Akihide Utani

Synchronization-based data gathering scheme using chaotic pulse-coupled neural networks in wireless sensor networks

Wireless sensor networks (WSNs) have attracted significant interests of many researchers because they have great potential as a means of obtaining information of various environments remotely. WSNs have their wide range of applications, such as natural environmental monitoring in forest regions and environmental control in office buildings. In WSNs, hundreds or thousands of micro-sensor nodes with such resource limitation as battery capacity, memory, CPU, and communication capacity are deployed without control in a region and used to monitor and gather sensor information of environments. Therefore, scalable and efficient network control and/or data gathering scheme for saving energy consumption of each sensor node is needed to prolong WSN lifetime. In this paper, assuming that sensor nodes synchronize to intermittently communicate with each other only when they are active for realizing the long-term employment of WSNs, we propose a new synchronization scheme for gathering sensor information using chaotic pulse-coupled neural networks (CPCNN). We evaluate the proposed scheme using computer simulation and discuss its development potential. In simulation experiment, the proposed scheme is compared with previous synchronization scheme based on a pulse-coupled oscillator model to verify its effectiveness.

Bio-inspired data transmission scheme to multiple sinks for the long-term operation of wireless sensor networks

Wireless sensor networks have a wide range of applications, such as natural environmental monitoring, object tracking, and environmental control in residential spaces or plants. In wireless sensor networks, many sensor nodes with limited resources are placed in an observation area and used to gather information about environments. Therefore, a data gathering scheme (or a routing algorithm) for saving and balancing the energy consumption of each sensor node is needed to prolong the lifetime of wireless sensor networks. This article proposes a new bio-inspired data transmission scheme for the long-term operation of wireless sensor networks. By using the proposed scheme, autonomous load-balancing data transmission to multiple sinks can be actualized. We evaluate the proposed scheme using computer simulations to verify its effectiveness, and also discuss its development potential.

Prolonging lifetime of multiple-sink wireless sensor networks using chaos-based data gathering scheme

This paper studies chaos synchronization-based data transmission scheme in multiple sink wireless sensor networks. In the proposed scheme, each wireless sensor node has a simple chaotic oscillator. The oscillators generate impulsive signals with chaotic interspike intervals, and are impulsively coupled by the signals via wireless communication. Each wireless sensor node receives and transmits sensor information only in the timing of the couplings. The proposed scheme can exhibit various chaos synchronization, and can effectively gather sensor information with low energy consumption. Also, the proposed scheme can flexibly adapt various wireless sensor networks not only with a single sink node but also with multiple sink nodes. We evaluate the proposed scheme using computer simulations. Through simulation experiments, we show effectiveness of the proposed scheme and discuss its development potential.

Coordinated Rule Acquisition of Decision Making on Supply Chain by Exploitation-Oriented Reinforcement Learning

Product order decision-making is an important feature of inventory control in supply chains. The beer game represents a typical task in this process. Recent approaches that have applied the agent model to the beer game have shown. Q-learning performing better than genetic algorithm (GA). However, flexibly adapting to dynamic environment is difficult for these approaches because their learning algorithm assume a static environment. As exploitation-oriented reinforcement learning algorithm are robust in dynamic environments, this study, approaches the beer game using profit sharing, a typical exploitation-oriented agent learning algorithm, and verifies its results validity by comparing performances.

A competitive PSO based on evaluation with priority for finding plural solutions

In this paper, we propose a simple competitive PSO for finding plural solutions. In the proposed PSO, particles are divided into groups corresponding to the required number of solutions. Each group simultaneously searches solutions having a priority search region. This region affects to prohibit that different groups search the same solutions. The proposed PSO can effectively find desired plural acceptable solutions with a high accuracy and with a low computation cost, and can easily control combinations of these solutions by adjusting a parameter. Also, the proposed PSO is applied to a problem in wireless sensor networks (WSNs). The simulation results show that obtained results can contribute to prolonging lifetime of WSNs.

An effective sink node allocation scheme for long-term operation of Wireless Sensor Networks using adaptive suppression PSO

Wireless Sensor Networks (WSNs) have attracted a significant amount of interests from many researchers for a wide range of applications, such as natural environmental monitoring and environmental control in residential spaces or factories. To realize long-term operation of WSNs, we discuss in this study a method of suppressing the communication load on sensor nodes by effectively placing a limited number of sink nodes in an observation area that integrate sensing data from sensor nodes around them. As a technique of solving effective locations for sink nodes, in past studies, we have proposed a search method based on particle swarm optimization that is one of the swarm intelligence algorithms, named the Suppression Particle Swarm Optimization (SPSO). This paper proposes a new technique, named the Advanced Suppression Particle Swarm Optimization (ASPSO) having an adaptive control scheme for its parameters.

A Sink Node Allocation Scheme in Wireless Sensor Networks Using Suppression Particle Swarm Optimization

A wireless sensor network, which is a key network to facilitate ubiquitous information environments, has attracted a significant amount of interest frommany researchers (Akyildiz et al., 2002). A wireless sensor network has a wide range of applications, such as natural environmental monitoring, environmental control in residential spaces or plants, object tracking, and precision agriculture. In a general wireless sensor network, hundreds or thousands of micro sensor nodes, which are generally compact and inexpensive, are placed in a large scale observation area and sensing data of each node is gathered to a sink node by inter-node wireless multi-hop communication. Each sensor node consists of a sensing function to measure the status (temperature, humidity, motion, etc.) of an observation point or object, a limited function on information processing, and a simplified wireless communication function, and generally operates on a resource of a limited power-supply capacity such as a battery. Therefore, a data gathering scheme and/or a routing protocol capable of meeting the following requirements has been mainly studied to prolong the lifetime of a wireless sensor network.

A Data Gathering Scheme in Wireless Sensor Networks Based on Synchronization of Chaotic Spiking Oscillator Networks

This paper studies chaos‐based data gathering scheme in multiple sink wireless sensor networks. In the proposed scheme, each wireless sensor node has a simple chaotic oscillator. The oscillators generate spike signals with chaotic interspike intervals, and are impulsively coupled by the signals via wireless communication. Each wireless sensor node transmits and receives sensor information only in the timing of the couplings. The proposed scheme can exhibit various chaos synchronous phenomena and their breakdown phenomena, and can effectively gather sensor information with the significantly small number of transmissions and receptions compared with the conventional scheme. Also, the proposed scheme can flexibly adapt various wireless sensor networks not only with a single sink node but also with multiple sink nodes. This paper introduces our previous works. Through simulation experiments, we show effectiveness of the proposed scheme and discuss its development potential.

A Chaos-Based Data Gathering Scheme Using Chaotic Oscillator Networks

Recently, wireless sensor networks have been studied extensivelywith a great amount of interest. In wireless sensor networks, many wireless sensor nodes are deployed in an observation area, and monitor status information such as temperature around them. Sensing information is transmitted to and gathered by one or more sink nodes. Each wireless sensor node not only transmits own sensing data but also relays the sensing data from the other wireless sensor nodes. By such a multi-hop wireless communication, the wireless sensor networks are available to observation for large-scale area, and have various applications including natural environmental monitoring. Since wireless sensor nodes generally operate by batteries, efficient data gathering schemes with saving energy consumption of each wireless sensor node are needed for prolonging wireless sensor network lifetime. Ant-based algorithms (Caro et al., 2004; Marwaha et al., 2002; Ohtaki et al., 2006; Subramanian et al., 1998) and cluster-based algorithms (Dasgupta et al., 2003; Heinzelman et al., 2000) have been proposed as routing algorithms. They are more scalable, efficient and robust than the other conventional routing algorithms (Clausen & Jaquet, 2003; Johnson et al., 2003; Ogier et al., 2003; Perkins & Royer, 1999). Sink node allocation schemes based on particle swarm optimization algorithms (Kumamoto et al., 2009; Yoshimura et al., 2009) aim to minimize total hop counts in wireless sensor networks and to reduce energy consumption in each wireless sensor node. Forwarding node set selection schemes (Nagashima et al., 2009; Sasaki et al., 2009) can significantly reduce the number of transmissions of duplicate query messages as compared with original flooding schemes. Secure communication schemes considering energy savings (Li et al., 2009; Wang et al., 2009) have also been proposed. Common purpose of these studies is to prolong wireless sensor network lifetime by saving energy consumption of each wireless sensor node. Along this line, this study focuses on control schemes for timings of transmissions and receptions of sensing data, proposed as a synchronization-based data gathering scheme (Wakamiya & Murata, 2005). In this scheme, each wireless sensor node has a timer characterized by an integrate-and-fire neuron (Keener et al., 1981). Coupling the timers of wireless sensor nodes which can directly communicate to each other, they construct a pulse-coupled neural network. It is known that pulse-coupled neural networks can exhibit various synchronous and asynchronous phenomena (Catsigeras & Budelli, 1992; Mirollo & Strogatz, 1990). The conventional synchronization-based data gathering scheme is based on the synchronization in pulse-coupled neural networks. As synchronization is achieved, the following control for timings of transmissions and receptions of sensing data is possible: wireless sensor nodes turn 21