17421892
Compiling real time functional reactive programming
Most of the past languages for reactive systems are based on synchronous dataflow. Recently, a new reactive language, called Real-Time Functional Reactive Programming (RT-FRP) [18] , has been proposed based on the functional paradigm. The unique feature of this language is the high-level abstraction provided in the form of behaviors for conti-nuous-time signals, and events for discrete-time signals. RT-FRP also features some performance guarantees in the form of bounded runtime and space usage for each reactive computation step.In this paper, we propose a new compilation scheme for RT-FRP. Our compilation scheme is based on two key stages. In the first stage, we translate RT-FRP program to an intermediate functional code. This code is deliberately kept at high level for two reasons. First, it is easier for us to validate its correctness. Second, it allows us to apply high-level source-to-source transformation to achieve further optimization. The second stage attempts to compile the intermediate code to a corresponding automata code. Our main novelty is the use of two high-level transformation techniques for this compilation. The first technique, partial evaluation, attempts to propagate constant values (wherever feasible) in order to perform more aggressive specialization. The second technique, tupling, combines mutually dependent automata together into a composite automaton whenever possible. Both techniques are needed for generating fast target code for RT-FRP.
16692811
PType System: A Featherweight Parallelizability Detector
Parallel programming is becoming an important cornerstone of general computing. In addition, type systems have significant impact on program analysis. In this paper, we demonstrate an automated type- based system that soundly detects parallelizability of sequential func- tional programs. Our type inference system discovers the parallelizability property of a sequential program in a modular fashion, by exploring a ring structure among the program's operators. It handles self-recursive functions with accumulating parameters, as well as a class of non-linear mutual-recursive functions. Programs whose types are inferred to be par- allelizable can be automatically transformed to parallel code in a mutu- morphic form - a succint model for parallel computation. Transforming into such a form is an important step towards constructing efficient data parallel programs.
37194320
The evidential reasoning approach for multi-attribute decision analysis under interval uncertainty
Abstract The evidential reasoning (ER) approach is a method for multiple attribute decision analysis (MADA) under uncertainties. It improves the insightfulness and rationality of a decision making process by using a belief decision matrix (BDM) for problem modelling and the Dempster–Shafer (D–S) theory of evidence for attribute aggregation. The D–S theory provides scope and flexibility to deal with interval uncertainties or local ignorance in decision analysis, which is not explored in the original ER approach and will be investigated in this paper. Firstly, interval uncertainty will be defined and modelled in the ER framework. Then, an extended ER algorithm, IER, is derived, which enables the ER approach to deal with interval uncertainty in assessing alternatives on an attribute. It is proved that the original ER algorithm is a special case of the IER algorithm. The latter is demonstrated using numerical examples.
205336
A strategy for persistent object service under CORBA and Web environment
With the rapid development of the Internet, the integrated applications of Web, database, CORBA and Java have offered the three-tiered client/server application models a good computing environment and implementation strategy. This paper briefly introduces this kind of client/server application model based on CORBA and Web, and discusses a persistent object service for it. The paper describes in detail the persistent object service's architecture model, interactive process of components, main interface descriptions and some considerations when implementing this strategy. Finally, a summary is supplied for the persistent object service.
7047265
Privacy-preserving alert correlation: a concept hierarchy based approach
With the increasing security threats from infrastructure attacks such as worms and distributed denial of service attacks, it is clear that the cooperation among different organizations is necessary to defend against these attacks. However, organizations' privacy concerns for the incident and security alert data require that sensitive data be sanitized before they are shared with other organizations. Such sanitization process usually has negative impacts on intrusion analysis (such as alert correlation). To balance the privacy requirements and the need for intrusion analysis, we propose a privacy-preserving alert correlation approach based on concept hierarchies. Our approach consists of two phases. The first phase is entropy guided alert sanitization, where sensitive alert attributes are generalized to high-level concepts to introduce uncertainty into the dataset with partial semantics. To balance the privacy and the usability of alert data, we propose to guide the alert sanitization process with the entropy or differential entropy of sanitized attributes. The second phase is sanitized alert correlation. We focus on defining similarity functions between sanitized attributes and building attack scenarios from sanitized alerts. Our preliminary experimental results demonstrate the effectiveness of the proposed techniques
15521655
An ultra-fast shared path protection scheme - distributed partial information management, part II
For pt.I see Chunming Qiao and Dahai Xu, INFOCOM'02, p.302-11, (2002). This paper describes a novel, ultra-fast heuristic algorithm to address an NP-hard optimization problem. One of its significances is that, for the first time, it is shown that a heuristic algorithm can also have better overall performance than its time-consuming, integer linear programming (ILP) based counterparts in the online case, which is non-intuitive. The proposed heuristic algorithm is useful for developing effective shared path (mesh) protection schemes that establish survivable connections in modern networks. The advantage of our heuristic algorithm over existing algorithms for finding a pair of link (or node) disjoint paths, active path (AP) and backup path (BP), comes from the following salient feature. It uses a so-called potential backup cost (PBC) function when selecting an AP in the first phase, in order to take into consideration the backup bandwidth needed by the corresponding BP yet to be chosen in the second phase. The PBC function is derived mathematically based on a rigorous statistical analysis of experimental data. While the use of PBC only requires partial aggregate information on existing connections and distributed control, it can also be applied even more effectively when complete information is available.
887820
A computational method for assessing peptide-identification reliability in tandem mass spectrometry analysis with SEQUEST
High throughput protein identification in mass spectrometry is predominantly achieved by first identifying tryptic peptides using SEQUEST and then by combining the peptide hits for protein identification. Peptide identification is typically carried out by selecting SEQUEST hits above a specified threshold, the value of which is typically chosen empirically in an attempt to separate true identifications from the false ones. These SEQUEST scores are not normalized with respect to the composition, length and other parameters of the peptides. Furthermore, there is no rigorous reliability estimate assigned to the protein identifications derived from these scores. Hence the interpretation of SEQUEST hits generally requires human involvement, making it difficult to scale up the identification process for genome-scale applications. To overcome these limitations, we have developed a method, which combines a neural network and a statistical model, for "normalizing" SEQUEST scores, and also for providing a reliability estimate for each SEQUEST hit. This method improves the sensitivity and specificity of peptide identification compared to the standard filtering procedure used in the SEQUEST package, and provides a basis for estimating the reliability of protein identifications.