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    Item type:Publication,
    EORL: Energy Optimization via Reinforcement Learning in Software-Defined Wireless Sensor Networks
    (2024-01-01)
    Boonlert, Arnut
    ;
    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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    Item type:Publication,
    An efficient dynamic multicast routing algorithm with advance resource reservation awareness
    (2004-06-28)
    Pavarangkoon, Praphan
    ;
    Gunabhibal, Apipol
    ;
    Pornavalai, Chotipat
    ;
    Varakulsiripunth, Ruttikorn
    Reserving the resources for the requested applications is one of the most effective schemes that were proposed to offer the time-critical multimedia applications recently. Because the resource is limited, an ability to provide resource reservation in advance is essential in multi-party applications with dynamic accessing and leaving of user such as modern integrated (voice, video and data) collaboration system. Modified Greedy (MG) algorithm was proposed for multicast routing in advance reservation environment (time of joining in and leaving from multicast group need to be informed to source node). However, MG algorithm has an assumption that member of multicast group join in and leave from multicast session punctually. In this work, we propose the late version of MG algorithm that yields a good performance in the situation that the inaccuracy of information given by user might be happened, as shown in our simulation results.