Relevance-based partial reliability in wireless sensor networks

Abstract

Wireless sensor networks can provide valuable information for a lot of measurement, tracking, surveillance, automation, and general-purpose monitoring applications. Information as humidity, temperature, pressure, infrared images, and noises will be sensed and packetized for distribution over the network, but corruption during transmission may compromise the accuracy of the retrieved information and even put people in danger. In fact, the sensed data may have different relevancies for the applications, altering the impact of packet corruptions. We propose a relevance-based partially reliable transmission approach to provide data delivery with different reliability guaranties, exploiting the relevancies of transmitted data when choosing the proper error recovery service. In this context, some error scenarios are investigated, considering different configurations of error bursts. We expect that the proposed partially reliable transmission mechanism can save energy over the network while assuring acceptable quality for sensing monitoring.

TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications

“…The relevance level of each sensor node (priority) is considered to calculate the positions of every sink in WVSNs. In a different perspective, the work in [ 8 ] exploits the nature of transmitted data to differentiate how corrupted packets will be recovered. Whatever is the employed optimization approach, prioritization levels may be exploited to enhance the performance of the network, delivering high quality data while reducing resource expenditure.…”

“…Among those challenges, hundreds or thousands of sensors may be continuously transmitting information, which may require considerable bandwidth, especially when streaming multimedia content. Furthermore, real-time delivery may also be required for fast response to external systems requests, which may also demand different levels of reliability guarantees for transmitted data [ 7 , 8 ]. Thus, optimizing transmissions of sensed data in Smart City scenarios is of paramount importance and it is the core motivation of this work.…”