12111515
Algorithm of integrating QFD and TRIZ for the innovative design process
TRIZ, the Russian acronym of the Theory of Inventive Problem Solving, is a useful tool that can solve the problem of "how to do" effectively in the innovative design process, while QFD (Quality Function Deployment) is able to settle the problem of "what to do". Although the potential of using both QFD and TRIZ in the product design process is huge, there are little tools to integrate these two methods effectively. In this research, we describe an algorithm that can integrate QFD and TRIZ effectively for the purpose of the innovative design process. The core of the algorithm is to identify the contradictions in TRIZ by defining rules based on HOQ (House of Quality) in QFD. A software tool called TRIZmatrix is developed based on this algorithm. Application of the algorithm to the case of the airbag problem is studied in detail. The software application and the case study show the advantage of this algorithm for CAI (computer aided innovation) software development.
14513982
An Online Model Checking Tool for Safety and Liveness Bugs
Modern software model checkers are usually used to find safety violations. However, checking liveness properties can offer a more natural and effective way to detect errors, particularly in complex concurrent and distributed e-business systems. Specifying global liveness properties which should always eventually be true proves to be more desirable, but it is hard for existing software model checkers to verify liveness in real codes because doing so requires finding an infinite execution. For solving such a challenge, this paper proposes an online checking tool to verify the safety and liveness properties of complex systems. We adopt the linear temporal logic to describe the semantics of the finite model checking, use binary instrumentation to obtain the distribute states and apply a checking engine to dynamically verify the finite trace linear temporal logic properties. At last, we demonstrate the method in a distributed system using distributed protocol Paxos and achieve good results by experiments.
13862518
Low Cost Mechanism for QoS-Aware Re-Planning of Composite Service
To meet the business and user requirements, it is crucial to manage the Quality of Service (QoS) of composite web service. Due to the dynamics nature of the web services, the runtime behavior of web services is likely to differ from the initial estimated one. Therefore, a re-planning to adapt the composite service to the QoS violated services, ensuring the global constraints and preferences will be needed. In this paper, we propose a low cost mechanism for re-planning. Such mechanism is supported by an offline re-planning execution environment and a performance prediction based low cost policy.The experimentations show better performance of the mechanism.
15004157
A Semantic QoS-Aware Discovery Framework for Web Services
Augmenting web services with explicit semantics forms the foundation of Service Oriented Architectures (SOAs) automation. As more and more Semantic Web Services (SWSs) are deployed, similar SWSs could have quite different quality-of-service (QoS) levels. The QoS-aware discovery becomes an important challenge. While some efforts try to solve it via Constraint Programming (CP), they suffer from the purely syntactic matchmaking method. Furthermore, the construction of constraints and the selection of services are completely dependent on the literal translation from QoS descriptions, which increase obstacles to actually apply CP. In this paper, we propose a semantic QoS-aware framework for SWSs discovery by combining the semantic matchmaking and CP. Initially, a QoS ontology is presented to define QoS data into service descriptions. Then the ontology reasoning is adopted to change previous syntactic matchmaking into a semantic way. Through confirming the compatibility of concepts, complex QoS conditions are solved as constraints and a selection algorithm is proposed to obtain the optimal offer. Finally, the prototype implementation of our framework is discussed and a SWSs discovery case is used to illustrate the comprehensive discovery process.
5812455
Knowledge Enhanced IT Service Management
To manage the increasing complexity of IT systems and align IT services with business is the main theme of IT Service Management (ITSM). Current ITSM architecture adopts ITU as the framework to integrate silos of operational management tools and configuration information to build an end-to-end solution based on best practices. However, it lacks of a systematic means to address an important aspect of IT operation, i.e., managing the knowledge separated in various tools and experts' minds. In this paper, a novel knowledge-enhanced architecture is proposed to improve the effectiveness and efficiency of ITSM. The essential contribution of this novel architecture is to involve a Knowledge Management Database (KMDB) which provides assistance for knowledge capture, mining, storage and sharing. The paper will discuss an approach of how to construct such a KMDB with motivating scenarios and detailed description of key components. To validate the approach, a prototype system is developed and evaluated by being applied for problem analysis on a Cisco Voice over IP (VoIP) system. The experiment results show a remarkable improvement in the effectiveness and efficiency for practical IT service management operations.
10702245
A wireless LAN-based indoor positioning technology
Context-aware computing is an emerging computing paradigm that can provide new or improved services by exploiting user context information. In this paper, we present a wireless-local-area-network-based (WLAN-based) indoor positioning technology. The wireless device deploys a position-determination model to gather location information from collected WLAN signals. A model-based signal distribution training scheme is proposed to trade off the accuracy of signal distribution and training workload. A tracking-assistant positioning algorithm is presented to employ knowledge of the area topology to assist the procedure of position determination. We have set up a positioning system at the IBM China Research Laboratory. Our experimental results indicate an accuracy of 2 m with a 90% probability for static devices and, for moving (walking) devices, an accuracy of 5 m with a 90% probability. Moreover, the complexity of the training procedure is greatly reduced compared with other positioning algorithms.
206800753
Automatic character location and segmentation in color scene images
This paper describes a connected component (CC)-based approach to automatic text location and segmentation in natural scene images. A multi-group decomposition scheme is used to deal with the complexity of the color background. Connected component extraction is implemented using the block adjacency graph (BAG) algorithm after noise filtering and runlength smearing (RLS) operation. Some heuristic features and priority adaptive segmentation (PAS) of characters are proposed in block candidate verification and grayscale-based recognition. A prototype system is completed and the experimental results prove the effectiveness of the proposed method.
17038094
On-line Algorithm for Server Selection of Video Streaming over P2P Networks
Abstract We consider a video streaming application over P2Pnetworks and introduce the P2P on-line server selection problem. This task is related to the classic K-server problem, known from the theory of online algorithms. The difference is that our problem has a dynamic cost matrix, due to network congestion which may trigger the rerouting of streaming paths. With the assumption that the number of hops of any alternative path from the server node p to the requesting node q is at most δ times the number of hops of the shortest path from p to q, our dynamic work function algorithm works for the P2P on-line server selection problem with competitive ratio δ×(2k-1). 1. Introduction In this paper we consider a video streaming application over P2Pnetworks. As we know, it isdifficult to provide large scale streaming service using traditional, centralized client-serverarchitecture, since a bottleneck occurs at the server. The network service model known as Peer-to-Peer (P2P) solves this problem, due to its distributed nature. We address the issue of optimizing the server selection for video streaming in P2P networks.Optimization tasks are classified into online and offline problems. Optimization problems in which the input is received piece by piece and the corresponding piece of output must be produced before knowing the entire input are called online problems. In some optimization tasks, such as job scheduling, both the online and offline versions of the problem are meaningful. Many other situations, such as telephone circuit switching, investment planning etc. are intrinsically online. For these problems, offline algorithms are not acceptable. Competitive algorithms were introduced by Sleator and Tarjan [1] in the context of optimization problems. They sought a worst case complexity measure for on-line algorithms that have to make decisions based on current and previous parts of the input. In the on-line problem the input is given as a sequence σ = σ
36787117
Parallelizing Support Vector Machines on Distributed Computers
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability, we have developed a parallel SVM algorithm (PSVM), which reduces memory use through performing a row-based, approximate matrix factorization, and which loads only essential data to each machine to perform parallel computation. Let n denote the number of training instances, p the reduced matrix dimension after factorization (p is significantly smaller than n), and m the number of machines. PSVM reduces the memory requirement from O(n2) to O(np/m), and improves computation time to O(np2/m). Empirical study shows PSVM to be effective. PSVM Open Source is available for download at http://code.google.com/p/psvm/.
4407504
Optimal ISP subscription for Internet multihoming: algorithm design and implication analysis
Multihoming is a popular method used by large enterprises and stub ISPs to connect to the Internet to reduce cost and improve performance. Recently researchers have studied the potential benefits of multihoming and proposed protocols and algorithms to realize these benefits. They focus on how to dynamically select which ISPs to use for forwarding and receiving packets, and assume that the set of subscribed ISPs is given a priori. In practice, a user often has the freedom to choose which subset of ISPs among all available ISPs to subscribe to. We call the problem of how to choose the optimal set of ISPs the ISP subscription problem. In this paper, We design a dynamic programming algorithm to solve the ISP subscription problem optimally. We also design a more efficient algorithm for a large class of common pricing functions. Using real traffic traces and realistic pricing data, we show that our algorithm reduces users' cost. Next we study how ISPs respond to users' optimal ISP subscription by adjusting their pricing strategies. We call this problem the ISP pricing problem. Using a realistic charging model, we formulate the problem as a non-cooperative game. We first prove that if cost is the only criterion used by a user to determine which subset of ISPs to subscribe to, at any equilibrium all ISPs receive zero revenue. We then study a more practical formulation in which different ISPs provide different levels of reliability and users choose ISPs to both improve reliability and reduce cost. We analyze this problem and show that at any equilibrium an ISP's revenue is positive and determined by its reliability.
6306890
APPLE: A Novel P2P Based e-Learning Environment
With the rapid development of information technology, dramatic changes have been taken place in the fundamental ways that people acquire and disseminate knowledge. Various e-Learning systems have been designed to help people take full advantage of the benefit brought by the technology. The newly emerged Peer to Peer (P2P) and grid computing will serve as the key driven forces to bring revolutionary impact on the future society. This paper evaluates the potential contribution of the P2P and grid technology into the e-Learning system and introduces a novel P2P based e-Learning environment, called APPLE. With the help of Gnutella-like P2P network, APPLE provides live broadcasting services to share services of education resources. We build a virtual classroom service based on WSRF.NET, which exposes the service as a grid service that could be accessed by all the users among the grid.