14269691
Multiprocessor scalability predictions through detailed program execution analysis
Scalability measures the ability of a parallel system to improve performance as the size of an application problem and the number of processors involved increase. There are some limits to existing scalability studies. First, the problem size in a computation is not well-defined. Second, the methods used to differentiate algorithmic and architectural scalabilities are not effective enough. Thh-dly, most approaches to scalability study are either highly time-consuming or restricted to simple problem/architecture structures. A major effort of this work is to address these limits. We have extended the latency metric [11] for more complex scaling of problems, and to possibly isolate the scalability of an algorithm from a parallel system. The scalability y prediction is based on a semi-empirical approach [10] that significantly reduces the time and cost of measurements and simulation. Our prediction results were validated on the KSR1 and on the CM-5.
13613044
Low-Cost and Reliable Mutual Anonymity Protocols in Peer-to-Peer Networks
We present several protocols to achieve mutual communication anonymity between an information requester and a provider in a P2P information-sharing environment, such that neither the requester nor the provider can identify each other, and no other peers can identify the two communicating parties with certainty. Most existing solutions achieve mutual anonymity in pure P2P systems without any trusted central controls. Compared with two such representative ones, our protocols improve efficiency in two different ways. First, utilizing trusted third parties and aiming at both reliability and low-cost, we propose a group of mutual anonymity protocols. We show that with some limited central support, our protocols can accomplish the goals of anonymity, efficiency, and reliability. Second, we propose a mutual anonymity protocol which relies solely on self-organizations among peers without any trusted central controls. In this protocol, the returning path can be shorter than the requesting path. This protocol does not need to broadcast the requested file back to the requester so that the bandwidth is saved and efficiency is improved. In addition, this protocol does not need special nodes to keep indices of sharing files, thus eliminating the index maintenance overhead and the potential for inconsistency between index records and peer file contents. We have evaluated our techniques in a browser-sharing environment. We show that the average increase in response time caused by our protocols is negligible, and these protocols show advantages over existing protocols in a P2P system.
7906272
Coordinating Parallel Processes on Networks of Workstations
The network of workstations (NOW) we consider for scheduling is heterogeneous and nondedicated, where computing power varies among the workstations and local and parallel jobs may interact with each other in execution. An effective NOW scheduling scheme needs sufficient information about system heterogeneity and job interactions. We use the measured power weight of each workstation to quantify the differences of computing capability in the system. Without a processing power usage agreement between parallel jobs and local user jobs in a workstation, job interactions are unpredictable, and performance of either type of jobs may not be guaranteed. Using the quantified and deterministic system information, we design a scheduling scheme calledself-coordinated local schedulingon a heterogeneous NOW. Based on a power usage agreement between local and parallel jobs, this scheme coordinates parallel processes independently in each workstation based on the coscheduling principle. We discuss its implementation on Unix System V Release 4 (SVR4). Our simulation results on a heterogeneous NOW show the effectiveness of the self-coordinated local scheduling scheme.
1520083
Token-ordered LRU: an effective page replacement policy and its implementation in Linux systems
Most computer systems use a global page replacement policy based on the LRU principle to approximately select a Least Recently Used page for a replacement in the entire user memory space. During execution interactions, a memory page can be marked as LRU even when its program is conducting page faults. We define the LRU pages under such a condition as false LRU pages because these LRU pages are not produced by program memory reference delays, which is inconsistent with the LRU principle. False LRU pages can significantly increase page faults, even cause system thrashing. This poses a more serious risk in a large parallel systems with distributed memories because of the existence of coordination among processes running on individual node. In the case, the process thrashing in a single node or a small number of nodes could severely affect other nodes running coordinating processes, even crash the whole system. In this paper, we focus on how to improve the page replacement algorithm running on one node. After a careful study on characterizing the memory usage and the thrashing behaviors in the multi-programming system using LRU replacement. we propose an LRU replacement alternative, called token-ordered LRU, to eliminate or reduce the unnecessary page faults by effectively ordering and scheduling memory space allocations. Compared with traditional thrashing protection mechanisms such as load control, our policy allows more processes to keep running to support synchronous distributed process computing. We have implemented the token-ordered LRU algorithm in a Linux kernel to show its effectiveness.
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.
12471348
Look-Ahead Architecture Adaptation to Reduce Processor Power Consumption
An effective approach to reducing processor power consumption is to adaptively activate and deactivate hardware resources. The authors propose a look-ahead scheme that adjusts the processor issue rate triggered by main-memory accesses. This architecture-independent technique is particularly effective for memory-intensive applications. Combined with an existing technique based on IPC values, it also reduces power consumption for computation-intensive applications.
1661896
Multiscale Fragile Watermarking Based on the Gaussian Mixture Model
In this paper, a new multiscale fragile watermarking scheme based on the Gaussian mixture model (GMM) is presented. First, a GMM is developed to describe the statistical characteristics of images in the wavelet domain and an expectation-maximization algorithm is employed to identify GMM model parameters. With wavelet multiscale subspaces being divided into watermarking blocks, the GMM model parameters of different watermarking blocks are adjusted to form certain relationships, which are employed for the presented new fragile watermarking scheme for authentication. An optimal watermark embedding method is developed to achieve minimum watermarking distortion. A secret embedding key is designed to securely embed the fragile watermarks so that the new method is robust to counterfeiting, even when the malicious attackers are fully aware of the watermark embedding algorithm. It is shown that the presented new method can securely embed a message bit stream, such as personal signatures or copyright logos, into a host image as fragile watermarks. Compared with conventional fragile watermark techniques, this new statistical model based method modifies only a small amount of image data such that the distortion on the host image is imperceptible. Meanwhile, with the embedded message bits spreading over the entire image area through the statistical model, the new method can detect and localize image tampering. Besides, the new multiscale implementation of fragile watermarks based on the presented method can help distinguish some normal image operations such as JPEG compression from malicious image attacks and, thus, can be used for semi-fragile watermarking
620811
Using data mining techniques to learn layouts of flat-file biological datasets
One of the major problems in biological data integration is that many data sources are stored as atlasses, with a variety of different layouts. Integrating data from such sources can be an extremely time-consuming task. We have been developing data mining techniques to help learn the layout of a dataset in a semi-automatic way. In this paper, we focus on the problem of identifying delimiters for optional fields. Since these fields do not occur in every record, frequency based methods are not able to identify the corresponding delimiters. We present a method which uses contrast analysis on the frequency of sequences to identify such delimiters and help complete the layout descriptions. We demonstrate the effectiveness of this technique using three atlasses biological datasets.
18526893
Scaling and parallelizing a scientific feature mining application using a cluster middleware
Summary form only given. As scientific simulations are generating large amounts of data, analyzing this data to gain insights into scientific phenomenon is increasingly becoming a challenge. We present a case study on the use of a cluster middleware for rapidly creating a scalable and parallel implementation of a scientific data analysis application. Using FREERIDE (framework for rapid implementation of data mining engines), we parallelize as well as scale to disk-resident datasets a feature extraction algorithm. We have developed a parallel algorithm for this problem which matches the communication and computation structure supported by the FREERIDE system. The main observations from our experimental results are as follows: 1) the overhead of using the middleware is quite small in most cases, 2) there is an overhead associated with breaking the datasets into more partitions or chunks, and 3) if the dataset is partitioned into the same number of chunks, the execution time stays proportional to the size of the dataset and inversely proportional to the number of nodes, i.e. the overhead of communication or reading disk-resident datasets is very small.
28741459
Learning Layouts of Biological Datasets Semi-automatically
A key challenge associated with the existing approaches for data integration and workflow creation for bioinformatics is the effort required to integrate a new data source. As new data sources emerge, and data formats and contents of existing data sources evolve, wrapper programs need to be written or modified. This can be extremely time consuming, tedious, and error-prone. 
 
This paper describes our semi-automatic approach for learning the layout of a flat-file bioinformatics dataset. Our approach involves three key steps. The first step is to use a number of heuristics to infer the delimiters used in the program. Specifically, we have developed a metric that uses information on the frequency and starting position of sequences. Based on this metric, we are able to find a superset of delimiters, and then we can seek user input to eliminate the incorrect ones. Our second step involves generating a layout descriptor based on the relative order in which the delimiters occur. Our final step is to generate a parser based on the layout descriptor. Our heuristics for finding the delimiters has been evaluated using three popular flat-file biological datasets.
1818817
An Exploratory Study on Knowledge Sharing in Information Retrieval
Different types of knowledge have been found important for a successful search. We designed a user interface: CIRR tool (Collaborative Information Retrieval Research) that supports sharing of search results as well as search queries (knowledge of finding the relevant items). We conducted a pilot study to explore what factors would affect the use of these knowledge sharing features. The results demonstrate that knowledge sharing in general is preferred by only some subjects for some tasks. For those who preferred sharing they share search queries, domain knowledge, and search results, rather than the usefulness judgment. The findings also show that knowledge sharing does not seem to have effects on search performance. However, it is significantly associated with the perceived task difficulty. The possible reasons leading to these results are analyzed. Limitations of this study are pointed out and the future studies are discussed.