• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.74-90
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• 2014

Routing in mobile wireless sensor networks (MWSNs) is an extremely challenging issue due to the features of MWSNs. In this paper, we present a novel bio-inspired trusted routing protocol (B-iTRP) based on artificial immune system (AIS), ant colony optimization (ACO) and Physarum optimization (PO). For trust mechanism, B-iTRP monitors neighbors' behavior in real time and then assesses neighbors' trusts based on AIS. For routing strategy, each node proactively finds routes to the Sink based on ACO. When a backward ant is on the way to return source, it senses the energy residual and trust value of each node on the discovered route, and calculates the link trust and link energy of the route. Moreover, B-iTRP also assesses the availability of route based on PO to maintain the route table. Simulation results show how B-iTRP can achieve the effective performance compared to existing state-of-the-art algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.44-46
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• 2020

Aggregating data with an optimal delay, which is a critical problem in Wireless Sensor Networks applications, is proven as NP-hard. In this paper, we focus on optimizing the aggregation delay by presenting an idea for channel and timeslot co-scheduling data aggregation in MWSNs. The proposed scheme, which names Break and Join, maximizes the number of sensor nodes to be scheduled in a working period, so that the overall number of working periods and data collection delay are reduced.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.175-177
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• 2020

In multi-channel wireless sensor networks, optimizing data aggregation delay without any channels and timeslots conflicts has been concerned these days. The aggregation delay can be reduced by using different aggregation tree construction methods or scheduling in different methods in bottom-up or top-down manners. In this paper, we propose a new way of constructing aggregation tree purposing to decrease the total aggregation delay. The result shows that our proposed scheme can improve up to 64% comparing with state-of-the-art schemes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.1-9
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• 2017

Recently, the active research into wireless sensor networks has led to the development of sensor nodes with improved performance, including their mobility and location awareness. One of the most important goals of such sensor networks is to transmit the data generated by mobile sensors nodes. Since these sensor nodes move in the mobile wireless sensor networks (MWSNs), the energy consumption required for them to transmit the sensed data to the fixed sink is increased. In order to solve this problem, the use of mobile sinks to collect the data while moving inside the network is studied herein. The important issues are the mobility and energy consumption in MWSNs. Because of the sensor nodes' limited energy, their energy consumption for data transmission affects the lifetime of the network. In this paper, a mobile-sink based energy-efficient clustering scheme is proposed for use in mobile wireless sensor networks (MECMs). The proposed scheme improves the energy efficiency when selecting a new cluster head according to the mobility of the mobile sensor nodes. In order to take into consideration the mobility problem, this method divides the entire network into several cluster groups based on mobile sinks, thereby decreasing the overall energy consumption. Through both analysis and simulation, it was shown that the proposed MECM is better than previous clustering methods in mobile sensor networks from the viewpoint of the network energy efficiency.