67,713 research outputs found
An empirical learning-based validation procedure for simulation workflow
Simulation workflow is a top-level model for the design and control of
simulation process. It connects multiple simulation components with time and
interaction restrictions to form a complete simulation system. Before the
construction and evaluation of the component models, the validation of
upper-layer simulation workflow is of the most importance in a simulation
system. However, the methods especially for validating simulation workflow is
very limit. Many of the existing validation techniques are domain-dependent
with cumbersome questionnaire design and expert scoring. Therefore, this paper
present an empirical learning-based validation procedure to implement a
semi-automated evaluation for simulation workflow. First, representative
features of general simulation workflow and their relations with validation
indices are proposed. The calculation process of workflow credibility based on
Analytic Hierarchy Process (AHP) is then introduced. In order to make full use
of the historical data and implement more efficient validation, four learning
algorithms, including back propagation neural network (BPNN), extreme learning
machine (ELM), evolving new-neuron (eNFN) and fast incremental gaussian mixture
model (FIGMN), are introduced for constructing the empirical relation between
the workflow credibility and its features. A case study on a landing-process
simulation workflow is established to test the feasibility of the proposed
procedure. The experimental results also provide some useful overview of the
state-of-the-art learning algorithms on the credibility evaluation of
simulation models
Promises, Impositions, and other Directionals
Promises, impositions, proposals, predictions, and suggestions are
categorized as voluntary co-operational methods. The class of voluntary
co-operational methods is included in the class of so-called directionals.
Directionals are mechanisms supporting the mutual coordination of autonomous
agents.
Notations are provided capable of expressing residual fragments of
directionals. An extensive example, involving promises about the suitability of
programs for tasks imposed on the promisee is presented. The example
illustrates the dynamics of promises and more specifically the corresponding
mechanism of trust updating and credibility updating. Trust levels and
credibility levels then determine the way certain promises and impositions are
handled.
The ubiquity of promises and impositions is further demonstrated with two
extensive examples involving human behaviour: an artificial example about an
agent planning a purchase, and a realistic example describing technology
mediated interaction concerning the solution of pay station failure related
problems arising for an agent intending to leave the parking area.Comment: 55 page
Community-Based Security for the Internet of Things
With more and more devices becoming connectable to the internet, the number
of services but also a lot of threats increases dramatically. Security is often
a secondary matter behind functionality and comfort, but the problem has
already been recognized. Still, with many IoT devices being deployed already,
security will come step-by-step and through updates, patches and new versions
of apps and IoT software. While these updates can be safely retrieved from app
stores, the problems kick in via jailbroken devices and with the variety of
untrusted sources arising on the internet. Since hacking is typically a
community effort? these days, security could be a community goal too. The
challenges are manifold, and one reason for weak or absent security on IoT
devices is their weak computational power. In this chapter, we discuss a
community based security mechanism in which devices mutually aid each other in
secure software management. We discuss game-theoretic methods of community
formation and light-weight cryptographic means to accomplish authentic software
deployment inside the IoT device community
Quality of Information in Mobile Crowdsensing: Survey and Research Challenges
Smartphones have become the most pervasive devices in people's lives, and are
clearly transforming the way we live and perceive technology. Today's
smartphones benefit from almost ubiquitous Internet connectivity and come
equipped with a plethora of inexpensive yet powerful embedded sensors, such as
accelerometer, gyroscope, microphone, and camera. This unique combination has
enabled revolutionary applications based on the mobile crowdsensing paradigm,
such as real-time road traffic monitoring, air and noise pollution, crime
control, and wildlife monitoring, just to name a few. Differently from prior
sensing paradigms, humans are now the primary actors of the sensing process,
since they become fundamental in retrieving reliable and up-to-date information
about the event being monitored. As humans may behave unreliably or
maliciously, assessing and guaranteeing Quality of Information (QoI) becomes
more important than ever. In this paper, we provide a new framework for
defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the
current state-of-the-art on the topic. We also outline novel research
challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN
Moving Ideas and Money: Issues and Opportunities in Funder Funding Collaboration
Presents an overview of funder collaboratives, ranging from information exchange, co-learning, informal and formal strategic alignments to pooled funding, joint ventures, and hybrid networks. Discusses elements of success, outcomes, and challenges
Data centric trust evaluation and prediction framework for IOT
© 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas
Research on Trust Transfer of Heterogeneous Information Sharing Based on Infomediary
On the condition of G2B(Government to Business) inter-organizational information sharing, vertical information asymmetry takes up dominant position, especially the credit information asymmetry between banks and government departments. As infomediary between them in the case, credit reporting system is constructed to collect and process government information in China. This research discussed the trust transfer of heterogeneous information within credit reporting system using the method of the multiple mediation path analysis. The result shows trust on information source can transfer to the perceived information quality within credit infomediary directly, and its trust can also be transferred by mediators of relevance, completeness, timeliness and accuracy indirectly. This research will play an active role in academic contribution of inter-organizational heterogeneous information sharing
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