40677929
Use of multi-attribute decision analysis for designing operations system framework in telecommunications management network
Abstract This paper is concerned with the design of an Operations System (OS) framework for implementing a proper telecommunications network in Korea Telecom. Since several types of OS frameworks are under consideration, the telecommunication network manager should now choose the best alternative for use later in establishing the infrastructure of operations systems. The decision making is done in this paper by means of a Multi-Attribute Decision-Making (MADM) analysis. A point to be noted in the present case is that the decision relevant information such as attribute weights and values of alternatives are not known exactly. Rather, these are to be taken in the form of rankings and/or bounds. To deal with such incomplete information, we employ a mathematical programming model-based MADM approach to the choice of an optimal OS framework design. This approach enables us to check dominance of alternatives and to obtain a set of non-dominated alternatives from evaluating five alternatives in reference to Telecommunications Management Network (TMN) standards. Scope and purpose Telecommunications Management Network (TMN) can be stated as a globalized and unified skeleton to meet the advanced operational environments of telecommunications networks and to handle heterogeneous and complex network elements. Although there are various subjects that should be addressed to accomplish TMN, we confine our attention to dealing with one important subject, design of an Operations System (OS) framework. This is necessary to manage telecommunications resources including networks in effective manner and for use as guidance in developing individual operations systems and in constructing a network management center. Several types of OS frameworks have been suggested by TMN standards. It is hence needed to evaluate each of these OS frameworks and then to choose an appropriate one in Korean TMN situation. Since this evaluation involves multiple criteria (or attributes), it is realized in this paper by a Multi-Attribute Decision-Making (MADM) analysis approach. The decision relevant information such as trade-off weights and individual criterion values are elicited from expert opinions which, however, is rather incomplete than exact numerical values. The decision making process with the incompletely identified information is presented in this paper.
46325531
A utility range-based interactive group support system for multiattribute decision making
Abstract This research suggests an interactive procedure for solving a multiattribute group decision problem using a range-typed utility information, and develops an interactive group support system (RINGS) to implement some capabilities of the procedure. It is often difficult for group members to articulate their preferences with cardinal values, instead they prefer to give incomplete information only. Utility ranges are obtained by solving linear programming problems with incompletely specified information. RINGS finds out conflicting opinions among group members, compares each member's preferences with the others’, and suggests a direction for consensus seeking. The procedure of RINGS utilizes range-typed visual information, which helps the group reach a consensus. RINGS has several facilities like graphic user interface, model base, and database, so the total time to reach a group consensus is reduced. The evaluation of information systems is illustrated as a demonstration of some capabilities of RINGS. Scope and purpose This paper deals with the multiple attribute decision-making problem using a separable linear programming technique when group decision makers give only their incomplete information about the attribute weight and alternative value. The utility range for individual decision maker is calculated from each decision maker's incomplete information, and the utility range for group decision makers is obtained from those of individual decision makers. An interactive procedure for establishing a group's pairwise dominance relations with a group's utility range is described, and an interactive group support system (RINGS) is developed to implement the procedure. A case study about the evaluation of information systems is illustrated as a demonstration of some capabilities of RINGS.
1972714
Fast color image processing using quantized color instruction set
The paper describes the Quantized Color Pack eXtension (QCPX) instruction set that can accelerate color-image processing applications. QCPX employs heterogeneous-subword-parallel instructions, which utilize the microprocessor's 16-bit wide datapaths to process a packed, quantized 16-bit color data type in YCbCr (Y: luminance, Cr and Cb: chrominance) format in parallel. Unlike typical multimedia instruction set extensions (e.g. MMX, SSE, ALTIVEC), QCPX obtains performance and code density improvements through implicit support for color pixel processing rather than depending solely upon generic subword parallelism. Five time-critical color image processing algorithms are coded with and without QCPX to fully measure its impact upon programming techniques. Simulation results indicate that the applications using QCPX achieve significant speedups in execution time over non-QCPX. In addition, QCPX results in higher system utilization (in excess of 94% in all cases) due to significant reduction of conditional instructions.
1231793
An effective data clustering measure for temporal selection and projection queries
Abstract Temporal databases (TDBs) allow users to record and retrieve time-varying data objects. Since TDBs usually manage a huge amount of underlying data objects, efficient disk accesses are essential for fast response time in temporal query processing. Data clustering is one of the most effective techniques that can improve performance of TDB systems. However, clustering measures for conventional data objects are not appropriate to temporal data objects because it is important to exploit temporal properties of underlying data objects and temporal queries as data clustering criteria. In this paper, we propose a data clustering measure called temporal affinity that can be used for effective temporal data clustering. The temporal affinity, which is based on the semantics of temporal operators, reflects the closeness among temporal data objects with respect to temporal query processing. We perform experiments to show the effectiveness of the proposed temporal data clustering measure. The experimental results indicate that a data clustering method based on the temporal affinity works better than other methods.
10063692
Supporting plan authoring and analysis
Interactive tools to help users author plans or processes are essential in a variety of domains. KANAL helps users author sound plans by simulating them, checking for a variety of errors and presenting the results in an accessible format that allows the user to see an overview of the plan steps or timelines of objects in the plan. From our experience in two domains, users tend to interleave plan authoring and plan checking while extending background knowledge of actions. This has led us to refine KANAL to provide a high-level overview of plans and integrate a tool for refining the background knowledge about actions used to check plans. We report on these lessons learned and new directions in KANAL.
35666646
A Linguistics-Based Approach for Use Case Driven Analysis Using Goal and Scenario Authoring
Although Use Case driven analysis has been widely used in requirements analysis, it does not facilitate effective requirements elicitation or provide rationale for the various artifacts that get generated. On the other hand, goal and scenario based approach is considered to be effective for elicitation but it does not lead to use cases. This paper discusses how to combine goal and scenario based requirements elicitation technique with use case driven analysis using natural language concepts. In our proposed approach, four levels of goals, scenario authoring rules, and linguistic techniques have been developed to identify use cases from text based goal and scenario descriptions. The artifacts resulting from our approach could be used as input to a use case diagramming tool to automate the process of use case diagram generation.
2562587
Creating a Robust Desktop Grid using Peer-to-Peer Services
The goal of the work described in this paper is to design and build a scalable infrastructure for executing grid applications on a widely distributed set of resources. Such grid infrastructure must be decentralized, robust, highly available, and scalable, while efficiently mapping application instances to available resources in the system. However, current desktop grid computing platforms are typically based on a client-server architecture, which has inherent shortcomings with respect to robustness, reliability and scalability. Fortunately, these problems can be addressed through the capabilities promised by new techniques and approaches in peer-to-peer (P2P) systems. By employing P2P services, our system allows users to submit jobs to be run in the system and to run jobs submitted by other users on any resources available in the system, essentially allowing a group of users to form an ad-hoc set of shared resources. The initial target application areas for the desktop grid system are in astronomy and space science simulation and data analysis.