This paper presents SemAnt, a novel ant-based multi-agent system designed for distributed query routing. While the ant metaphor has been successfully applied to network routing both in wireless and fixed networks, lit...
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This paper presents SemAnt, a novel ant-based multi-agent system designed for distributed query routing. While the ant metaphor has been successfully applied to network routing both in wireless and fixed networks, little is yet known about its applicability to the task of query routing in distributed environments. We point out the similarities and dissimilarities between routing of data packets and routing of queries, and we present the design of SemAnt, which is based on the ant colony optimization meta-heuristic. For experimental evaluation, we deploy the algorithm in a peer-to-peer environment with a real-world application scenario and compare its performance against the well-known k-random walker approach. As we show, the benefits of SemAnt are that the routes for queries are optimized according to their popularity, and that the algorithm is highly suitable for volatile environments
Customer data privacy is known to be a factor which makes just-in-time data sharing and mining among enterprises challenging. Learning-from-abstraction is a recently proposed paradigm for privacy preserving distribute...
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Customer data privacy is known to be a factor which makes just-in-time data sharing and mining among enterprises challenging. Learning-from-abstraction is a recently proposed paradigm for privacy preserving distributed data mining where distributed local data sources are protected by probabilistic data abstraction. In this paper, we investigate the use of a normalized negative log likelihood together with the paradigm for quantifying the level of privacy protection, and studied theoretically the change of the privacy levels of the local data abstractions after being aggregated for global data analysis. Experiments on distributed data clustering with a synthetic data set were conducted on a service-oriented BPEL platform. The promising results obtained demonstrates the effectiveness of the adopted privacy measure
In this paper, we present the design and implementation of and interdisciplinary research project involving an intelligent agent-based framework for collaborative e-commerce applications. A multi-agent system (MAS) ar...
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In this paper, we present the design and implementation of and interdisciplinary research project involving an intelligent agent-based framework for collaborative e-commerce applications. A multi-agent system (MAS) architecture for large collaborative e-commerce environments is designed and developed, where a number of geographically dispersed users (customers/merchants) can participate. This architecture not only applies agent technologies in e-commerce system in novel manners, but also incorporates privacy law and legislation into its technical design, and in that respect it is different from other existing e-commerce systems
Economic resource allocation in application layer networks (such as grids) is critical to allow applications and users to effectively exploit computational and data infrastructures like service-oriented computing as a...
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Economic resource allocation in application layer networks (such as grids) is critical to allow applications and users to effectively exploit computational and data infrastructures like service-oriented computing as a utility. Thus, the evaluation of resource allocation strategies plays a major part in the selection of a resource allocation method. This paper presents an evaluation framework for resource allocation methods in application layer networks, that aims at supporting both a technical and an economic evaluation. The presented evaluation model shows a layered metrics pyramid with different aggregation levels. Statistical methods are used to describe this pyramid. On top of the pyramid, one single number, the social utility, is able to characterize an economic resource allocation method. This number may serve to compare different resource allocation strategies
Trust is an essential component for secure collaboration in uncertain environments. Trust management can be used to reason about future interactions between entities. In reputation-based trust management, an entity...
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ISBN:
(纸本)354038619X
Trust is an essential component for secure collaboration in uncertain environments. Trust management can be used to reason about future interactions between entities. In reputation-based trust management, an entity's reputation is usually built on ratings from those who have had direct interactions with the entity. In this paper, we propose a Bayesian network based trust management model. In order to infer trust in different aspects of an entity's behavior, we use multidimensional application specific trust values and each dimension is evaluated using a single Bayesian network. This makes it easy both to extend the model to involve more dimensions of trust and to combine Bayesian networks to form an opinion about the overall trustworthiness of an entity. Each entity can evaluate his peers according to his own criteria. The dynamic characteristics of criteria and of peer behavior can be captured by updating Bayesian networks. Risk is explicitly combined with trust to help users making decisions. In this paper, we show that our system can make accurate trust inferences and is robust against unfair raters.
In position-based routing algorithms for ad-hoc networks, the nodes use the geographical information to make the routing decisions. Recent research in this field primarily addresses such routing algorithms in two dime...
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ISBN:
(纸本)9781424404988
In position-based routing algorithms for ad-hoc networks, the nodes use the geographical information to make the routing decisions. Recent research in this field primarily addresses such routing algorithms in two dimensional space (W). However, in real applications, nodes may be distributed in 3D space. In this paper we extend previous randomized routing algorithms from 2D space to 3D space, and we propose two new position-based routing algorithms that combine randomized AB3D routing algorithms with a deterministic CFace (coordinate face) algorithm. The first algorithm AB3D-CFace(1)-AB3D starts with AB3D routing algorithm until a local minimum is reached. The algorithm then switches to CFace routing using one projected coordinate. If CFace(1) enters a loop, the algorithm switches back to AWD. The second algorithm AWD-CFace(3) starts with AWD, until a local minimum is reached. The algorithm then permanently switches to CFace routing using three projected coordinates, in order We evaluate our mechanisms and compare them with the current routing algorithms. The simulation results show the significant improvement in delivery rate over pure AB3D randomized routing (97% compared to 70%) and reduction in path dilation (up to 50%) overpure CFace algorithm.
Self-healing and self-optimizing service based applications are important steps towards the self-organizing service oriented architectures (SOA). Self-organizing SOAs replace services by functional equivalent services...
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Self-healing and self-optimizing service based applications are important steps towards the self-organizing service oriented architectures (SOA). Self-organizing SOAs replace services by functional equivalent services in the case of faults or in respect of quality of service. These features depend on automatic service discovery which provides service alternatives. We enter the WSC'06 contest to present a semantic service discovery system for large sets of services. A recursive algorithm builds service compositions by adding services in each iteration. The search works backwards, since we add services that produce a certain output regardless of its input parameters. A valid service composition produces a set of queried output parameters and input parameters necessary for the composed services. The algorithm is improved by using efficient data structures in our service composition system
Classical location-based services (LBSs) automatically derive the current location of known persons in order to select, compile, or filter location-dependent information and present it to their users. Zone services wo...
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Classical location-based services (LBSs) automatically derive the current location of known persons in order to select, compile, or filter location-dependent information and present it to their users. Zone services work the other way round: they estimate the amount of persons which are located in a given geographic zone and optionally obtain personal information from them in order to compile statistical information like the number of persons staying in a zone, their average age, and marital status. Zone services address a broad field of applications, ranging from emergency services to mobile marketing and research. This paper presents an approach for realizing such services by using broadcast technologies in combination with terminal-based positioning like GPS. Because data collected in this way always runs the risk of being misused, the paper also presents a framework that allows observed persons to define and enforce their privacy preferences
To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an algorithm that (1) is flexible with respect to the outlier definition, (2) works in-network with a communication load...
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To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an algorithm that (1) is flexible with respect to the outlier definition, (2) works in-network with a communication load proportional to the outcome, and (3) reveals its outcome to all sensors. We examine the algorithm’s performance using simulation with real sensor data streams. Our results demonstrate that the algorithm is accurate and imposes a reasonable communication load and level of power consumption.
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