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

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

Incentive Mechanism Design in Mobile Crowdsensing Systems

In the past few years, the popularity of Mobile Crowdsensing Systems (MCSs) has been greatly prompted, in which sensory data can be ubiquitously collected and shared by mobile devices in a distributed fashion. Typically, a MCS consists of a cloud platform, sensing tasks, and mobile users equipped with mobile devices, in which the mobile users carry out sensing tasks and receive monetary rewards as compensation for resource consumption ( e.g., energy, bandwidth, and computation) and risk of privacy leakage ( e.g., location exposure). Compared with traditional mote-class sensor networks, MCSs can reduce the cost of deploying specialized sensing infrastructures and enable many applications that require resources and sensing modalities beyond the current mote-class sensor processes as today’s mobile devices (smartphones (iPhones, Sumsung Galaxy), tablets (iPad) and vehicle-embedded sensing devices (GPS)) integrate more computing, communication, and storage resources than traditional mote-class sensors. The current applications of MCSs include traffic congestion detection, wireless indoor localization, pollution monitoring, etc . There is no doubt that one of the most significant characteristics of MCSs is the active involvement of mobile users to collect and share sensory data. In this dissertation, we study the incentive mechanism design in mobile crowdsensing system with consideration of economic properties. Firstly, we investigate the problem of joining sensing task assignment and scheduling in MCSs with the following three considerations: i) partial fulfillment, ii) attribute diversity, and iii) price diversity. Then, we design a distributed auction framework to allow each task owner to independently process its local auction without collecting global information in a MCS, reducing communication cost. Next, we propose a cost-preferred auction scheme (CPAS) to assign each winning mobile user one or more sub- working time durations and a time schedule-preferred auction scheme (TPAS) to allocate each winning mobile user a continuous working time duration. Secondly, we focus on the design of an incentive mechanism for an MCS to minimize the social cost. The social cost represents the total cost of mobile devices when all tasks published by the MCS are finished. We first present the working process of a MCS, and then build an auction market for the MCS where the MCS platform acts as an auctioneer and users with mobile devices act as bidders. Depending on the different requirements of the MCS platform, we design a Vickrey-Clarke-Groves (VCG)-based auction mechanism for the continuous working pattern and a suboptimal auction mechanism for the discontinuous working pattern. Both of them can ensure that the bidding of users are processed in a truthful way and the utilities of users are maximized. Through rigorous theoretical analysis and comprehensive simulations, we can prove that these incentive mechanisms satisfy economic properties and can be implemented in reasonable time complexcity. Next, we discuss the importance of fairness and unconsciousness of MCS surveillance applications. Then, we propose offline and online incentive mechanisms with fair task scheduling based on the proportional share allocation rules. Furthermore, to have more sensing tasks done over time dimension, we relax the truthfulness and unconsciousness property requirements and design a (ε, μ)-unconsciousness online incentive mechanism. Real map data are used to validate these proposed incentive mechanisms through extensive simulations. Finally, future research topics are proposed to complete the dissertation

A Dynamic Spectrum Access Framework (Bring Your Own Spectrum)

In this thesis, a unified and sustainable framework for spectrum allocation is presented. This multi-level operator-agnostic framework, Bring Your Own Spectrum (BYOS), is the result of a few thought experiments reflecting the ways in which spectrum could be bought and sold as an asset, similar to service models in cloud computing where every technical element can be traded via an "as-a-Service" model. BYOS architectural features form the major part of this thesis and cover four levels of abstraction as – contextual, conceptual, logical and physical. First, the contextual aspect of BYOS is covered, which addresses the question: "why is the framework needed?". To understand the reasons behind the need for a new framework an exhaustive survey of history of telecommunications policy development of 32 countries was conducted that included major economies in several key regions of the world. This research provided insight into the role of the government, mechanisms used for allocations, success/failure of allocations, and business models in the sector. Additionally, a review of existing and emerging technologies was done to understand various possible mechanisms of spectrum access. Next, the conceptual aspect of BYOS is presented, which addresses the question: "what does the framework look like?". For this, the information from the study above was converted into a skeleton framework, ensuring that it covers the requirements gathered. The framework has a three-level architecture with a quasi-static allocation scheme. The levels of architecture are designated based on periods of ownership and the thesis presents an original exponential-based-scale to determine the allocation periods (longest to shortest). The framework accommodates different types of operators, categorising in terms of their spectrum access privileges. Following this, the thesis focuses on the physical level of the framework, where the question: "with what?" i.e. the technical mechanisms are discussed. In this part, a novel analogy is presented where the wireless spectrum is compared to a multi-lane, multi-level highway. This analogy provides the basis for unit of information transport between two points, which in turn form the trading unit. In this thesis, "Interference (transmission power) spread over bandwidth" is chosen as the basic trading unit for the BYOS framework. Also included is a discussion on the required changes to the calculation of "population" – an inherent part of reserve price calculation – in view of the proliferation of device using different types of mobile technologies. A second part of the physical framework presents an original mechanism for competition management in view of the new framework and trading unit. Using the principles of network traffic management, a new tracking unit – token – is introduced, which helps the regulators keep track of the process of spectrum allocation, but in a hands-off manner. Multiple models of using tokens in the framework are presented. Tokens are intended only for the shortterm trades, though the initial number is determined by the total spectrum acquisitions and cumulative participation behaviour. Finally, the logical or system model of the framework is presented, which addresses the question: "how to structure and organise the architecture to achieve the desired requirements". This discussion is also divided into two parts. First, the discussion focuses on the multiple ways to use tokens and demonstrates the different use cases by way of competition games. Key novel points here are the discussion of competition management over multi-period allocation and addressing the needs of public safety services. Additionally, the discussion also focuses on unequal desirability of available spectrum lots based on spectrum characteristics, acquisition periods, and operator’s own requirements. The second part of the discussion focuses on various methods of implementation of this framework. A potential enterpriseblockchain based method is explored, though there may be other better solutions. Another focus of this thesis, which can be considered as a separate minor segment, came out of the initial policy research was to organize and analyse this information systematically. For this purpose, the theory of policy diffusion was explored, and the research provides evidence for the existence of, and analyses the mechanisms used for policy diffusion in different regions and countries.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronics, 202

Applying Secure Multi-party Computation in Practice

In this work, we present solutions for technical difficulties in deploying secure multi-party computation in real-world applications. We will first give a brief overview of the current state of the art, bring out several shortcomings and address them. The main contribution of this work is an end-to-end process description of deploying secure multi-party computation for the first large-scale registry-based statistical study on linked databases. Involving large stakeholders like government institutions introduces also some non-technical requirements like signing contracts and negotiating with the Data Protection Agency

Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution

Enabled by the connected and automated vehicle (CAV) technology, cooperative truck platooning that offers promising energy savings is likely to be implemented soon. However, as the trucking industry operates in a highly granular manner so that the trucks usually vary in their operation schedules, vehicle types and configurations, it is inevitable that 1) the spontaneous platooning over a spatial network is rare, 2) the total fuel savings vary from platoon to platoon, and 3) the benefit achieved within a platoon differs from position to position, e.g., the lead vehicle always achieves the least fuel-saving. Consequently, trucks from different owners may not have the opportunities to platoon with others if no path coordination is performed. Even if they happen to do so, they may tend to change positions in the formed platoons to achieve greater benefits, yielding behaviorally unstable platoons with less energy savings and more disruptions to traffic flows. This thesis proposes a hierarchical modeling framework to explicate the necessitated strategies that facilitate cooperative truck platooning. An empirical study is first conducted to scrutinize the energy-saving potentials of the U.S. national freight network. By comparing the performance under scheduled platooning and ad-hoc platooning, the author shows that the platooning opportunities can be greatly improved by careful path planning, thereby yielding substantial energy savings. For trucks assembled on the same path and can to platoon together, the second part of the thesis investigates the optimal platoon formation that maximizes total platooning utility and benefits redistribution mechanisms that address the behavioral instability issue. Both centralized and decentralized approaches are proposed. In particular, the decentralized approach employs a dynamic process where individual trucks or formed platoons are assumed to act as rational agents. The agents decide whether to form a larger, better platoon considering their own utilities under the pre-defined benefit reallocation mechanisms. Depending on whether the trucks are single-brand or multi-brand, whether there is a complete information setting or incomplete information setting, three mechanisms, auction, bilateral trade model, and one-sided matching are proposed. The centralized approach yields a near-optimal solution for the whole system and is more computationally efficient than conventional algorithms. The decentralized approach is stable, more flexible, and computational efficient while maintaining acceptable degrees of optimality. The mechanisms proposed can apply to not only under the truck platooning scenario but also other forms of shared mobility.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163047/1/xtsun_1.pd

To boldly go:an occam-π mission to engineer emergence

Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances. This paper describes a process-oriented architecture for fine-grained concurrent systems that enables experiments with such indirect engineering. Examples are presented showing the differing complex behaviours that can arise from minor (non-linear) adjustments to low-level parameters, the difficulties in suppressing the emergence of unwanted (bad) behaviour, the unexpected relationships between apparently unrelated physical phenomena (shown up by their separate emergence from the same primordial process swamp) and the ability to explore and engineer completely new physics (such as force fields) by their emergence from low-level process interactions whose mechanisms can only be imagined, but not built, at the current time