Adaptive Data Dissemination in Sensor Networks Using WPDD

In wireless sensor networks (WSNs), address-based routing approaches often lead to severe problems due to node mobility, energy-saving sleep-cycles, and often missing or unreliable address information. Data-centric routing schemes such as flooding or gossiping solve these problems but may lead to congestion or starvation. Based on biologically inspired mechanisms known from cellular signaling pathways, we discovered potentials in enhancing the communication required for self-organization in network environments suffering from datapaths with low reliability and time variations of the reliability. Using an importance factor for particular transmissions in combination with feedback loops, the overall quality of the global system can be increased. The resulting algorithm, Weighted Probabilistic Data Dissemination (WPDD), includes an inherent adaptation to changing network conditions. Congestion control is supported as well as prioritized data communication. This paper outlines the working behavior of WPDD and demonstrates its applicability based on selected simulation results.