Pornavalai, Chotipat

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Pornavalai, Chotipat
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Pomavalai, Chotipat
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chotipat.po@kmitl.ac.th

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    An effective safety alert broadcast algorithm for VANET
    (2008-12-01)
    Suriyapaibonwattana, Kanitsorn
    ;
    Pomavalai, Chotipat
    VANET has become an interesting research field because we can get a lot of benefit from VANET such as to enhance road safety, reduce traffic congestion and etc. However VANET has some drawbacks such as broadcast storm disrupting network communication, rapid Topology changes. These problems need solutions to improve VANET's performance. In this paper we propose a new approach to reduce Broadcast Storm and improve performance for Safety Alert application in VANET. Finally we compare of the proposed algorithm performance the current standard approach. © 2008 IEEE.
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    An MLP-based face authentication technique robust to orientation
    (2009-11-20)
    Chakraborty, Goutam
    ;
    Chakraborty, Basabi
    ;
    Patra, Jagdish C.
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    Pornavalai, Chotipat
    The need for stricter security, availability of sophisticated algorithms and improved hardware at cheaper price, are the driving forces for increasing popularity of biometric authentication. Machine authentication from face images or fingerprints at the entrance of a building or at bank-teller is getting more and more common. The popularity of using face image features for authentication is due to its ease of use. But its success depends on proper orientation and illumination. Facial features change with the angle of orientation, and even a genuine person would be rejected by the machine due to improper orientation of the face towards the camera. In this work, we proposed a multi-layer perceptron based face identification technique which is robust to orientation of the face image under similar illumination condition. Training data of facial features against orientation angle features is used to train a Multi-Layer Perceptron (MLP). It is then used for interpolation of facial features at different angles. Experiments were conducted with two types of face image identifying features, using PCA and ICA. A good interpolation property could be obtained by the trained MLP, and a zero equal error rate (EER) could be achieved. © 2009 IEEE.
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    The fuzzy-based cluster head election algorithm for equal cluster size in wireless sensor networks
    (2016-11-18)
    Eak-Une, Pichatorn
    ;
    Pornavalai, Chotipat
    In Wireless Sensor Network (WSNs), clustering technique is widely used to balance energy usages consumed by the sensors. In each round of operation, a number of sensors are chosen to be candidate cluster head (CCHs) with a fixed and predefined probability value. CCHs then compete among themselves to become Cluster Head (CH) based on some criteria such as its remaining residual energy. CH role is rotated among sensors within the network field to balance their residual energy. However, area near to the corner and edge of the network field usually has less number of sensors to be CHs role than sensors located around center of the field. This will create energy holes problem on the area where sensors that needed to be CHs more often than others. Another problem is almost existing cluster head competition methods cannot precisely control the size of clusters in the networks. Depend on the spatial correlation of sensor nodes, this may impact the quality of data aggregation performed by the CHs. In this paper, we propose fuzzy based cluster head election algorithm (called FuzzCHE) to control and maintain cluster size while balance residual energy of sensors and extend the network lifetime. With FuzzCHE, each sensor can dynamically adjust probability that each sensor becomes CCH in each round by fuzzy logic. Comparing with existing cluster head election algorithm, results from simulations show that FuzzCHE can give more precise control of the average operated cluster size in the network to the deployed size required by the application.
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    Adaptive multi-hop routing for wireless sensor networks
    (2013-09-09)
    Tanessakulwattana, Sarayoot
    ;
    Pornavalai, Chotipat
    ;
    Chakraborty, Goutam
    A large portion of energy-aware routing protocol for wireless sensor networks are cluster-based. In cluster based approach, energy at the cluster head nodes are drained more rapidly compared to other member nodes. Dynamically change cluster heads periodically could partialy mitigate this problem, but clusters that are far from base station still suffer from large amount of energy for directly transmit their cluster data back to base station. Multi-hop routing was introduced to reduce energy dissipation of cluster heads that far away from base station by relaying data through nearer cluster heads. However it may overload cluster heads that are near the base station. In this paper, we propose an adaptive multi-hop hierarchical routing approach where member nodes in cluster may send their data, based on distance information, to cluster head or to base station directly to reduce energy dissipation of cluster heads. This decision is independent at each node which makes this approach highly distributed. Simulation results show that the proposed routing protocol has longer node lifetime than the original LEACH and M-LEACH protocol. © 2013 IEEE.
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    EORL: Energy Optimization via Reinforcement Learning in Software-Defined Wireless Sensor Networks
    (2024-01-01)
    Boonlert, Arnut
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    Pornavalai, Chotipat
    ;
    Tuwanut, Panwit
    ;
    Tanessakulwattana, Sarayoot
    A wireless sensor network is a collection of sensors placed in a particular area to collect and transmit data to the base station or sink. They usually have batteries as the primary power sources. If they work for a long time, their energy will be exhausted. Replacing the battery may not be cost-effective compared to developing an algorithm that optimizes energy efficiency to extend the network lifetime. This work optimizes the energy consumption of wireless sensor networks by adaptively selecting an optimal routing path in a Software-defined Wireless Sensor Networks (SDWSN) environment. A concept of the energy balance among nodes according to the current network status by the SDWSN controller using Reinforcement Learning (RL) is introduced. We propose energy optimization via reinforcement learning (EORL) for SDWSN using a minimum energy reward function and state design that considers energy consumption. The EORL algorithm then identifies the node that requires attention and selects the most energy-efficient path for that node. The performance of the EORL shows that it has a more extended network lifetime compared with other RL solutions.
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    A Simplified Analog Implementation of Cyclic Shift Chirp Encoding and Decoding for LoRa Communications
    (2026-06-01)
    Saelim, Nopparut
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    Tuwanut, Panwit
    ;
    Pornavalai, Chotipat
    Currently, LoRa wireless communication technology has become widely adopted in IoT systems due to its long-range capability and low power consumption. However, LoRa is a technology developed by Semtech, which does not disclose the details of the Cyclic Shift Chirp encoding process, a core component of LoRa signals. This lack of transparency prevents users from accessing the physical-layer structure of the signal or freely customizing key parameters such as bandwidth and spreading factor. Although such customization can enhance system flexibility, there is currently no officially disclosed method to achieve it. This research proposes a Cyclic Shift Chirp encoder/decoder circuit built from basic analog components, including adders, subtractors, comparators, and ramp generators, based on a Pulse Width Modulation (PWM) principle. This approach enables researchers and developers to generate LoRa-like signals independently and customize various parameters without introducing limitations. Moreover, the proposed circuit is simple, low-cost, and easy to understand, making it suitable for advanced research, educational experiments, and the design of communication systems that require high flexibility at the LoRa PHY layer.
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    Firewall rules analysis
    (2006-12-01)
    Chomsiri, Thawatchai
    ;
    Pornavalai, Chotipat
    In this paper, we propose a method to analyze the firewall policy or rule-set using Relational Algebra and Raining 2D-Box Model. It can discover all the anomalies in the firewall rule-set in the format that is usually used by many firewall products such as Cisco Access Control List, IPTABLES, IPCHAINS and Check Point Firewall-1. While the existing analyzing methods consider the anomalies between any two rules in the firewall rule-set, we consider more than two rules together at the same time to discover the anomaly. Therefore we can find all the hidden anomalies in the firewall rule-set. Results from analyzing can be used with the proposed rules-combination method presented in this paper, to minimize the firewall rule without changing the policy. Finally, we have developed an application based on the proposed analyzing method. This application could help administrator to analyze and modify a complex firewall policy with less error.
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    Fuzzy-spray: Efficient routing in delay tolerant ad-hoc network based on fuzzy decision mechanism
    (2009-01-01)
    Mathurapoj, Akadet
    ;
    Pornavalai, Chotipat
    ;
    Chakraborty, Goutam
    Delay Tolerant Network (DTN) is a sparse and intermittently connected mobile wireless network where reliable communication and end-to-end connectivity cannot be assured. In DTN, a node delivers messages to the destination using store and forward scheme. Messages are copied and transferred to multiple relay-nodes in order to increase the opportunity for that message to reach the intended destination. Contact is the time duration for which two or more mobile nodes encounter each other within their radio transmission ranges, and are able to transfer messages. Due to arbitrary node movement, contact time will be varied, and is unlikely to be predictable. In this paper, we propose a fuzzy decision mechanism we called "fuzzy-spray", to improve the routing and packet transfer efficiency in DTN environment. Fuzzy-spray can reduce overall latency in DTN by intelligently selecting appropriate messages to send to the relay-node during its next contact time. It uses fuzzy logic to prioritize messages that are stored in the buffer, based only on local parameters from each message, namely forward transmission count and message size. There is no need to know a priori information about network such as node mobility model, or node-distribution across the deployed area. The simulation results show that fuzzy-spray has the best performance in terms of overall speed of delivery, and lowest average message delay compared with other existing algorithms. ©2009 IEEE.
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    Multipath energy balancing for clustered wireless sensor networks
    (2019-07-01)
    Tanessakulwattana, Sarayoot
    ;
    Pornavalai, Chotipat
    In wireless sensor networks, sensors at different locations in the field use different energy levels to propagate sensing data back to the sink or base station. This causes unbalanced energy usage among sensors and also lowers the network lifetime. Currently there are several techniques to mitigate this problem, such as deploying multiple sinks, adding more sensors on heavy traffic areas, or managing the size of clusters depending on the distance from sensor to sink. In this paper, we propose a distributed algorithm and protocol called Multipath Energy Balancing (MEB) to mitigate unbalanced energy usage in clustered wireless sensor networks using multi-path and multi-hop, with a transmission power control approach. The network field is divided into regions, where the ratio of inter-region transmission traffic from all cluster head sensors in one region to other cluster head sensors in the two regions in front can be pre-computed and pre-programmed into the sensors to ease sensor deployment. To further prolong network lifetime, we also present a simple heuristic algorithm to procrastinate cluster formation and routing. Simulation results show that MEB can balance energy much better than Energy-efficient Clustering (EC) and Balancing Energy Consumption (BEC) solutions. It also has a longer network lifetime than EC and BEC protocols, especially when the required cluster size is small. Procrastinating cluster formation and routing also can further improve the network lifetime.
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    Proximity neighbor selection using IP prefix matching in Kademlia-based distributed hash table
    (2010-07-30)
    Sub-R-Pa, Chayanon
    ;
    Pornavalai, Chotipat
    KAD is one of the most popular Peer-to-Peer (P2P) networks on the Internet. It uses Kademlia-based Distributed Hash Tables (DHTs) to form a tree-structured P2P network. Iterative routing algorithm is used on Kademlia to perform key-value DHT lookup operation based on XOR distance of peer identifiers, which are randomized. Therefore the lookup operation might increase the lookup latency, as well as introduce a lot of cross-network traffic to other Internet Service Providers (ISPs). In this paper, we propose a new efficient proximity neighbor selection in Kademlia-based DHT. The locality among the peers is simply justified based only on the IP prefix matching of peers' IP addresses. Unlike other existing approaches, there are no needs of local database of geographic information about peers, or modification of peer identification structure. Results from simulation on 2000 nodes network show that the proposed technique can reduce both the lookup latency and cross network traffic significantly, comparing to the traditional Kademlia lookup algorithm.