43889456
Integrating User Preferences and Real-Time Workload in Information Services
We propose priority pricing as an on-line adaptive resource scheduling mechanism to manage real-time databases within organizations. These databases provide timely information for delay sensitive users. The proposed approach allows diverse users to optimize their own objectives while collectively maximizing organizational benefits. We rely on economic principles to derive priority prices by modeling the fixed-capacity real-time database environment as an economic system. Each priority is associated with a price and a delay, and the price is the premium (congestion toll resulting from negative externalities) for accessing the database. At optimality, the prices are equal to the aggregate delay cost imposed on all other users of the database. These priority prices are used to control admission and to schedule user jobs in the database system. The database monitors the arrival processes and the state of the system, and incrementally adjusts the prices to regulate the flow. Because our model ignores the operational intricacies of the real-time databases (e.g., intermediate queues at the CPU and disks, memory size, etc.) to maintain analytical tractability, we evaluate the performance of our pricing approach through simulation. We evaluate the database performance using both the traditional real-time database performance metrics (e.g., the number of jobs serviced on time, average tardiness) and the economic benefits (e.g., benefits to the organization). The simulation results, under various database workload parameters, show that our priority pricing mechanism not only maximizes organizational benefits but also outperforms in all aspects of traditional performance measures compared to frequently used database scheduling techniques, such as first-come-first-served, earliest deadline first and least slack first.
57631
Insights and analyses of online auctions
30721210
Economic analysis of consumer purchase intentions in electronic and traditional retail channels: competitive and strategic implications
We develop a multiattribute economic model to analyze consumer behavior for traditional and electronic channels based on consumers' risk profiles and risk-neutral or risk-averse. We then conduct comparative analyses of consumer purchase decisions to derive strategies for different channels. We study the attitudinal and economic factors that lead to specific purchase decisions under different combinations of price, delivery time, and product customization. We develop theoretical propositions concerning consumer channel switching behavior, incentives to consumers, and pricing strategies for different channels. We also use simulations to gain insights for cases where analytical model becomes intractable.
7914809
Predicting Bidders' Willingness to Pay in Online Multiunit Ascending Auctions: Analytical and Empirical Insights
We develop a real-time estimation approach to predict bidders' maximum willingness to pay in a multiunit ascending uniform-price and discriminatory-price (Yankee) online auction. Our two-stage approach begins with a bidder classification step, which is followed by an analytical prediction model. The classification model identifies bidders as either adopting a myopic best-response (MBR) bidding strategy or a non-MBR strategy. We then use a generalized bid-inversion function to estimate the willingness to pay for MBR bidders. We empirically validate our two-stage approach using data from two popular online auction sites. Our joint classification-and-prediction approach outperforms two other naive prediction strategies that draw random valuations between a bidder's current bid and the known market upper bound. Our prediction results indicate that, on average, our estimates are within 2% of bidders' revealed willingness to pay for Yankee and uniform-price multiunit auctions. We discuss how our results can facilitate mechanism-design changes such as dynamic-bid increments and dynamic buy-it-now prices.
17233820
IT-enabled transparent electronic markets: the case of the air travel industry
The electronic market hypothesis predicts that by reducing coordination costs, information technology (IT) will shift industrial organization from hierarchical to market-based forms of economic activity. While academic researchers and practitioners have witnessed these shifts with the advent of the Internet, there is little understanding about the process and the underlying forces that drive them. In this paper, we provide an in-depth analysis of the air travel industry, which has recently experienced significant IT-driven transformations. We conclude that, together with IT, pro-competitive laws and the information-intensive nature of air travel products have triggered competition for consumers with transparent market mechanisms, which is leading to the emergence of more transparent electronic markets in the air travel industry.
166893960
Priority pricing of integrated services networks
10962942
Towards bringing database management task in the realm of IT non-experts
Internet enabled services have led to an increase in the size and complexity of the database making the database administration task very complex. This necessitates the hiring of skilled personnel for the management of data, which is a bane for industries, especially in developing countries. We at IBM India research Lab, have been developing technologies (i.e. database administration tools), wherein the database administrator, who may be inexperienced person, can define error-free policies for managing and maintaining the distributed information repositories, and can define data access privileges to users at fine as well as at coarse-grained level using natural language like constructs. These policies represent the actions that need to be carried out when specific database/temporal events occur within the system or externally and are notified to the system. In this paper, we discuss the architecture of our policy based database administration and access control system and outline some of the technical challenges in this area.
17420676
A workstation's communication performance benchmark
In this paper we propose a communication benchmark suite: BTU(Bits To the User). In the BTU benchmarking process, the vendor supplies a workstation running a UNIX* operating system, we install our benchmark program and connect the workstation to a testbed which emulates a LAN/WAN environment. The benchmark run will submit the workstation to a carefully designed combination of tests. The result is a predictor of what the user, at the application level, can expect in terms of bits sent to or received from a remote host. Our benchmark takes into account concurrent activities such as CPU and I/O activities which compete for resources on the test machine. The combination of these activities and concurrent activities on the network will interfere with the test machine’s communication performance. The automated BTU benchmark test suite produces results at various levels of abstractions ranging from a single number, characterizing average performance in the style of SPEC92, to a TCP time sequence chart for abnormal behaviors. We intend to serve the user of a workstation by providing information which should enable the users to make a reasonable judgment when acquiring a workstation with a specific configuration within certain cost constraints. Our results when used along with existing benchmarks will make a powerful combination for predicting overall performance. Neither price nor SPECmarks are as good a predictor of communication performance as that measured by BTUs. We conclude this paper with a discussion of extensions to faster networks and our plans for having the community accept this proposal as a communication benchmark.
18542805
IT infrastructure in emerging markets: arguing for an end-to-end perspective
To help sustain large-scale pervasive computing in emerging markets, researchers must address unique challenges in the delivery fabric and enterprise backbone. Such challenges present opportunities for high impact innovation. Although most research organizations have focused on developing consumer-facing solutions, we posit that future research must take an end-to-end perspective. That is, researchers must not only consider the front end (such as consumer devices) but also the medium to reach the consumer (for example, the delivery fabric) and the back end (for example, the enterprise backbone) to create an economically sustainable, scalable solution. Although our end-to-end perspective generalizes to all emerging markets, in this article, we mainly discuss the Indian market from which we based our observations.
37839097
Retaining personal expression for social search
Web is being extensively used for personal expression, which includes ratings, reviews, recommendations, blogs. This user created content, e.g. book review on Amazon.com, becomes the property of the website, and the user often does not have easy access to it. In some cases, user's feedback may get averaged with feedback from other users e.g. ratings of a video. We argue that the creator of such content needs to be able to retain (a link to) her created content. We introduce the concept of MEB which is a user controlled store of such retained links. A MEB allows a user to access/share all the reviews she has given on different websites. With this capability users can allow their friends to search through their feedback. Searching through one's social network allows harnessing the power of social networks where known relationships provide the context & trust necessary to interpret feedback.
116973756
Surface and volumetric segmentation of complex 3-D objects using parametric shape models
The problem of part definition, description, and decomposition is central to the shape recognition systems. In this dissertation, we develop an integrated framework for segmenting dense range data of complex 3-D scenes into their constituent parts in terms of surface and volumetric primitives. Unlike previous approaches, we use geometric properties derived from surface, as well as volumetric models, to recover structured descriptions of complex objects without a priori domain knowledge or stored models. 
To recover shape descriptions, we use bi-quadric models for surface representation and superquadric models for object-centered volumetric representation. The surface segmentation uses a novel approach of searching for the best piecewise description of the image in terms of bi-quadric (z = f(x, y)) models. It is used to generate the region adjacency graphs, to localize surface discontinuities, and to derive global shape properties of the surfaces. A superquadric model is recovered for the entire data set and residuals are computed to evaluate the fit. The goodness-of-fit value based on the inside-outside function, and the mean-squared distance of data from the model provide quantitative evaluation of the model. The qualitative evaluation criteria check the local consistency of the model in the form of residual maps of overestimated and underestimated data regions. 
The control structure invokes the models in a systematic manner, evaluates the intermediate descriptions, and integrates them to achieve final segmentation. Superquadric and bi-quadric models are recovered in parallel to incorporate the best of the coarse-to-fine and fine-to-coarse segmentation strategies. The model evaluation criteria determine the dimensionality of the scene, and decide whether to terminate the procedure, or selectively refine the segmentation by following a global-to-local part segmentation approach. The control module generates hypotheses about superquadric models at clusters of underestimated data and performs controlled extrapolation of the part-model by shrinking the global model. As the global model shrinks and the local models grow, they are evaluated and tested for termination or further segmentation. 
We present results on real range images of scenes of varying complexity, including objects with occluding parts, and scenes where surface segmentation is not sufficient to guide the volumetric segmentation. We analyze the issue of segmentation of complex scenes thoroughly by studying the effect of missing data on volumetric model recovery, generating object-centered descriptions, and presenting a complete set of criteria for the evaluation of the superquadric models. We conclude by discussing the applications of our approach in data reduction, 3-D object recognition, geometric modeling, automatic model generation, object manipulation, and active vision.