2657730
Approximate Analysis of Single and Multiple Ring Networks
Asynchronous packet-switched interconnection networks with decentralized control are very appropriate for multiprocessing and data-flow architectures. The authors present performance models of single- and multiple-ring networks based on token-ring, slotted-ring, and register-insertion-ring protocols. The multiple ring networks have the advantage of being reliable, expandable, and cost effective. An approximate and uniform analysis, based on the gate M/G/1 queuing model, has been developed to evaluate the performance of both existing single-ring networks and the proposed multiple-ring networks. Approximations are good for low and medium load. The analyses are based on symmetric ring structure with nonexhaustive service policy and infinite queue length at each station. They essentially involve modeling of queues with single- and multiple-walking servers. The results obtained from the analytical models are compared to those obtained from simulation. >
27106762
Analysis and Comparison of Cache Coherence Protocols for a Packet-Switched Multiprocessor
Analytical models are developed for seven existing cache protocols, namely, Write-Once, Write-Through, Synapse, Berkeley, Illinois, Firefly, and Dragon. The protocols are implemented on a multiprocessor with a packet-switched shared bus. The models are based on queuing networks that consist of both open and closed classes of customers. The models incorporate the requests for invalidation signals, write-through, and write-back operations, and the solution is based on the mean value analysis (MVA) algorithm. The performance of these protocols under various system parameters is compared on the basis of the models. It is found that Firefly and Dragon perform better than the others. >
30032661
Data preparation for data mining
Data preparation is a fundamental stage of data analysis. While a lot of low-quality information is available in various data sources and on the Web, many organizations or companies are interested in how to transform the data into cleaned forms which can be used for high-profit purposes. This goal generates an urgent need for data analysis aimed at cleaning the raw data. In this paper, we first show the importance of data preparation in data analysis, then introduce some research achievements in the area of data preparation. Finally, we suggest some future directions of research and development.
40202410
On Performance of Parallel iSCSI Protocol for Networked Storage Systems
A newly emerging protocol for storage networking, iSCSI, was recently ratified by the Internet Engineering Task Force. The iSCSI protocol is perceived as a low cost alternative to the FC protocol for networked storages. It allows block level storage data to be transported over the popular TCP/IP network that is widely understood. This paper presents a new storage architecture allowing parallel processing of iSCSI packets. By leveraging inexpensive Ethernet ports, we are able to greatly improve the throughput of iSCSI storages through parallel processing. We have carried out a performance analysis to evaluate the performance of the new architecture as compared to the existing iSCSI storages. Our numerical results show that the new architecture has good performance potential
18784921
Multidimensional Vector Regression for Accurate and Low-Cost Location Estimation in Pervasive Computing
In this paper, we present an algorithm for multidimensional vector regression on data that are highly uncertain and nonlinear, and then apply it to the problem of indoor location estimation in a wireless local area network (WLAN). Our aim is to obtain an accurate mapping between the signal space and the physical space without requiring too much human calibration effort. This location estimation problem has traditionally been tackled through probabilistic models trained on manually labeled data, which are expensive to obtain. In contrast, our algorithm adopts kernel canonical correlation analysis (KCCA) to build a nonlinear mapping between the signal-vector space and the physical location space by transforming data in both spaces into their canonical features. This allows the pairwise similarity of samples in both spaces to be maximally correlated using kernels. We use a Gaussian kernel to adapt to the noisy characteristics of signal strengths and a Matern kernel to sense the changes in physical locations. By using real data collected in an 802.11 wireless LAN environment, we achieve accurate location estimation for pervasive computing while requiring a much smaller set of labeled training data than previous methods
10182841
Planning as Refinement Search: A Unified Framework for Evaluating Design Tradeoffs in Partial-Order Planning
Despite the long history of classical planning, there has been very little comparative analysis of the performance tradeoffs offered by the multitude of existing planning algorithms. This is partly due to the many different vocabularies within which planning algorithms are usually expressed. In this paper we show that refinement search provides a unifying framework within which various planning algorithms can be cast and compared. Specifically, we will develop refinement search semantics for planning, provide a generalized algorithm for refinement planning, and show that planners that search in the space of (partial) plans are specific instantiations of this algorithm. The different design choices in partial-order planning correspond to the different ways of instantiating the generalized algorithm. We will analyze how these choices affect the search space size and refinement cost of the resultant planner, and show that in most cases they trade one for the other. Finally, we will concentrate on two specific design choices, viz., protection strategies and tractability refinements, and develop some hypotheses regarding the effect of these choices on the performance on practical problems. We will support these hypotheses with a series of focused empirical studies.
20437986
Design and analysis of multiple-bus arbiters with different priority schemes
The authors present four multiple-user and multiple-server arbiter designs of multiple-bus multiprocessors. All designs are based on decentralized control, which has the advantage of good reliability and potentially high throughput. The priority protocols considered are fixed priority, rotating priority, round-robin priority, and equal priority. For the first two priority protocols, lookahead techniques are used to speed up the arbitration process. The round-robin protocol is based on the decentralized daisy-chain idea and is operated in an asynchronous fashion. Analytical models are developed for the four different priority protocols to evaluate the performance of the different designs. The analyses are based on a probabilistic model for the synchronous case and simple queuing analysis for the asynchronous system. Numerical results obtained from the proposed model show that the equal priority protocol performs better than the others in the system with a few buses. The performance difference is not significant when the number of buses is relatively large.<<ETX>>