Feasibility problems for recurring tasks on one processor
MFCS '90 Selected papers of the 15th international symposium on Mathematical foundations of computer science
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
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
Intelligent fluid infrastructure for embedded networks
Proceedings of the 2nd international conference on Mobile systems, applications, and services
Versatile low power media access for wireless sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
RTSS '04 Proceedings of the 25th IEEE International Real-Time Systems Symposium
Z-MAC: a hybrid MAC for wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Data collection, storage, and retrieval with an underwater sensor network
Proceedings of the 3rd international conference on Embedded networked sensor systems
Approximation Algorithms for Scheduling Multiple Feasible Interval Jobs
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Distributed Minimal Time Convergecast Scheduling in Wireless Sensor Networks
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Controllably Mobile Infrastructure for Low Energy Embedded Networks
IEEE Transactions on Mobile Computing
Mobile Element Scheduling with Dynamic Deadlines
IEEE Transactions on Mobile Computing
SenCar: An Energy-Efficient Data Gathering Mechanism for Large-Scale Multihop Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Rendezvous Planning in Mobility-Assisted Wireless Sensor Networks
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
Rendezvous design algorithms for wireless sensor networks with a mobile base station
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Brimon: a sensor network system for railway bridge monitoring
Proceedings of the 6th international conference on Mobile systems, applications, and services
Optimal Speed Control of Mobile Node for Data Collection in Sensor Networks
IEEE Transactions on Mobile Computing
SenCar: an energy efficient data gathering mechanism for large scale multihop sensor networks
DCOSS'06 Proceedings of the Second IEEE international conference on Distributed Computing in Sensor Systems
Multiple controlled mobile elements (data mules) for data collection in sensor networks
DCOSS'05 Proceedings of the First IEEE international conference on Distributed Computing in Sensor Systems
Mobility-based communication in wireless sensor networks
IEEE Communications Magazine
Path Planning of Data Mules in Sensor Networks
ACM Transactions on Sensor Networks (TOSN)
Poster abstract: connected wireless camera network deployment with visibility coverage
Proceedings of the 12th international conference on Information processing in sensor networks
Collecting data in ad-hoc networks with reduced uncertainty
Ad Hoc Networks
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Unlike traditional multihop forwarding among stationary sensor nodes, use of mobile devices for data collection in wireless sensor networks has recently been gathering more attention. The use of mobility significantly reduces the energy consumption at sensor nodes, elongating the functional lifetime of the network. However, a drawback is an increased data delivery latency. Reducing the latency through optimizing the motion of data mules is critical for this approach to thrive. In this article, we focus on the problem of motion planning, specifically, determination of the speed of the data mule and the scheduling of the communication tasks with the sensors. We consider three models of mobility capability of the data mule to accommodate different types of vehicles. Under each mobility model, we design optimal and heuristic algorithms for different problems: single data mule case, single data mule with periodic data generation case, and multiple data mules case. We compare the performance of the heuristic algorithm with a naive algorithm and also with the multihop forwarding approach by numerical experiments. We also compare one of the optimal algorithms with a previously proposed method to see how our algorithm improves the performance and is also useful in practice. As far as we know, this study is the first of a kind that provides a systematic understanding of the motion planning problem of data mules.