7800069
Detection of summative global predicates
In distributed programs, we usually keep some global predicates from being satisfied to make it easy to run the programs correctly. A common type of global predicates are: the total number of certain tokens in the whole distributed system is always the same or in specific ranges. In this paper, we call this summative predicates, classified into the following four: (1) at some global state of the system, N/spl ne/K, (2) NK (or N/spl ges/K), and (4) N=K, where N is the total number of tokens and K is a constant. This paper investigates the methods of detecting various summative global predicates. The first class of summative predicates are trivial to detect by simply checking each message. For the second class of summative predicates, B. Groselj (1993) and V.K. Garg (1995) solved the problem by reducing the problem to a maximum network flow problem. In this paper, we propose an elegant technique, called normalization, to allow the second and third classes of summative predicates to be solved by also reducing the problem to a maximum network flow problem. For the fourth class of summative predicates, we prove that it is an NP-complete problem.
2039675
On Detection of Bounded Global Predicates
Distributed programs often follow some bounded global predicates, for example, the total number of certain tokens is always the same or bounded in a range. In order to detect bounded global predicates, we can first derive the minimum and maximum global snapshots and then check if the minimum and maximum are out of the range. Recently, Chase and Garg proposed an efficient method to derive the minimum global snapshot by reducing this problem to a maximum network flow problem. A restriction of this method is that all message values (e.g., the token number in messages) must be zero and all process state values (e.g., the token number in processes) must be non-negative. In this paper, we propose an elegant technique, called normalization. By using this technique, we can remove the above restriction and also derive the minimum and maximum global snapshots at the same time.
205888059
On the Time Complexity of Minimum and Maximum Global Snapshot Problems
Abstract Deriving the minimum and maximum global snapshots is very useful for some error detection problems in distributed programs. Several researchers, e.g., Groselj, Chen and Wu, have shown that the minimum and maximum global snapshot problems are linear-time reducible to the maximum constant-ratio network flow (MCNF) problem, here defined as the wellknown maximum network flow problem with m = Θ(n), where m is the number of edges and n is the number of vertices in the given flow network. In this paper we show in a reverse way that the MCNF problem is also linear-time reducible to these global snapshot problems. Thus, we can conclude that the global snapshot problems are “as difficult as” the MCNF problem in terms of time complexity.
8727184
Estimating Link Capacity in High Speed Networks
Knowledge of bottleneck capacity of an Internet path is critical for efficient network design, management, and usage. With emerging high speed Internet links, most traditional estimation techniques are limited in providing fast and accurate capacity estimations. In this paper, we propose a new technique, called PBProbe, to estimate high speed links. PBProbe is based on CapProbe; however, instead of solely relying on packet pairs, PBProbe employs a “packet bulk” technique and adapts the bulk length in order to overcome the well known problem with packet pair based approaches, namely the lack of accurate timer resolution. As a result, PBProbe not only preserves the simplicity and speed of CapProbe, but it also correctly estimates link capacities within a much larger range. Using analysis, we evaluate PBProbe with various bulk lengths and network configurations. We then perform emulation and Internet experiments to verify the accuracy and speed of PBProbe on high speed links. The results show that PBProbe is consistently fast and accurate in the great majority of test cases.
4775385
A fine-grained replacement strategy for XML query cache
Caching popular queries and reusing results of previously computed queries is one important query optimization technique, especially in modern distributed environments such as the WWW. Based on the recent proliferation of XML data and the emergence of the XQuery language, we are thus developing a query- based caching system for XQuery queries, called ACE-XQ. ACE-XQ applies innovative query containment and rewriting strategies to answer incoming user queries based on the cached XQueries, whenever possible, instead of accessing remote XML data sources.To manage the space of the cache, a straightforward application of traditional replacement strategies would correspond to removing a complete cached query and its derived XML document as a whole when space needs to be freed. This coarse granularity however does not match well with the typical access pattern of web searches where new queries often partially overlap with cached queries.In this paper, we propose a novel replacement strategy appropriate for such query-based XML caching systems. In particular, we collect user access statistics at the granularity of the XML path structure instead of the complete XML query regions. We then apply a more fine-grained replacement strategy that purges XML fragments off a cached region instead of the whole XML document and accordingly adjusts the query descriptor. This may better capture the user access patterns since more frequently used XML document fragments are likely to remain in the cache while other less beneficial parts are purged. This approach has been implemented in our ACE-XQ System. Preliminary experiment results illustrate the performance improvement achievable by our fine-grained replacement strategy over the one which replaces a whole XML view at a time when the cache size is relatively large.
11658624
Statistical Feature Selection for Mandarin Speech Emotion Recognition
Performance of speech emotion recognition largely depends on the acoustic features used in a classifier. This paper studies the statistical feature selection problem in Mandarin speech emotion recognition. This study was based on a speaker dependent emotional mandarin database. Pitch, energy, duration, formant related features and some velocity information were selected as base features. Some statistics of them consisted of original feature set and full stepwise discriminant analysis (SDA) was employed to select extracted features. The results of feature selection were evaluated through a LDA based classifier. Experiment results indicate that pitch, log energy, speed and 1st formant are the most important factors and the accuracy rate increases from 63.1 % to 76.5 % after feature selection. Meanwhile, the features selected by SDA are better than the results of other feature selection methods in a LDA based classifier and SVM. The best performance is achieved when the feature number is in the range of 9 to 12.
26340415
Effects of Filtering Policies on Task Performance in a Desktop CVE System
To quantify the regularity of state updates, the concept of Irregular Degree was introduced. Two experiments corresponding to four different filtering policies were designed. In the first experiment three filtering policies based on Irregular Degree were compared. In the second experiment, the filtering policy achieving the best task performance in the first experiment was selected to compare with other filtering policies. The results of the first experiment indicate that the stability of state updates per second is a more important impact factor than Irregular Degree on the task performance. The results of the second experiment indicate that corresponding to different state updates per second, the filtering policies can achieve different task performance.
26961598
A Distributed Power-Efficient Data Gathering and Aggregation Protocol for Wireless Sensor Networks
In this paper, we propose a distributed power-efficient data gathering and aggregation algorithm (DPEG), in which a node, according to its residual energy and the strength of signal received from its neighboring nodes, independently makes its decision to compete for becoming a cluster head. In addition, assume that the inter-cluster communication data is, in a multi-hop manner, sent to the designated node, which then sends the data gathered by the whole network to the base station. DPEG also proposes a simple approach to solve the cluster coverage problem. With the increase in node density, this approach lets sensor network lifetime be linear in the number of nodes. Our experimental results have proved that DPEG algorithm, in the best case, lets sensor network lifetime be respectively increased by 1800% and 300% as compared with another two data gathering and aggregation protocols— LEACH and PEGASIS.