Parallel watershed transformation algorithms for image segmentation
Parallel Computing
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Parallel Asynchronous Watershed Algorithm-Architecture
IEEE Transactions on Parallel and Distributed Systems
Fast and energy efficient sensor data collection by multiple mobile sinks
Proceedings of the 5th ACM international workshop on Mobility management and wireless access
SenCar: An Energy-Efficient Data Gathering Mechanism for Large-Scale Multihop Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Efficient data propagation strategies in wireless sensor networks using a single mobile sink
Computer Communications
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
Promoting Heterogeneity, Mobility, and Energy-Aware Voronoi Diagram in Wireless Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Optimal Speed Control of Mobile Node for Data Collection in Sensor Networks
IEEE Transactions on Mobile Computing
DCOSS'07 Proceedings of the 3rd IEEE international conference on Distributed computing in sensor systems
A Rendezvous-Based Approach Enabling Energy-Efficient Sensory Data Collection with Mobile Sinks
IEEE Transactions on Parallel and Distributed Systems
Strategies for data dissemination to mobile sinks in wireless sensor networks
IEEE Wireless Communications
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This paper presents a clustering protocol combined with a mobile sink (MS) solution for efficient data gathering in wireless sensor networks (WSNs). The main insight for the cluster creation method is drawn from image processing field and namely from the watershed transformation which is widely used for image segmentation. The proposed algorithm creates multi-hop clusters whose clusterheads (CHs) as well as all cluster members near the CHs have high energy reserves. As these are exactly the nodes most burdened with relaying of data from other cluster members, the higher levels of available energy at these nodes prolong the network lifetime eventually. After cluster creation, a MS periodically visits each CH and collects the data from cluster members already gathered at the CH. Simulation results show the higher performance of the proposed scheme in comparison to other competent approaches from the literature.