Efficient Data Transmission in Delay Fault Tolerant Mobile Sensor Networks (DFT-MSN)

Pervasive information gathering plays a key role in many applications. One typical example is flu virus tracking, where the goal is to collect data of flu virus in the area with high human activities in order to monitor and prevent the explosion of devastating flu. Another example is air quality monitoring for tracking the average toxic gas taken by people everyday. The aforementioned applications share several unique characteristics. First, the data gathering is human-oriented. More specifically, while samples can be collected at strategic locations for flu virus tracking or air quality monitoring, the most accurate and effective measurement shall be taken at the people, making it a natural approach to deploy wearable sensing units that closely adapt to human activities. Second, we observe that delay and faults are usually tolerable in such applications, which aim at gathering massive information from a statistic perspective and to update the information base periodically. In this research, we study a Delay and Fault Tolerant Mobile Sensor Network (DFT-MSN) for pervasive information gathering. A DFT-MSN consists of two types of nodes, the wearable sensor nodes and the high-end sink nodes. The former are attached to people, gathering target information and forming a loosely connected mobile sensor network for information delivery. With short sensor transmission range and nodal mobility, the connectivity of DFT-MSN is very low, where a sensor connects to other sensors only occasionally. A number of high-end nodes (e.g., mobile phones or personal digital assistants with sensor interfaces) are either deployed at strategic locations with high visiting probability or carried by a subset of people, serving as the sinks to receive data from wearable sensors and forward them to access points of the backbone network. After carefully studying related work in the literature (such as Data Mule [1], ZebraNet [2], Habitat Monitoring [3], Delay Tolerant Networking [4], etc.) and