Wireless sensor node mobility and its effect on transmission reliability

Abstract: Deploying a Wireless Sensor Network (WSN) poses certain challenges such as data reliability due to Electromagnetic Interference (EMI), multipath fading as well as faster energy depletion of nodes located near the base station creating communication holes in the network. Several energy efficient algorithms have been developed to improve the energy consumption of static nodes however the issue of battery depletion of nodes near the base station remains present. In this paper we attempt to model the relationship between the node mobility and the reliability of data transmission. Mobile nodes could move near static nodes experiencing high traffic in order to reduce the number of packets sent through the saturated nodes. This paper will investigate, using a real environment, the effect of speed and packet size on the reliability of the wireless link. This is a required prerequisite, prior to a detailed design of a Mobile relay node

Measurement Study of Mobility-Induced Losses in IEEE 802.15.4

Recent years have seen an increasing need of wireless networks in a mobile environment serving for more complex tasks and applications. Mobility becomes an indispensable factor of the system design and has been widely recognized as a general cause of packet loss. Though many works have been done on mobility study, to the best of our knowledge, they are mainly based on simulations or analytical studies that assume idealized link conditions. In this work, we experimentally investigate the nature of the error characteristics of mobility-induced packet losses at "chip-level" in IEEE 802.15.4. We believe this more understanding of mobility-induced packet losses can bring great potential benefits for further study on channel coding, routing and protocol design. Toward this end, we design and implement an efficient algorithm to distinguish mobility-induced packet losses from other packet losses of static environments such as attenuation. Our algorithm is greatly advantaged as it needs no training data even when environment changes. Collecting three corrupted packets is sufficient to obtain a satisfactory performance. This feature makes our design in particular suitable for dynamic and mobile environments, allowing real-time mobility-induced loss detection in an online manner. Experiments based on GNU Radio testbed show that our algorithm can provide an accuracy of up to 96%