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

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels. Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load. To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions. The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments. The proposed InterCloud environment supports scaling of applications across multiple vendor clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape

Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data

In the context of a myriad of mobile apps which collect personally identifiable information (PII) and a prospective market place of personal data, we investigate a user-centric monetary valuation of mobile PII. During a 6-week long user study in a living lab deployment with 60 participants, we collected their daily valuations of 4 categories of mobile PII (communication, e.g. phonecalls made/received, applications, e.g. time spent on different apps, location and media, photos taken) at three levels of complexity (individual data points, aggregated statistics and processed, i.e. meaningful interpretations of the data). In order to obtain honest valuations, we employ a reverse second price auction mechanism. Our findings show that the most sensitive and valued category of personal information is location. We report statistically significant associations between actual mobile usage, personal dispositions, and bidding behavior. Finally, we outline key implications for the design of mobile services and future markets of personal data.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2014

User-Centric Security and Privacy Mechanisms in Untrusted Networking and Computing Environments

Our modern society is increasingly relying on the collection, processing, and sharing of digital information. There are two fundamental trends: (1) Enabled by the rapid developments in sensor, wireless, and networking technologies, communication and networking are becoming more and more pervasive and ad hoc. (2) Driven by the explosive growth of hardware and software capabilities, computation power is becoming a public utility and information is often stored in centralized servers which facilitate ubiquitous access and sharing. Many emerging platforms and systems hinge on both dimensions, such as E-healthcare and Smart Grid. However, the majority information handled by these critical systems is usually sensitive and of high value, while various security breaches could compromise the social welfare of these systems. Thus there is an urgent need to develop security and privacy mechanisms to protect the authenticity, integrity and confidentiality of the collected data, and to control the disclosure of private information. In achieving that, two unique challenges arise: (1) There lacks centralized trusted parties in pervasive networking; (2) The remote data servers tend not to be trusted by system users in handling their data. They make existing security solutions developed for traditional networked information systems unsuitable. To this end, in this dissertation we propose a series of user-centric security and privacy mechanisms that resolve these challenging issues in untrusted network and computing environments, spanning wireless body area networks (WBAN), mobile social networks (MSN), and cloud computing. The main contributions of this dissertation are fourfold. First, we propose a secure ad hoc trust initialization protocol for WBAN, without relying on any pre-established security context among nodes, while defending against a powerful wireless attacker that may or may not compromise sensor nodes. The protocol is highly usable for a human user. Second, we present novel schemes for sharing sensitive information among distributed mobile hosts in MSN which preserves user privacy, where the users neither need to fully trust each other nor rely on any central trusted party. Third, to realize owner-controlled sharing of sensitive data stored on untrusted servers, we put forward a data access control framework using Multi-Authority Attribute-Based Encryption (ABE), that supports scalable fine-grained access and on-demand user revocation, and is free of key-escrow. Finally, we propose mechanisms for authorized keyword search over encrypted data on untrusted servers, with efficient multi-dimensional range, subset and equality query capabilities, and with enhanced search privacy. The common characteristic of our contributions is they minimize the extent of trust that users must place in the corresponding network or computing environments, in a way that is user-centric, i.e., favoring individual owners/users

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions