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Author: search.filters.author.Tanessakulwattana, Sarayoot

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    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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    A Novel Precomputed Optimal Procrastination Time Interval for Re-Clustering to Maximize Operation Time of Wireless Sensor Networks
    (2023-09-01)
    Pornavalai, Chotipat
    ;
    Tanessakulwattana, Sarayoot
    ;
    Chakraborty, Goutam
    In wireless sensor networks, the energy consumption of sensors is not uniform over the whole region of deployment. The uneven energy usage occurs because some sensors have to transmit data to farther distances or have to transmit more data packets than others. This leads to a shorter duration of operation because some sensors' energy will deplete fast creating holes in the network. To alleviate this problem, we proposed an algorithm we named Procrastinated Clustering and Multi-Hop Routing (PCMR). To prolong the operation, it will optimally assign sensors with different precomputed procrastination periods to schedule the clustering and routing processes. In PCMR, sensors' clustering and routing intervals depend on their locations in the network with respect to the sink. The algorithm could reduce and balance energy consumption for sensors distributed over a wide area. Procrastination periods are precomputed off-line before deployment. Therefore, it is easy to implement and is efficient, even for a large network for which real-time reorganization would involve transmitting a large number of signaling packets. The results from simulations show that the proposed PCMR algorithm could balance energy usage among sensors, and prolong the network lifetime compared to existing works based on techniques such as adjusting cluster size and/or multi-path transmission.
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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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    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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    Optimal multi-path energy-aware routing protocol for wireless sensor networks
    (2012-10-02)
    Tanessakulwattana, Sarayoot
    ;
    Pornavalai, Chotipat
    ;
    Chakraborty, Goutam
    ;
    Naik, Sagar
    A large portion of energy-aware routing protocol for wireless sensor networks are cluster-based. In cluster based approaches, power of the cluster head (CH) nodes are drained more rapidly compared to other member nodes. Dynamic CH approach could partially alleviate this problem. But even with dynamic CH approach, energy is not uniformly dissipated among all nodes. In this paper, we propose a new energy-aware routing protocol where the communication protocol is such that, even when the clusters are fixed, power dissipation is same over all nodes (except CHs). Every node co-operates with each other to carry the payload to the CH so as the power dissipation is uniform. Therefore reconfiguration of cluster is not necessary, thereby saving a huge signalling cost and interruption in service. Simulation results show that the proposed protocol has longer node lifetime and better distribution of energy dissipation than the original LEACH protocol. © 2012 IEEE.