Takuya Iwai

Error-Tolerant Coverage Control based on Bio-inspired Attractor Selection Model for Wireless Sensor Networks

A coverage problem is one of major issues of a wireless sensor network to prolong the lifetime while guaranteeing that the target region and objects are monitored by sufficient number of active nodes. There have been many proposals on the coverage problem, but most of them use geometric algorithms in order to determine whether to monitor around or sleep. As such, these algorithms require information about the location, sensing area, and sensing state of neighbor nodes. In addition, they suffer from localization error leading to degradation of coverage and redundancy of active nodes. In this paper, we propose a coverage control mechanism where each sensor node relies only on the information about the degree of coverage of the target region. To enable autonomous decision of sensor nodes, we adopt a nonlinear mathematical model called the attractor selection model of adaptive behavior of biological systems to dynamically changing environment. Through simulation experiments, it is shown that the proposal outperforms the existing protocol regarding the per-node coverage and the overhead under influece of localization error.

Error-Tolerant and Energy-Efficient Coverage Control Based on Biological Attractor Selection Model in Wireless Sensor Networks

A coverage problem is one of the important issues to prolong the lifetime of a wireless sensor network while guaranteeing that the target region is monitored by a sufficient number of active nodes. Most of existing protocols use geometric algorithm for each node to estimate the degree of coverage and determine whether to monitor around or sleep. These algorithms require accurate information about the location, sensing area, and sensing state of neighbor nodes. Therefore, they suffer from localization error leading to degradation of coverage and redundancy of active nodes. In addition, they introduce communication overhead leading to energy depletion. In this paper, we propose a novel coverage control mechanism, where each node relies on neither accurate location information nor communication with neighbor nodes. To enable autonomous decision on nodes, we adopt the nonlinear mathematical model of adaptive behavior of biological systems to dynamically changing environment. Through simulation, we show that the proposal outperforms the existing protocol in terms of the degree of coverage per node and the overhead under the influence of localization error.

Proposal for Dynamic Organization of Service Networks over a Wireless Sensor and Actuator Network

Abstract In the ambient information society, embedded sensors detect and conjecture environmental and personal conditions. Then, actuators provide users with information services and environmental controls which are suited for time, place, occasion, and people. Although a single service cannot meet diverse requirements of di_erent situations, it is hard to deploy and configure a variety of devices for each of envisioned services. To solve the problem, we propose a mechanism to dynamically self-organize service networks by combining existing devices. In our proposal, we adopt a mathematical model of division of labors in a colony of social insects to accomplish autonomous selection of devices, which o_er sensing and control functions to a service network, while taking into account their states and service requirements. Through simulation, we confirmed that our proposal can organize e_cient service networks combining nodes with higher residual energy and more service provision.

Free-Energy-Based Design Policy for Robust Network Control against Environmental Fluctuation

Bioinspired network control is a promising approach for realizing robust network controls. It relies on a probabilistic mechanism composed of positive and negative feedback that allows the system to eventually stabilize on the best solution. When the best solution fails due to environmental fluctuation, the system cannot keep its function until the system finds another solution again. To prevent the temporal loss of the function, the system should prepare some solution candidates and stochastically select available one from them. However, most bioinspired network controls are not designed with this issue in mind. In this paper, we propose a thermodynamics-based design policy that allows systems to retain an appropriate degree of randomness depending on the degree of environmental fluctuation, which prepares the system for the occurrence of environmental fluctuation. Furthermore, we verify the design policy by using an attractor selection model-based multipath routing to run simulation experiments.

Thermodynamics-Based Strategy to Achieve Balance between Robustness and Performance for Self-Organized Network Controls

Bio-inspired network controls are driven by the competition between their ordering force and disordering force. Both forces simultaneously affect their performance and robustness. Therefore, we must carefully determine their balance. In this paper, we focus on thermodynamic phenomena where a substance achieves the balance between both forces depending on its temperature. We translate bio-inspired network controls from the perspective of thermodynamics, and we analytically show that the appropriate balance between both forces can be achieved by selecting appropriate temperature.

Characteristic Analysis of Response Threshold Model and Its Application for Self-organizing Network Control

There is an emerging research area to adopt bio-inspired algorithms to self-organize an information network system. Despite strong interests on their benefits, i.e. high robustness, adaptability, and scalability, the behavior of bio-inspired algorithms under non-negligible perturbation such as loss of information and failure of nodes observed in the realistic environment is not well investigated. Because of lack of knowledge, none can clearly identify the range of application of a bio-inspired algorithm to challenging issues of information networks. Therefore, to tackle the problem and accelerate researches in this area, we need to understand characteristics of bio-inspired algorithms from the perspective of network control. In this paper, taking a response threshold model as an example, we discuss the robustness and adaptability of bio-inspired model and its application to network control. Through simulation experiments and mathematical analysis, we show an existence condition of the equilibrium state in the lossy environment. We also clarify the influence of the environmental condition and control parameters on the transient behavior and the recovery time.