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In large-scale Wireless Sensor Networks (WSNs), leveraging data sinks' mobility for data gathering has drawn substantial interests in recent years. Current researches either focus on planning a mobile sink's moving trajectory in advance to achieve optimized network performance, or target at collecting a small portion of sensed data in the network. In many application scenarios, however, a mobile sink...
Multiple Channel Design (MCD) has been adopted widely in wireless networks to increase throughput and reliability with relatively less energy consumption. Due to physical restrictions of sensor nodes, applying multiple radio channels in sensor networks poses significant challenges, particularly on energy consumption. To address such challenges, we propose an energy-aware MCD scheme called SmartChannel...
This paper addresses energy-efficient data gathering issues in wireless sensor networks (WSNs). Leveraging data correlation in densely-deployed sensor networks, we propose an Energy-aware Probability-based Clustering algorithm (EPC), featuring high scalability and flexibility particularly suitable for large-scale WSNs. Unlike most existing data gathering schemes that construct static routing structures...
In Wireless Sensor Networks (WSN), data gathering using mobile sinks typically incurs constant propagation of sink location indication messages to guide the direction of data reporting. Such behavior is undesirable, especially when the sensor network scale increases, as frequent message flooding will cause serious congestion in network communication and significantly impair the sensor network lifetime...
This paper proposes a mobile-agent-based data gathering system (called TinyBee) in wireless sensor networks. Most existing mobile-agent-based systems consider only static sinks/servers. In this paper, we consider both mobile servers and lightweight mobile agents. We aim to design a data gathering system using a special kind of mobile agent called TinyBee to collect data all over a network. TinyBee...
We propose a novel measure method of information utility for tracking and localization in wireless sensor networks (WSNs). The target moving arbitrarily in WSNs is modeled by Markov chains using a transition matrix. The proposed information utility measurement allows us to expect the next state of the target and identify the informative sensors. Further, compared with existing localization methods,...
Wireless sensor networks (WSNs) are severely constrained in computation and communication capabilities due to the cost and size of available sensors. On the other hand, autonomic computing (AC) offers a promising solution to manage large-scale computing systems without human intervention. Realizing the similarity between WSNs and AC applications, this paper proposes an autonomic sensor network framework...
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