thesis (M.B.A.)--University of Hong Kong, 1998. / Includes bibliographical references (leaf 99-102).

Thesis (M.A.)--Ball State University, 2009. / Title from PDF t.p. (viewed on Apr. 16, 2010). Includes bibliographical references (p. 54-63).

Thesis (Ph.D.)--Ohio University, March, 2006. / Includes bibliographical references (leaves 200-210)

Internet Service Providers, or ISPs, like any other rational entity make decisions to maximize their profit. While some of their decisions are on how to attract customers, they inevitably need to control how much resources consumers utilize. In this dissertation, we focus on two different aspects of ISP's decisions, including bandwidth allocation and pricing techniques through which ISPs manage allotting their limited capacity to users with high demand, and zero-rating, which can be one of the tools through which the ISP can attract customers. For bandwidth allocation, this dissertation discusses the data plans available for each user's monthly billing cycle. Within those, the ISPs guarantee a fixed amount of data at high rates until a byte threshold is reached, at which point the user's data rate is throttled to a lower rate for the remainder of the cycle. In practice, the thresholds and rates of throttling can appear and may be somewhat arbitrary. In this dissertation, we evaluate the choice of threshold and rate as an optimization problem (regret minimization) and demonstrate that intuitive formulations of client regret, which preserve desirable fairness properties, lead to optimization problems that have tractably computable solutions. For zero-rating options in the ISP market, and their relation to net neutrality, we begin by introducing the concept of zero-rating, which refers to the practice of providing free Internet access to some users under certain conditions, and usually concurs with differentiation among users or content providers. Even though zero-rating is banned in some countries (India, Canada), others have either taken no stance or explicitly allowed it (South Africa, Kenya, U.S.). While there is broad agreement that preserving the content quality of service falls under the purview of net neutrality, the role of differential pricing, especially the practice of \emph{zero-rating} remains controversial. An objective of net neutrality is to design regulations for the Internet and ensure that it remains a public, open platform where innovations can thrive. We show the practice of zero-rating does not agree with that. This dissertation shows how ISPs could make zero-rating decisions to attract customers, and then show how these decisions may negatively impact the market and customer welfare, which necessitates the existence of some zero-rating regulations.

Our daily lives are increasingly reliant on Internet-based services, which in turn are increasingly dependent upon a small number of cloud providers to support their functionality. Internet service consolidation aggrandizes the select few cloud providers who are consolidation’s beneficiaries. As cloud providers’ networks – primarily those of Amazon, Google, IBM, and Microsoft – become more vital to the Internet’s operation and functionality, it is paramount that we understand the different factors that affect their performance and how they are affecting the greater Internet. It is also imperative that researchers are able to conduct independent measurements and tests regarding these topics without requiring collaboration with, or special access from, the cloud providers. Due to proprietary implementations, the results of collaborative studies or experiments lack transparency and are difficult, if not impossible, for independent researchers to repeat. In this dissertation we seek to understand how the cloud providers’ networks impact Internet user performance versus using the public Internet and how they are affecting the Internet’s topological structure. To achieve this, first we enable future research to test how various net- work component interactions affect performance by creating a testbed that approximates the cloud providers’ network environment. The testbed provides researchers with the same control and fidelity as the operators of a complex network, such as the cloud providers. No prior work provided such a platform for Internet networking research. Second, we examine how the cloud providers’ private Wide Area Networks (WANs) impact user performance. We do this by leveraging new services provided by Google and Amazon which enables us to isolate the latency differences between using their private WANs versus us- ing the public Internet. We conduct the first comprehensive study that quantifies the performance difference, sourced from networks we estimate to represent 91% of the Internet’s user population. We then examine several case studies in specific regions where one of the two networks provides significant performance benefits and examine why these outliers occur. This body of work shows that using only measurements and analyses that do not require special access or permissions from the cloud providers, we can discern that the cloud providers’ private WANs deliver modest performance improvements over the public Internet. Third, we examine the impact the cloud providers’ networks have on the Internet and its topology. We start by investigating and quantifying to what extent increased connectivity between the cloud providers and other networks allows the cloud providers to bypass the hierarchical Inter- net. We then analyze the geographic deployment strategy of the cloud providers, compare it against the Tier-1 and Tier-2 Internet Service Providers (ISPs), and examine the population coverage of each based on geographic proximity to network resources. We show that the cloud providers’ extensive peering footprints provide the potential for them to reach the majority of networks while bypassing the hierarchical Internet.

The Internet does not currently provide end-to-end Quality of Service (QoS) guarantees across multiple network providers. We demonstrate that networks. by using dynamic pricing, can provide end-to-end QoS guarantees for those applications that need it. We propose the concept of QoS-Transit Services: a set of primitive services offered by an Internet Service Provider (ISP) in order to deliver packets with statistical performance guarantees within its network, using dynamic pricing. ISPs can choose their own pricing schemes, as long as QoS is guaranteed. Through simulation, we demonstrate that even simple pricing mechanisms can guarantee the advertised performance of a QoS-Transit Service. End-to-end QoS across multiple networks is achieved by using multiple QoS¬Transit Services, from different ISPs, in sequence. Since QoS-Transit Services are offered by ISPs to generate revenues. we determine how to allocate bandwidth among the services in order to maximize revenue. assuming that demand functions can be estimated. We propose the IterLP and IterGreedy heuristics to determine the optimal allocation of bandwidth on predefined paths. IterLP achieves revenue close to 99% of the optimal solution. achieving this result quickly. IterGreedy achieves 90-95% optimality, but executes faster than IterLP. Additionally, to determine the paths on which to route the QoS-Transit Services so as to maximize the ISP's revenue, we propose three heuristics with different specific advantages: Service Grouping. Iterative Bottleneck Avoidance, and Iterative Bottleneck Avoidance with Tabu. We demonstrate that Iterative Bottleneck Avoidance with Tabu achieves approximately 98% of an optimal solution. Route selection is also shown to be more important when fewer QoS-Transit Services are offered. When demand functions cannot be adequately estimated. an ISP can use our Iterative Allocation Adjustment heuristic to find the optimal allocation of bandwidth for a set QoS-Transit Services. The heuristic achieves over 95% of the optimal revenue for an ISP. We then examine how better routes can be identified by valuing the links in the network to identify rerouting possibilities, or to identify paths for new QoS-Transit Services. To receive a specified end-to-end QoS, customers may use concatenated QoS-Transit Services. We propose the Hub Charging Model to provide scalable charging, using Brokers as middle-men. Additionally, we propose the concept of Overlay ISPs: ISPs that provide QoS-Transit Services by controlling an overlay network. An Overlay ISP, a type of virtual network operator, can offer QoS over a large geographic area without universal ISP support for QoS-Transit Services. Finally, we detail an architecture for offering QoS-Transit Services using existing protocol standards. By using a Broker-ISP as an intermediary between customers and the 1SPs offering QoS-Transit Services, routing and charging complexities can be hidden from the customers. Additionally we describe how security, billing, metering. and policing can be achieved. The competitive environment assumed within this dissertation is now emerging, with ISPs charging content providers in order to deliver content at a superior quality level to the ISP's customers. The time is therefore ripe for dynamic pricing to be deployed.

Thesis (LL. M.)--University of Toronto, 2005. / Includes bibliographical references.