Reputation-based Energy Efficient Opportunistic Routing for Wireless Sensor Network

Selection of the best next-hop in Opportunistic Routing (OR) is a crucial task in wireless sensor networks (WSN). To increase the throughput, network lifetime and reliability of WSN, there is a need of an optimal OR protocol. To improve the reliability of network, reputation management is important. Reputation management gives a chance to nodes to transmit data on secure and reliable routes. This paper gives a new reputation based OR metric and protocol, in which the next hop selection is based on its reputation. The proposed OR metric considers the reputation level as a primary selection parameter for next-hop. New OR metric relies on energy efficiency and packet delivery ratio of next-hop. Proposed OR protocol selects all middle position neighbors as next-hop and potential forwarder will be decided on the basis of new OR metric. Energy consumption is considered to be dynamic. The protocol has been compared with Middle Position Dynamic Energy Opportunistic Routing (MDOR), and Trust and Location Aware Routing Protocol (TLAR). Simulation results depict that the proposed OR protocol optimized the throughput and network lifetime

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