10102756
Semi-Empirical Multiprocessor Performance Predictions
This paper presents a multiprocessor performance prediction methodology supported by experimental measurements, which predicts the execution time of large application programs on large parallel architectures based on a small set of sample data. We propose a graph model to describe application program behavior. In order to precisely abstract an architecture model for the prediction, important and implicit architecture parameters are obtained by experiments. We focus on performance predictions of application programs in shared-memory and data-parallel architectures. Real world applications are implemented using the shared-memory model on the KSR-1 and using the data-parallel model on the CM-5 for performance measurements and prediction validation. We show that experimental measurements provide strong support for performance predictions on multiprocessors with implicit communications and complex memory systems, such as shared-memory and data-parallel systems, while analytical techniques partially applied in the prediction significantly reduce computer simulation and measurement time.
5918703
Delving into internet streaming media delivery: a quality and resource utilization perspective
Modern Internet streaming services have utilized various techniques to improve the quality of streaming media delivery. Despite the characterization of media access patterns and user behaviors in many measurement studies, few studies have focused on the streaming techniques themselves, particularly on the quality of streaming experiences they offer end users and on the resources of the media systems that they consume. In order to gain insights into current streaming services techniques and thus provide guidance on designing resource-efficient and high quality streaming media systems, we have collected a large streaming media workload from thousands of broadband home users and business users hosted by a major ISP, and analyzed the most commonly used streaming techniques such as automatic protocol switch, Fast Streaming, MBR encoding and rate adaptation. Our measurement and analysis results show that with these techniques, current streaming systems these techniques tend to over-utilize CPU and bandwidth resources to provide better services to end users, which may not be a desirable and effective is not necessary the best way to improve the quality of streaming media delivery. Motivated by these results, we propose and evaluate a coordination mechanism that effectively takes advantage of both Fast Streaming and rate adaptation to better utilize the server and Internet resources for streaming quality improvement.
9344326
Fine-grain priority scheduling on multi-channel memory systems
Configurations of contemporary DRAM memory systems become increasingly complex. A recent study shows that the application performance is highly sensitive to choices of configurations. In this study we show that, by utilizing fine-grain priority access scheduling, we are able to find a workload independent configuration that achieves optimal performance on a multichannel memory system. Our approach can well utilize the available high concurrency and high bandwidth on such memory systems, and effectively reduce the memory stall time of memory-intensive applications. Conducting execution-driven simulation of a 4-way issue, a 2 GHz processor, we show that the average performance improvement for fifteen memory-intensive SPEC2000 programs by using an optimized fine-grain priority scheduling is about 13% and 8% for a 2-channel and a 4-channel Direct Rambus DRAM memory system, respectively, compared with gang scheduling. Compared with burst scheduling, the average performance improvement is 16% and 14% for the 2-channel and 4-channel memory systems, respectively.
6064925
Coordinated data prefetching for web contents
With the development of active proxy, the functions of a proxy have been enhanced beyond simply storing Web contents. Web prefetching activity in proxy is such an example to reduce client-perceived latency. In this paper, we propose a coordinated proxy-server prefetching technique that adaptively utilizes the access information and coordinates prefetching activities at both proxy and Web servers. In our design, the access information stored in proxies will be the main source serving data prefetching for groups of clients sharing common surfing interests. The access information in the Web server will be used to serve data prefetching only for data objects that are not qualified for proxy-based prefetching. Conducting trace-driven simulations, we show that both hit ratios and byte hit ratios contributed from coordinated proxy-server prefetching are 30-75% higher than other prefetching schemes, and they are comparable to the ratios from a proxyless server-based prefetching that is able to observe every access to the server.
8429922
ASAP: an AS-Aware Peer-Relay Protocol for High Quality VoIP
Peer-to-peer (P2P) technology has been successfully applied in Internet telephony or Voice over Internet Protocol (VoIP), such as the Skype system, where P2P is used for both searching clients and relaying voice packets. Selecting one or multiple suitable peers to relay voice packets is a critical factor for the quality, scalability and cost of a VoIP system. In this paper, we first present two sets of intensive Internet measurement results to confirm the benefits gained by peer relays in VoIP, and to investigate the performance of the Skype system. We obtain the following results: (1) many relay peer selections are suboptimal; (2) the waiting time to select a relay node can be quite long; and (3) there are a large number of unnecessary probes, resulting in heavy network traffic to limit scalability of the VoIP system. Our further analysis shows that two main reasons cause these problems. First, the peer selections do not take Autonomous System (AS) topology into consideration, and second, the complex communication relationships among peers are not well utilized. Motivated by our measurements and analysis, we propose an AS-aware peer-relay protocol called ASAP. Our objective is to significantly improve VoIP quality and system scalability with low overhead. Our intensive evaluation by trace-driven simulation shows ASAP is highly effective and easy to implement on the Internet for building large and scalable VoIP systems.
82838
Designs of high quality streaming proxy systems
Researchers often use segment-based proxy caching strategies to deliver streaming media by partially caching media objects. The existing strategies mainly consider increasing the byte hit ratio and/or reducing the client perceived startup latency (denoted by the metric delayed startup ratio). However, these efforts do not guarantee continuous media delivery because the to-be-viewed object segments may not be cached in the proxy when they are demanded. The potential consequence is playback jitter at the client side due to proxy delay in fetching the uncached segments, which we call proxy jitter. Thus, for the best interests of clients, a correct model for streaming proxy system design should aim to minimize proxy jitter subject to reducing the delayed startup ratio and increasing the byte hit ratio. However, we have observed two major pairs of conflicting interests inherent in this model: (1) one between improving the byte hit ratio and reducing proxy jitter, and (2) the other between improving the byte hit ratio and reducing the delayed startup ratio. In this study, we first propose an active prefetching method for in-time prefetching of uncached segments, which provides insights into the first pair of conflicting interests. Second, we further improve our lazy-segmentation scheme which effectively addresses the second pair of the conflicting interests. Finally, considering our main objective of minimizing proxy jitter and optimizing the two trade-offs, we propose a new streaming proxy system called Hyper Proxy by effectively coordinating both prefetching and segmentation techniques. Synthetic and real workloads are used to systematically evaluate our system. The performance results show that the hyper proxy system generates minimum proxy jitter with a low delayed startup ratio and a small decrease of byte hit ratio compared with existing schemes
14687114
Price Cycles in Online Advertising Auctions
Paid placement in search engines has become one of the most successful and rapidly growing sectors of the online advertising industry. The innovative use of auctions to sell keyword-related advertisement positions is perhaps the most important factor driving the success of this market. There has been no systematic analysis, however, of the advertisers’ strategies to bid for ranks in a dynamic environment, where each bidder’s bid can be updated and observed by the competitors in real time. We capture this dynamic setting using a Markov process and identify the Markov perfect equilibrium. We find that in such a dynamic environment, bidders’ bidding strategies follow a cyclical pattern (Edgeworth cycle) similar to that conjectured by Edgeworth (1925) in a totally different context. A new data set that contains a detailed bidding history of all advertisers for sample keywords in a leading search engine makes it possible for us to study the real-world behavior of bidders. We propose an empirical framework based on maximum likelihood estimation of latent Markov state switching to confirm the theory. We also discuss the theoretical and practical significance of finding such cycles in an online market place.
26388893
Grouping edge points into line segments by sequential Hough transformation
An algorithm to group edge points into digital line segments with Hough transformation is described. The edge points are mapped onto the parameter domain discretized at specific intervals, on which peaks appear to represent different line segments. By modeling each peak as a Gaussian function in the parameter domain, a region to which the edge points are supposed to be mapped is determined. Then the edge points are grouped and the parameters for a line segment are computed. For the edges including multiple line segments, a sequential Hough transformation for detecting peaks one by one in the parameter domain is implemented, and the points from the region around each peak are grouped, thus the line segments are described. Experiments show the robustness of the algorithm implemented on both the generated edges disturbed by different noise levels and real images taken from an indoor environment.
8448018
Efficient Frequent Pattern Mining on Web Logs
Mining frequent patterns from Web logs is an important data mining task. Candidate-generation-and-test and pattern-growth are two representative frequent pattern mining approaches. We have conducted extensive experiments on real world Web log data to analyse the characteristics of Web logs and the behaviours of these two approaches on Web logs. To improve the performance of current algorithms on mining Web logs, we propose a new algorithm – Combined Frequent Pattern Mining (CFPM) to cater for Web log data specifically. We use heuristics to prune search space and reduce costs in mining so that better efficiency is achieved. Experimental results show that CFPM significantly improves the performance of the pattern-growth approach by 1.2–7.8 times on mining frequent patterns from Web logs.
40769679
Content-based image retrieval using a Gaussian mixture model in the wavelet domain
The research on Content-based Image Retrieval (CBIR) has been very active in recent years. The performance of a CBIR system can be significantly improved by selecting a good indexing feature space to represent image characteristics. In this paper, we introduce a statistical-model based technique for analyzing and extracting image features in the wavelet domain. The images are decomposed into a set of wavelet subspaces in the wavelet domain and for each wavelet subspace, a two component Gaussian mixture model is developed to describe the statistical characteristics of the wavelet coefficients. The model parameters, which are a good reflection of image features in the wavelet subspaces, are obtained by an EM (Expectation-Maximization) algorithm and employed to construct the indexing feature space for a CBIR system. We apply the new method on the Brodatz image database to demonstrate its performance. The experimental results indicate that our indexing feature space is very effective in representing image characteristics and provides a high retrieval rate in the CBIR system. When compared with some other conventional feature extraction methods, the new method achieves comparable retrieval performance with less number of features in the feature space, which means it is more computationally efficient.
194152
A class of nonlinear stochastic volatility models and its implications for pricing currency options
A class of stochastic volatility (SV) models is proposed by applying the Box-Cox transformation to the volatility equation. This class of nonlinear SV (N-SV) models encompasses all standard SV models, including the well-known lognormal (LN) SV model. It allows to empirically compare and test all standard specifications in a very convenient way and provides a measure of the degree of departure from the classical models. A likelihood-based technique is developed for analyzing the model. Daily dollar/pound exchange rate data provide some evidence against LN model and strong evidence against all the other classical specifications. An efficient algorithm is proposed to study the economic importance of the proposed model on pricing currency options.