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

Optimizing the Lifetime of Sensor Networks with Uncontrollable Mobile Sinks and QoS Constraints

In past literature, it has been demonstrated that the use of mobile sinks (MSs) increases dramatically the lifetime of wireless sensor networks (WSNs). In applications where the MSs are humans, animals, or transportation systems, the mobility of the MSs is often uncontrollable and could also be random and unpredictable. This implies the necessity of algorithms tailored to handle uncertainty on the MS mobility. In this article, we define the lifetime optimization of a WSN in the presence of uncontrollable sink mobility and Quality of Service (QoS) constraints. After defining an ideal scheme (called Oracle) which provably maximizes network lifetime, we present a novel Swarm-Intelligence-based Sensor Selection Algorithm (SISSA), which optimizes network lifetime and meets predefined QoS constraints. Then we mathematically analyze SISSA and derive analytical bounds on energy consumption, number of messages exchanged, and convergence time. The algorithm is experimentally evaluated on practical experimental setups, and its performances are compared to that by the optimal Oracle scheme, as well as with the IEEE 802.15.4 MAC and TDMA schemes. Results conclude that SISSA provides on the average the 56% of the lifetime provided by Oracle and outperforms IEEE 802.15.4 and TDMA in terms of yielded network lifetime