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Wichai Pawgasame

Bio: Wichai Pawgasame is an academic researcher from Sirindhorn International Institute of Technology. The author has contributed to research in topics: Wireless network & Sensor node. The author has an hindex of 3, co-authored 9 publications receiving 31 citations.

Papers
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Proceedings ArticleDOI
01 Jan 2016
TL;DR: A survey for adaptive hybrid wireless sensor networks in the military operations is presented, which reviews their technologies, applications, constraints, architectures, and challenges.
Abstract: A Sensor Network is the primary source for acquiring information in today's military operations that require situation awareness (SA) of a battlefield. There are several types of sensor nodes, and each type of sensors has limited capability. The requirement for gathering and analyzing information about the field cannot be fulfilled by one type of sensor. Several sensors are needed to be networked and provide distributed sensing in such the way that the complete information about the field can be achieved. With current sensor and wireless technologies, a large number of heterogeneous sensor nodes can be rapidly deployed and wirelessly networked in a battlefield. These sensor nodes can perform distributed sensing tasks in collaborative and cooperative manner in order to extract features of the event in the field. Unlike any typical network, military wireless sensor network is operating under the harsh condition of a battlefield. Hence, the resources are constrained in terms of energy, bandwidth, and computing power, which limit the sensing capability of the wireless sensor network. In addition, a network is prone to attack by enemies. Such a network requires the self-adaptability that can cope with intermittent changes in a harsh environment. This paper presents a survey for adaptive hybrid wireless sensor networks in the military operations, which reviews their technologies, applications, constraints, architectures, and challenges.

14 citations

Proceedings ArticleDOI
23 Apr 2015
TL;DR: Several research gaps in performance, security, routing, and management of tactical wireless networks that are needed to be improved, are pointed out to pave the way for future research in this area.
Abstract: As network centric warfare becoming the key concept in the modern military doctrine, tactical wireless networks have been used extensively throughout military operations for sharing crucial information among deployed units. Most tactical wireless networks are operating in a hostile environment, in which normal network operation cannot be easily achieved. In military operations, tactical wireless networks have high demands for robustness, responsiveness, reliability, availability and security. These requires continuous development of new technologies in order to cope with random behaviours of hostile environment. However, the random behaviour of tactical wireless networks under hostile environment has not been fully understood. This paper provides a survey on current issues, and research challenges in tactical wireless networks due to hostile environment. Several research gaps in performance, security, routing, and management of tactical wireless networks that are needed to be improved, are pointed out to pave the way for future research in this area. This paper provides insight understanding about the issues and trends for future development of tactical wireless networks.

13 citations

Proceedings ArticleDOI
23 Apr 2015
TL;DR: This paper gives intuitive idea of implementing simulation tool for designing of solid propellant mass in rocket application and shows the reasonable trend of thrust profile according to the real behavior of thrust generated bySolid propellant.
Abstract: The knowledge of internal ballistics simulation is quite obscure due to security reason related to rocket implementation for national defense. Internal ballistics simulation involves complex calculation of thrust profile generated by burning solid propellant mass. The design of appropriate solid propellant mass for desired thrust profile requires visualization of propellant mass and overlook how it burns from the start to the end. Object-oriented programming has been used as a tool for simulation of complex mathematic algorithms in many fields. This paper introduced object-oriented programming framework and software architecture for solving complex calculation of thrust profile and visualization of burning solid propellant. JAVA programming language is chosen to implement a test program for proving objected-oriented programming based internal ballistics simulation. The result shows the reasonable trend of thrust profile according to the real behavior of thrust generated by solid propellant. This paper gives intuitive idea of implementing simulation tool for designing of solid propellant mass in rocket application.

4 citations

Proceedings ArticleDOI
01 Jan 2017
TL;DR: The result shows that SoC-based SDR can be a potential for SDR in the military communications, and digital codings on SoC as the digital processing unit are evaluated.
Abstract: The modern military communication extensively utilizes radio spectrums to convey important information. Radio transceivers have evolved from large analog transceivers to miniature digital transceivers. Digital transceivers are relied on digital communication techniques, which include various digital codings and digital modulations. Digital codings are crucial processes in most digital communications. The outstanding advantages of digital codings are that it conserves channel bandwidth, and it makes information more robust. There are plenty of digital codings in military communications. Each coding is suitable for the specific application and environment. The implementation of various digital codings on one device is possible with a software defined radio (SDR), at which the transmission characteristics of a SDR can be defined by the software running on the device. Hence, a SDR can be reprogrammed to meet the require transmission characteristics. A logic parts of SDR can be implemented either by Digital Signal Processor (DSP) or Field Programmable Gate Array (FPGA). With the current semiconductor technology, both DSP and FPGA can be integrated into one chip, which is known as a System-on-Chip (SoC). This article evaluates the performance of the military digital codings on SoC as the digital processing unit. The result shows that SoC-based SDR can be a potential for SDR in the military communications.

2 citations

Proceedings ArticleDOI
13 Jul 2016
TL;DR: A decent method is presented to derive the intruder detection probability and the effects of the design factors to the intruder Detection probability are analyzed to guide the way to design a mobile sensor network in a belt region with improved intruder detection probabilities.
Abstract: A belt region can be used to describe a border area, which has the characteristic as a long strip area. Intruders may want to trespass this region without authorization. To prevent this illegal border crossing, a mobile sensor network can be deployed in the region. Mobile sensors can move throughout a region looking for an intruder, while the number of mobile sensor nodes can be kept at the minimum. However, there are some design factors that impact the intruder detection probability of a mobile sensor network. These factors are environment model, intruder arrivals, intruder mobility, sensing capability of a sensor node, and sensor selection mechanism. By understanding the impacts of these factors to the intruder detection probability, a mobile sensor network can be designed for better performance. This paper presents a decent method to derive the intruder detection probability and analyzes the effects of the design factors to the intruder detection probability. The result will guide the way to design a mobile sensor network in a belt region with improved intruder detection probability.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: AI has provided robust solutions to some specific tasks in mobile robotics, such as information retrieval from scenes, mapping, localization and exploration, which can be of interest making an analysis of the current state of the topic.
Abstract: Nowadays, the field of mobile robotics has experienced an important evolution and these robots are more commonly proposed to solve different tasks autonomously. The use of visual sensors has played an important role in mobile robotics tasks during the past few years due to the advances in computer vision hardware and algorithms. It is worth remarking the use of AI tools to solve a variety of problems in mobile robotics based on the use of images either as the only source of information or combining them with other sensors such as laser or GPS. The improvement of the autonomy of mobile robots has attracted the attention of the scientific community. A considerable amount of works have been proposed over the past few years, leading to an extensive variety of approaches. Building a robust model of the environment (mapping), estimating the position within the model (localization) and controlling the movement of the robot from one place to another (navigation) are important abilities that any mobile robot must have. Considering this, this review focuses on analyzing these problems; how researchers have addressed them by means of AI tools and visual information; and how these approaches have evolved in recent years. This topic is currently open and a large number of works can be found in the related literature. Therefore, it can be of interest making an analysis of the current state of the topic. From this review, we can conclude that AI has provided robust solutions to some specific tasks in mobile robotics, such as information retrieval from scenes, mapping, localization and exploration. However, it is worth continuing to develop this line of research to find more integral solutions to the navigation problem so that mobile robots can increase their autonomy in large, complex and heterogeneous environments.

54 citations

Journal ArticleDOI
Nof Abuzainab1, Walid Saad1
TL;DR: In this paper, the problem of network connectivity is studied for an adversarial Internet of Battlefield Things (IoBT) system in which an attacker aims at disrupting the connectivity of the network by choosing to compromise one of the IoBT nodes at each time epoch.
Abstract: In this paper, the problem of network connectivity is studied for an adversarial Internet of Battlefield Things (IoBT) system in which an attacker aims at disrupting the connectivity of the network by choosing to compromise one of the IoBT nodes at each time epoch. To counter such attacks, an IoBT defender attempts to reestablish the IoBT connectivity by either deploying new IoBT nodes or by changing the roles of existing nodes. This problem is formulated as a dynamic multistage Stackelberg connectivity game that extends classical connectivity games and that explicitly takes into account the characteristics and requirements of the IoBT network. In particular, the defender’s payoff captures the IoBT latency as well as the sum of weights of disconnected nodes at each stage of the game. Due to the dependence of the attacker’s and defender’s actions at each stage of the game on the network state, the feedback Stackelberg solution [feedback Stackelberg equilibrium (FSE)] is used to solve the IoBT connectivity game. Then, sufficient conditions under which the IoBT system will remain connected, when the FSE solution is used, are determined analytically. Numerical results show that the expected number of disconnected sensors, when the FSE solution is used, decreases up to 46% compared to a baseline scenario in which a Stackelberg game with no feedback is used, and up to 43% compared to a baseline equal probability policy.

32 citations

Journal ArticleDOI
TL;DR: A novelTwo-tier quantizer that can be applied to different node deployment problems including the energy conservation in two-tier wireless sensor networks and three Lloyd-like algorithms are proposed and analyzed.
Abstract: Multi-tier networks have many applications in different fields. We define a novel two-tier quantizer that can be applied to different node deployment problems including the energy conservation in two-tier wireless sensor networks consisting of $N$ access points (APs) and $M$ fusion centers (FCs). We aim at finding an optimal deployment of APs and FCs to minimize the average weighted total, or Lagrangian, of sensor and AP powers. For one FC, $M=1$ , we show that the optimal deployment of APs is simply a linear transformation of the optimal $N$ -level quantizer for density $f$ , and the sole FC should be located at the geometric centroid of the sensing field. We also provide the exact expression of the AP-Sensor power function and prove its convexity. For more than one FC, $M>1$ , we provide a necessary condition for the optimal deployment. Furthermore, to numerically optimize the AP and FC deployment, we propose three Lloyd-like algorithms and analyze their convergence. Simulation results show that our algorithms outperform the existing algorithms.

31 citations

Proceedings ArticleDOI
01 Dec 2018
TL;DR: The results obtained indicate that ensemble-based learning methods outperformed single learning methods when the authors consider the detection accuracy metrics; AUC, TPR, and FPR, however, ensemble classifiers tend to be slower in in terms of build time and model test time.
Abstract: Modern tactical wireless network (TWN) communication technologies are not only capable of transmitting voice but also capable of transmitting data. Due to such capabilities, TWN have high security requirements as any security breach can lead to detrimental effects. Hence, securing such an environment is not only a requirement but also a virtual prerequisite to the network centric warfare operational (NCW) theory. One key to securing this environment is to promptly and accurately recognize information warfare attacks directed to the network and respond to them. This is achieved using intrusion detection systems (IDS). However, false detection of nodes in hostile environment remains a major problem that need to be addressed. Recently, machine learning methods and algorithms have shown applicability and are growing research area for cyber security and intrusion detection. Conversely, several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. The question then becomes, which one amongst these machine learning algorithms have the potential to enhance or address IDS issues in TWN. In this paper, seven machine learning classifiers are analyzed; Multi-Layer Perceptron, Bayesian Network, Support Vector Machine (SMO), Adaboost, Random Forest, Bootstrap Aggregation, and Decision Tree (J48). WEKA tool was used to implement and evaluate the classifiers. The results obtained indicate that ensemble-based learning methods outperformed single learning methods when we consider the detection accuracy metrics; AUC, TPR, and FPR. However, ensemble classifiers tend to be slower in in terms of build time and model test time.

28 citations

Proceedings ArticleDOI
01 Aug 2018
TL;DR: A new method of distributed multi-user dynamic spectrum access in cognitive radio network is proposed through combining deep reinforcement learning with evolutionary game theory, and the replicator dynamic is introduced into the setting of the reward function for reinforcement learning to effectively balance the collaboration among users.
Abstract: With the rapid development of wireless communication technology, the low utilization of spectrum resources and the high demand for spectrum have always been an urgent and paradoxical problem to be resolved. In order to alleviate this conflict, cognitive radio technology has been proposed. In this paper, we propose a new method of distributed multi-user dynamic spectrum access in cognitive radio network through combining deep reinforcement learning with evolutionary game theory. This method utilizes the Deep Q-network (DQN) as the main framework, and each user independently performs DQN algorithm to select channel. Through dynamic spectrum management, the utilization of spectrum resources can be effectively improved. In addition, we introduce the replicator dynamic using evolutionary game theory into the setting of the reward function for reinforcement learning, so as to effectively balance the collaboration among users. The simulation results show that the proposed algorithm can significantly reduce the collision rate of cognitive users and effectively increase the system capacity.

25 citations