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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
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Tuwanut, Panwit
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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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An efficient dynamic multicast routing algorithm with advance resource reservation awareness
(2004-06-28)
Pavarangkoon, Praphan
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Gunabhibal, Apipol
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Pornavalai, Chotipat
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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.
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Routing Timing Effect on the Performance of Multimedia Network
(2002-12-01)
Sathitwiriyawong, Chanboon
;
Wanvilai, Pattana
This paper presents the performance study of routing timing effect on the performance of multimedia networks. Since routing timing is a major factor on the performance of adaptive distributed routing, selecting an appropriated value of this parameter can enhance the total network performance. The simulation results show that the decrease in the value of routing timing can reduce both data packet transfer delay and its delay variation. Both routing approaches, link state algorithm (LSA) and path finding algorithm (PFA), have impact on delay variation, but not its mean delay. LSA can also achieve lower delay variation than PFA. Moreover, using a routing scheme that has a rapid route update process, such as LSA, can slightly improve network performance. Despite high workload conditions, both LSA and PFA can achieve data packet transfer delay within the bound acceptable for all interactive multimedia communications. Besides, frequent checks for routing update do not incur much overhead. Therefore, small routing timing is always preferable.

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