Dynamic bandwidth allocation in ATM networks

Includes bibliographical references.This thesis investigates bandwidth allocation methodologies to transport new emerging bursty traffic types in ATM networks. However, existing ATM traffic management solutions are not readily able to handle the inevitable problem of congestion as result of the bursty traffic from the new emerging services. This research basically addresses bandwidth allocation issues for bursty traffic by proposing and exploring the concept of dynamic bandwidth allocation and comparing it to the traditional static bandwidth allocation schemes

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

ATOM : a distributed system for video retrieval via ATM networks

The convergence of high speed networks, powerful personal computer processors and improved storage technology has led to the development of video-on-demand services to the desktop that provide interactive controls and deliver Client-selected video information on a Client-specified schedule. This dissertation presents the design of a video-on-demand system for Asynchronous Transfer Mode (ATM) networks, incorporating an optimised topology for the nodes in the system and an architecture for Quality of Service (QoS). The system is called ATOM which stands for Asynchronous Transfer Mode Objects. Real-time video playback over a network consumes large bandwidth and requires strict bounds on delay and error in order to satisfy the visual and auditory needs of the user. Streamed video is a fundamentally different type of traffic to conventional IP (Internet Protocol) data since files are viewed in real-time, not downloaded and then viewed. This streaming data must arrive at the Client decoder when needed or it loses its interactive value. Characteristics of multimedia data are investigated including the use of compression to reduce the excessive bit rates and storage requirements of digital video. The suitability of MPEG-1 for video-on-demand is presented. Having considered the bandwidth, delay and error requirements of real-time video, the next step in designing the system is to evaluate current models of video-on-demand. The distributed nature of four such models is considered, focusing on how Clients discover Servers and locate videos. This evaluation eliminates a centralized approach in which Servers have no logical or physical connection to any other Servers in the network and also introduces the concept of a selection strategy to find alternative Servers when Servers are fully loaded. During this investigation, it becomes clear that another entity (called a Broker) could provide a central repository for Server information. Clients have logical access to all videos on every Server simply by connecting to a Broker. The ATOM Model for distributed video-on-demand is then presented by way of a diagram of the topology showing the interconnection of Servers, Brokers and Clients; a description of each node in the system; a list of the connectivity rules; a description of the protocol; a description of the Server selection strategy and the protocol if a Broker fails. A sample network is provided with an example of video selection and design issues are raised and solved including how nodes discover each other, a justification for using a mesh topology for the Broker connections, how Connection Admission Control (CAC) is achieved, how customer billing is achieved and how information security is maintained. A calculation of the number of Servers and Brokers required to service a particular number of Clients is presented. The advantages of ATOM are described. The underlying distributed connectivity is abstracted away from the Client. Redundant Server/Broker connections are eliminated and the total number of connections in the system are minimized by the rule stating that Clients and Servers may only connect to one Broker at a time. This reduces the total number of Switched Virtual Circuits (SVCs) which are a performance hindrance in ATM. ATOM can be easily scaled by adding more Servers which increases the total system capacity in terms of storage and bandwidth. In order to transport video satisfactorily, a guaranteed end-to-end Quality of Service architecture must be in place. The design methodology for such an architecture is investigated starting with a review of current QoS architectures in the literature which highlights important definitions including a flow, a service contract and flow management. A flow is a single media source which traverses resource modules between Server and Client. The concept of a flow is important because it enables the identification of the areas requiring consideration when designing a QoS architecture. It is shown that ATOM adheres to the principles motivating the design of a QoS architecture, namely the Integration, Separation and Transparency principles. The issue of mapping human requirements to network QoS parameters is investigated and the action of a QoS framework is introduced, including several possible causes of QoS degradation. The design of the ATOM Quality of Service Architecture (AQOSA) is then presented. AQOSA consists of 11 modules which interact to provide end-to-end QoS guarantees for each stream. Several important results arise from the design. It is shown that intelligent choice of stored videos in respect of peak bandwidth can improve overall system capacity. The concept of disk striping over a disk array is introduced and a Data Placement Strategy is designed which eliminates disk hot spots (i.e. Overuse of some disks whilst others lie idle.) A novel parameter (the B-P Ratio) is presented which can be used by the Server to predict future bursts from each video stream. The use of Traffic Shaping to decrease the load on the network from each stream is presented. Having investigated four algorithms for rewind and fast-forward in the literature, a rewind and fast-forward algorithm is presented. The method produces a significant decrease in bandwidth, and the resultant stream is very constant, reducing the chance that the stream will add to network congestion. The C++ classes of the Server, Broker and Client are described emphasizing the interaction between classes. The use of ATOM in the Virtual Private Network and the multimedia teaching laboratory is considered. Conclusions and recommendations for future work are presented. It is concluded that digital video applications require high bandwidth, low error, low delay networks; a video-on-demand system to support large Client volumes must be distributed, not centralized; control and operation (transport) must be separated; the number of ATM Switched Virtual Circuits (SVCs) must be minimized; the increased connections caused by the Broker mesh is justified by the distributed information gain; a Quality of Service solution must address end-to-end issues. It is recommended that a web front-end for Brokers be developed; the system be tested in a wide area A TM network; the Broker protocol be tested by forcing failure of a Broker and that a proprietary file format for disk striping be implemented

Some aspects of traffic control and performance evaluation of ATM networks

The emerging high-speed Asynchronous Transfer Mode (ATM) networks are expected to integrate through statistical multiplexing large numbers of traffic sources having a broad range of statistical characteristics and different Quality of Service (QOS) requirements. To achieve high utilisation of network resources while maintaining the QOS, efficient traffic management strategies have to be developed. This thesis considers the problem of traffic control for ATM networks. The thesis studies the application of neural networks to various ATM traffic control issues such as feedback congestion control, traffic characterization, bandwidth estimation, and Call Admission Control (CAC). A novel adaptive congestion control approach based on a neural network that uses reinforcement learning is developed. It is shown that the neural controller is very effective in providing general QOS control. A Finite Impulse Response (FIR) neural network is proposed to adaptively predict the traffic arrival process by learning the relationship between the past and future traffic variations. On the basis of this prediction, a feedback flow control scheme at input access nodes of the network is presented. Simulation results demonstrate significant performance improvement over conventional control mechanisms. In addition, an accurate yet computationally efficient approach to effective bandwidth estimation for multiplexed connections is investigated. In this method, a feed forward neural network is employed to model the nonlinear relationship between the effective bandwidth and the traffic situations and a QOS measure. Applications of this approach to admission control, bandwidth allocation and dynamic routing are also discussed. A detailed investigation has indicated that CAC schemes based on effective bandwidth approximation can be very conservative and prevent optimal use of network resources. A modified effective bandwidth CAC approach is therefore proposed to overcome the drawback of conventional methods. Considering statistical multiplexing between traffic sources, we directly calculate the effective bandwidth of the aggregate traffic which is modelled by a two-state Markov modulated Poisson process via matching four important statistics. We use the theory of large deviations to provide a unified description of effective bandwidths for various traffic sources and the associated ATM multiplexer queueing performance approximations, illustrating their strengths and limitations. In addition, a more accurate estimation method for ATM QOS parameters based on the Bahadur-Rao theorem is proposed, which is a refinement of the original effective bandwidth approximation and can lead to higher link utilisation

Three Essays on the Macroeconomic Consequences of Prices

To understand the workings of the macroeconomy, it is not enough to simply focus on the movements of the aggregate variables of the economy. It is necessary to also understand the behavior of its various components and their interactions. In this thesis, I study three important components of macroeconomic behavior; prices, wages, and the financial system and their connection to the behavior of the aggregate economy. In the first chapter (joint work with Andrew Usher), we use retail scanner data to show two previously unknown empirical facts about prices. First, the probability of price adjustment increases with product revenue. Second, the absolute size of price adjustment decreases with revenue. These facts are consistent with a menu cost model where the fixed cost of adjustment does not scale with product revenue. Taken together, these facts suggest that prices of products with higher revenues respond more to monetary policy than prices of products with lower revenues. Over the business cycle, both the mean and variance of the (log) revenue distribution across goods decrease with the unemployment rate. These empirical facts imply that monetary policy should have stronger effects on the economy in recessions than in expansions. We verify this property using a quantitative menu cost model, and we provide additional evidence of the state-dependence of monetary policy using aggregate data. In the second chapter (joint work with Miles S. Kimball), we study the optimal wage structure of a firm with imperfect monitoring of worker effort. We find that when firms can commit to (implicit) long-term contracts, imperfect monitoring leads to optimal wage profiles that reflect worker seniority. We provide a precise definition of seniority as a measure of worker value to the firm rather than the length of service by a worker. The paper illustrates how worker seniority will evolve over the worker's tenure with the firm and how wage, effort, and separation evolve with seniority. We also show that monitoring and amenities reflect seniority as well. To solve the optimal contract problem, we present a solution technique, the ``retrograde approach," of solving complex optimization problems with endogenous discounting and forward-looking state variables in a simple and intuitive way. In chapter three, I find that system wide runs can be triggered by small shocks to fundamental asset values. Informational frictions amplify small shocks causing large contractions in the amount of credit provided to financial institutions. Asset fire sales exacerbate these effects and force a complete collapse of lending to these institutions; a system wide run. The paper identifies the incentive of healthy institutions to differentiate themselves from distressed ones as the key channel driving the contraction in credit. This contrasts with traditional bank runs that stem from the coordination failures of lenders. The findings lead to direct policy implications; including a government clearing house for loans and quantitative easing.PHDEconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144157/1/dikang_1.pd

The Value of Bargaining in Online Platform Markets

Bargaining is an important pricing mechanism, prevalent in both the online and offline worlds. However, little empirical work on the value of bargaining in markets exists, primarily due to the lack of real-world bargaining data. In the first essay, "Meet Me Halfway: The Value of Bargaining", I leverage the availability of rich, transaction-level data on bargaining outcomes on an online platform to quantify the value of bargaining for sellers, buyers, and the platform. I incorporate the decision to bargain, the bargaining realization, and the purchase decision into a structural model, and I perform counterfactual analyses to show the value of allowing bargaining on the platform. I do this by disallowing bargaining, which means that all sellers on the platform must use a fixed-price mechanism. I find that sellers' profits are higher under the fixed-price only regime. The benefits are heterogeneous across sellers, however, with sellers with low reputation levels, high detailed seller ratings, and non-promotion products benefiting more. I also show that buyers' bargaining cost savings are economically significant. Thus, my findings suggest banning bargaining is beneficial for both buyers and sellers, and therefore for a social planner as well. I provide some reasons for why bargaining still exists on the platform despite the above findings. Finally, I show that the results are robust to the assumptions and can be replicated in different product categories. In the second essay, "Negotiation Pricing on a Health Platform Market: Bringing Hospitals and Patients Together", I study the bargaining between a business-to-consumer platform and the business-side of the platform. The platform connects hospitals with patients who seek health checkups. As a business entity, the platform negotiates with hospitals on the depth of price discount, online or offline payment, and clearing cycle (per transaction, weekly, or monthly). I investigate how the consumer network size and the hospital network size affect the hospitals' willingness to sign contracts and join the platform and the three key negotiation outcomes. I find that both network sizes have positive significant effects on hospitals' willingness to sign contracts and on the three negotiation outcomes, making hospitals more likely to accept terms that are more favorable to the platform. To further investigate the hospital side, I separate public and private hospital network sizes and find their effects on negotiation are heterogeneous. I discuss the findings and explore potential mechanisms behind these findings.PHDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145899/1/xuzh_1.pd