Introduction to algorithms
Message Ferrying: Proactive Routing in Highly-Partitioned Wireless Ad Hoc Networks
FTDCS '03 Proceedings of the The Ninth IEEE Workshop on Future Trends of Distributed Computing Systems
A message ferrying approach for data delivery in sparse mobile ad hoc networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
Data collection, storage, and retrieval with an underwater sensor network
Proceedings of the 3rd international conference on Embedded networked sensor systems
CenWits: a sensor-based loosely coupled search and rescue system using witnesses
Proceedings of the 3rd international conference on Embedded networked sensor systems
Slip surface localization in wireless sensor networks for landslide prediction
Proceedings of the 5th international conference on Information processing in sensor networks
Efficient In-Network Moving Object Tracking in Wireless Sensor Networks
IEEE Transactions on Mobile Computing
Hybrid routing in clustered DTNs with message ferrying
Proceedings of the 1st international MobiSys workshop on Mobile opportunistic networking
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
IEEE Transactions on Mobile Computing
Using mobile wireless sensors for in-situ tracking of debris flows
Proceedings of the 6th ACM conference on Embedded network sensor systems
YushanNet: A Delay-Tolerant Wireless Sensor Network for Hiker Tracking in Yushan National Park
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Using predictable observer mobility for power efficient design of sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
My Tai-Chi book: a virtual-physical social network platform
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Hi-index | 0.00 |
This paper considers a field with a number of isolated wireless sensor networks served by some mobile mules and base stations (BSs). Sensing data needs to be carried by mobile mules to BSs via opportunistic contact between them. Also, such contact may not be frequent. Thus there are four types of communications in this environment: (i) inter-node communications within a WSN, (ii) opportunistic WSN-to-mule communications, (iii) opportunistic mule-to-mule communications, and (iv) opportunistic mule-to-BS communications. In such disconnected WSNs, since sensors' memory spaces are limited and data collection from isolated WSNs to mules and then to BSs relies on opportunistic communications in the sense that contact between these entities is occasional, storing and collecting higher-priority data is necessary. Therefore, there are two critical issues to be addressed: the data storage management in each isolated WSN and opportunistic data collection between these entities. We address the storage management problem by modeling the limited memory spaces of a WSN's sensor nodes as a distributed storage system. Assuming that there is a sink in the WSN that will be visited by mobile mules occasionally, we address three issues: (i) how to buffer sensory data to reduce data loss due to a shortage of storage spaces, (ii) if dropping of data is inevitable, how to avoid higher-priority data from being dropped, and (iii) how to manage the data nearby the sink to facilitate the downloading jobs of mules when the downloading time is unpredictable. We propose a Distributed Storage Management (DSM) strategy based on a novel shuffling mechanism similar to heap sort. It allows nodes to exchange sensory data with neighbors efficiently in a distributed manner. For the opportunistic data collection problem, based on a utility model, we then develop an Opportunistic Data Exchange (ODE) strategy to guide two mules to exchange data that would lead to a higher reward. To the best of our knowledge, this is the first work addressing distributed storage strategy for isolated WSNs with opportunistic communications using mobile mules. We conduct extensive simulations to investigate the merit of DSM and ODE. The simulation results indicate that the level of data importance collected by our DSM is very close to a global optimization and our ODE could facilitate delivery of important data to BSs through mules. We also implement these strategies in a real sensor platform, which demonstrates that the simple and lightweight protocols can achieve our goals.