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.
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.
4784687
SERF: ODMG-based generic re-structuring facility
The age of information management and with it the advent of increasingly sophisticated technologies have kindled a need in the database community and others to re-structure existing systems and move forward to make use of these new technologies. Legacy application systems are being transformed to newer state-of-the-art systems, information sources are being mapped from one data model to another, a diversity of data sources are being transformed to load, cleanse and consolidate data into modern data-warehouses [CR99].
Re-structuring is thus a critical task for a variety of applications. For this reason, most object-oriented database systems (OODB) today support some form of re-structuring support [Tec94, Obj93, BKKK87]. This existing support of current OODBs [BKKK87, Tec94, Obj93] is limited to a pre-defined taxonomy of simple fixed-semantic schema evolution operations. However, such simple changes, typically to individual types only, are not sufficient for many advanced applications [Bré96]. More radical changes, such as combining two types of redefining the relationship between two types, are either very difficult or even impossible to achieve with current commercial database technology [Tec94, Obj93]. In fact, most OODBs would typically require the user to write ad-hoc programs to accomplish such transformations. Research that has begun to look into the issue of complex changes [Bré96, Ler96] is still limited by providing a fixed set of some selected (even if now more complex) operations.
To address these limitations of the current restructuring technology, we have proposed the SERF framework which aims at providing a rich environment for doing complex user-defined transformations flexibly, easily and correctly [CJR98b]. The goal of our work is to increase the usability and utility of the SERF framework and its applicability to re-structuring problems beyond OODB evolution. Towards that end, we provide re-usable transformations via the notion of SERF Templates that can be packaged into libraries, thereby increasing the portability of these transformations. We also now have a first cut at providing an assurance of consistency for the users of this system, a semantic optimizer that provides some performance improvements via enhanced query optimization techniques with emphasis on the re-structuring primitives [CNR99]. In this demo we give an overview of the SERF framework, its current status and the enhancements that are planned for the future. We also present an example of the application of SERF to a domain other than schema evolution, i.e., the web restructuring.
1469255
Approximation algorithms for data distribution with load balancing of web servers
Given the increasing traffic on the World Wide Web (Web), it is difficult for a single popular Web server to handle the demand from its many clients. By clustering a group of Web servers, it is possible to reduce the origin Web server's load significantly and reduce user's response time when accessing a Web document. A fundamental question is how to allocate Web documents among these servers in order to achieve load balancing? In this paper, we are given a collection of documents to be stored on a cluster of Web servers. Each of the servers is associated with resource limits in its memory and its number of HTTP connections. Each document has an associated size and access cost. The problem is to allocate the documents among the servers so that no server's memory size is exceeded, and the load is balanced as equally as possible. In this paper, we show that most simple formulations of this problem are NP-hard, we establish lower bounds on the value of the optimal load, and we show that if there are no memory constraints for all the servers, then there is an allocation algorithm, that is within a factor 2 of the optimal solution. We show that if all servers have the same number of HTTP connections and the same memory size, then a feasible allocation is achieved within a factor 4 of the optimal solution using at most 4 times the optimal memory size. We also provide improved approximation results for the case where documents are relatively small.
6229211
Resource allocation in a middleware for streaming data
Increasingly, a number of applications rely on, or can potentially benefit from, analysis and monitoring of <i>data streams.</i> To support processing of streaming data in a grid environment, we have been developing a middleware system called GATES (Grid-based AdapTive Execution on Streams). Our target applications are those involving high volume data streams and requiring distributed processing of data arising from a distributed set of sources.
 This paper addresses the problem of resource allocation in the GATES system. Though resource discovery and resource allocation have been active topics in grid community, the pipelined processing and real-time constraint required by distributed streaming applications pose new challenges. We present a resource allocation algorithm that is based on minimal spanning trees. We evaluate the algorithm experimentally and demonstrate that it results in configurations that are very close to optimal, and significantly better than most other possible configurations.
22490692
Aligning Multiple Protein Structures by Deterministic Annealing
Protein structure alignment plays a key role in protein structure prediction and fold family classification. An efficient method for multiple protein structure alignment in a mathematical manner is presented, based on deterministic annealing technique. The alignment problem is mapped onto a nonlinear continuous optimization problem (NCOP) with common consensus chain, matching assignment matrices and atomic coordinates as variables. At each step in the annealing procedure, the NCOP is decomposed into as many sub-problems as the number of protein chains, each of which is actually an independent pairwise structure alignment between a protein chain and the consensus chain and hence can be efficiently solved by the parallel computation technique. The proposed method is robust with respect to choice of iteration parameters for a wide range of proteins, and performs well in both multiple and pairwise structure alignment cases, compared with existing alignment methods.
9822806
Wavelet-based optical flow estimation
In this paper, a new algorithm for accurate optical flow estimation using discrete wavelet approximation is proposed. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately represent "things", to model optical flow vectors and image related functions. Each flow vector and image function are represented by linear combinations of wavelet basis functions. From such wavelet-based approximation, the leading coefficients of these basis functions carry the global information of the approximated "things". The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of wavelet coefficients. Once all the corresponding coefficients are decided, the flow vectors can be determined accordingly. Experiments conducted on both synthetic and real image sequences show that our approach outperformed the existing methods in terms of accuracy.