Process Automation concentrates on automating structured processes of an organization in order to achieve excellent service delivery by enabling the employees to pay more attention to semi structured or unstructured p...
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We consider a security problem on a distributed network. We assume a network whose nodes are vulnerable to infection by threats (e.g. viruses), the attackers. A system security software, the defender, is available in ...
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Let M be a single s-t network of parallel links with load dependent latency functions shared by an infinite number of selfish users. This may yield a Nash equilibrium with unbounded Coordination ratio [12, 26]. A Lead...
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ISBN:
(纸本)1595934529
Let M be a single s-t network of parallel links with load dependent latency functions shared by an infinite number of selfish users. This may yield a Nash equilibrium with unbounded Coordination ratio [12, 26]. A Leader can decrease the coordination ratio by assigning flow αr on M, and then all Followers assign selfishly the (1 - α)r remaining flow. This is a Stackelberg Scheduling Instance (M, r, α), 0 ≤ α ≤ 1. It was shown [23] that it is weakly NP-hard to compute the optimal Leader's strategy. For any such network M we efficiently compute the minimum portion βM of flow r needed by a Leader to induce M's optimum cost, as well as his optimal strategy. Unfortunately, Stackelberg routing in more general nets can be arbitrarily hard. Roughgarden presented a modification of Braess's Paradox graph, such that no strategy controlling αr flow can induce ≤ 1/α times the optimum cost. However, we show that our main result also applies to any s-t net G. We take care of the Braess's graph explicitly, as a convincing example. Copyright 2006 ACM.
We consider the QoS-aware Multicommodity Flow problem, a natural generalization of the weighted multicommodity flow problem where the demands and commodity values are elastic to the Quality-of-Service characteristics ...
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ISBN:
(纸本)9783939897019
We consider the QoS-aware Multicommodity Flow problem, a natural generalization of the weighted multicommodity flow problem where the demands and commodity values are elastic to the Quality-of-Service characteristics of the underlying network. The problem is fundamental in transportation planning and also has important applications beyond the transportation domain. We provide a FPTAS for the QoS-aware Multicommodity Flow problem by building upon a Lagrangian relaxation method and a recent FPTAS for the non-additive shortest path problem.
This paper deals with a distributed bandwidth broker that we try to extend in order to perform inter-domain operation. The basic issues for inter-domain operation are discussed and we try to approach the most demandin...
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ISBN:
(纸本)1841021571
This paper deals with a distributed bandwidth broker that we try to extend in order to perform inter-domain operation. The basic issues for inter-domain operation are discussed and we try to approach the most demanding issues as the selection of the best inter domain routing path. Generally, we discuss three models for inter domain routing through bandwidth broker, analyzing their advantages. Also, a very important point that affects the interdomain operation is the SLAs between adjacent domains and the capability that a bandwidth broker should have to ask and perform dynamic negotiation. Finally, we analyze the best model and present how it should be incorporated in the existing distributed implementation.
We propose a simple and intuitive cost mechanism which assigns costs for the competitive usage of m resources by n selfish agents. Each agent has an individual demand;demands are drawn according to some probability di...
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We propose a simple and intuitive cost mechanism which assigns costs for the competitive usage of m resources by n selfish agents. Each agent has an individual demand;demands are drawn according to some probability di...
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The paper introduces an algorithm for personalized clustering based on a range tree structure, used for identifying all web documents satisfying a set of predefined personal user preferences. The returned documents go...
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ISBN:
(纸本)1595934537
The paper introduces an algorithm for personalized clustering based on a range tree structure, used for identifying all web documents satisfying a set of predefined personal user preferences. The returned documents go through a clustering phase before reaching the end user, thus allowing more effective manipulation and supporting the decision making process. The proposed algorithm demonstrates increased applicability in semantic web settings, since they offer the infrastructure for the explicit declaration of web document attributes and their respective values, thus allowing for more automated retrieval. The proposed algorithm improves the k-means range algorithm, as it uses the already constructed range tree (i.e. during the personalized filtering phase) as the basic structure on which the clustering step is based, applying instead of the k-means, the k-windows algorithm. The total number of parameters used for modeling the web documents dictates the number of dimensions of the Euclidean space representation. The time complexity of the algorithm is O(log d-2n+v), where d is the number of dimensions, n is the total number of web documents and v is the size of the answer. Copyright 2006 ACM.
In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic a...
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In this poster, we present an approach to contex-tualized semantic image annotation as an optimization problem. Ontologies are used to capture general and contextual knowledge of the domain considered, and a genetic algorithm is applied to realize the final annotation. Experiments with images from the beach vacation domain demonstrate the performance of the proposed approach and illustrate the added value of utilizing contextual information.
In this work Statistical Graphical Language Models (SGLMs), a technique adapted from Statistical Language Models (SLMs), are applied to the task of graphical object recognition. SLMs are used in Natural Language Proce...
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ISBN:
(纸本)9781932415957
In this work Statistical Graphical Language Models (SGLMs), a technique adapted from Statistical Language Models (SLMs), are applied to the task of graphical object recognition. SLMs are used in Natural Language Processing for tasks such as Speech Recognition and Information Retrieval. SGLMs view graphical objects as belonging to graphical languages and use this view to compute probabilistic distributions of graphical objects within graphical documents. SGLMs such as N-grams require large corpora of training data, which consist of graphical objects in contextual use (real world graphical documents). Constructing corpora is an important stage in developing the models and many issues need to be addressed. This paper discusses the development of graphical corpora and presents approaches to some of the problems encountered.
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