Engineering Crowdsourced Stream Processing Systems

A crowdsourced stream processing system (CSP) is a system that incorporates crowdsourced tasks in the processing of a data stream. This can be seen as enabling crowdsourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ human intelligence. It also leads to a substantial expansion of the capabilities of data processing systems. Engineering a CSP system requires the combination of human and machine computation elements. From a general systems theory perspective, this means taking into account inherited as well as emerging properties from both these elements. In this paper, we position CSP systems within a broader taxonomy, outline a series of design principles and evaluation metrics, present an extensible framework for their design, and describe several design patterns. We showcase the capabilities of CSP systems by performing a case study that applies our proposed framework to the design and analysis of a real system (AIDR) that classifies social media messages during time-critical crisis events. Results show that compared to a pure stream processing system, AIDR can achieve a higher data classification accuracy, while compared to a pure crowdsourcing solution, the system makes better use of human workers by requiring much less manual work effort

Integrating Security Risk Management into Business Process Management for the Cloud

Abstract-Security issues are still preventing wider adoption of cloud computing, especially for businesses which are handling sensitive information. Indeed, by outsourcing its information system (IS), a company can lose control over its infrastructure, its software or even its data. Therefore, new methods and tools need to be defined to respond to this challenge. In this paper we propose to integrate Security Risk Management approaches into Business Process Management to effectively treat security issues at the early phases of the Information System construction. We focus on cloud brokers, emerging actors of the cloud delivery model, who enhance and aggregate existing cloud services to match them with their cloud consumers' requirements. Our main goal is to provide them with tools and techniques to increase the global security level of an IS through different risk treatment strategies

A Prototype for an Agent-Based Electronic Contracting using an Organizational Model

The purpose of a contract, in a B2B context, is to establish an agreement in order to decrease risks associated with the interactions between trading partners. Humans currently carry manually out the business contract processes. This mainly includes the mechanisms of negotiation, signing, validation and monitoring. In order to improve the execution of the contracts with complex scenarios the use of Multi Agent System technologies is more appropriate. This paper describes a prototype implementing the concepts of Electronic Contract dedicated for Tele-services based on MOISE Inst, an organizational model for agents. This model aims to specify the rights and duties of agents in a society according to four points of view: structural, functional, contextual and normative. We use a real-world contract scenario as a test-bed for examining our e-contract architecture and for implementing our prototype. 1