A methodology for maintaining trust in virtual environments

The increasing interest in carrying out business in virtual environments has resulted in much research and discussion of trust establishment between the entities involved. Researchers over the years have acknowledged that the success of any transaction or interaction via the virtual medium is determined by the trust level between trusting agent and trusted agent. Numerous publications have attempted to address the various challenges of assigning a trust level and building trust in an interacting party. However, the building and allocating a value of trust is neither easy nor quick. It involves high cost and effort. Hence, the ensuing research challenge is how to maintain the trust that has been established and assigned. Due to the dynamic nature of trust, the trust evolution, and the fragility of trust in virtual environments, one of the most pressing challenges facing the research community is how trust can be maintained over time. This thesis is an effort in that direction. Specifically, the objective of this thesis is to propose a methodology for trust maintenance in virtual environments which we term “Trust Maintenance Methodology” (TMM). The methodology comprises five frameworks that can be used to achieve the objective of trust maintenance.In order to achieve the aforesaid objective, this thesis proposes a: (a) Framework for third party agent selection, (b) Framework for Formalization and Negotiation of service requirements, (c) Framework for Proactive Continuous Performance Monitoring, (d) Framework for Incentive Mechanism, and (e) Framework for Trust Re-calibration.The framework for third party agent selection is used for choosing and selecting a neutral agent who will supervise the interaction between two parties. This is the first step of our methodology. The neutral agent is involved throughout the course of the interaction between two parties and takes a proactive-corrective role in continuous performance monitoring. Once both parties have chosen a neutral agent, they carry out a formalization and negotiation process of their service requirements using our proposed framework. This is in order to create an SLA which will guide the interaction between two parties. The framework for proactive continuous performance monitoring then can be used to evaluate the performance of both parties in delivering their service based on the SLA. If a performance gap occurs during the course of transaction, the third party agent will take action to help both parties close the performance gap in a timely manner. A key salient feature of our continuous performance monitoring is that it is proactive-corrective. Additionally, we design a framework for providing an incentive during the course of interaction to motivate both parties to perform as closely as possible to the terms of the mutual agreement or SLA. By the end of the interaction time space, both parties will be able to re-assess or re-calibrate their trust level using our proposed framework for trust re-calibration.Finally, in order to validate our proposed methodology, we engineered a multi-agent system to simulate the validity of the TMM. Numerous case studies are presented to elucidate the workings of our proposed methodology. Moreover, we run several experiments under various testing conditions including boundary conditions. The results of experiments show that our methodology is effective in assisting the parties to maintain their trust level in virtual environments

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

A collaborative citizen science platform for real-time volunteer computing and games

Volunteer computing (VC) or distributed computing projects are common in the citizen cyberscience (CCS) community and present extensive opportunities for scientists to make use of computing power donated by volunteers to undertake large-scale scientific computing tasks. Volunteer computing is generally a non-interactive process for those contributing computing resources to a project whereas volunteer thinking (VT) or distributed thinking, which allows volunteers to participate interactively in citizen cyberscience projects to solve human computation tasks. In this paper we describe the integration of three tools, the Virtual Atom Smasher (VAS) game developed by CERN, LiveQ, a job distribution middleware, and CitizenGrid, an online platform for hosting and providing computation to CCS projects. This integration demonstrates the combining of volunteer computing and volunteer thinking to help address the scientific and educational goals of games like VAS. The paper introduces the three tools and provides details of the integration process along with further potential usage scenarios for the resulting platform.Comment: 12 pages, 13 figure

A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201