Wipawee Usaha

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In this paper, we develop and assess online decision-making algorithms for call admission and routing for low Earth orbit (LEO) satellite networks. It has been shown in a recent paper that, in a LEO satellite system, a semi-Markov decision process formulation of the call admission and routing problem can achieve better performance in terms of an average(More)
This paper proposes a path discovery scheme which supports delay-constrained least cost routing in MANETs. The aim of the scheme is to maximise the probability of success in finding feasible paths while maintaining communication overhead under control in presence of information uncertainty. The problem is viewed as a partially observable Markov decision(More)
Data readings from wireless sensor networks (WSNs) may be abnormal due to detection of unusual phenomena, limited battery power, sensor malfunction, or noise from the communication channel. It is thus, important to detect such data anomalies available in WSNs to determine a suitable course of action. This paper proposes an integrated data compression and(More)
One of the preconditions to guarantee the quality of service (QoS) of cellular mobile networks is the rapid and accurate detection of key performance index (KPI) anomalies. This paper applies a neural network algorithm called self-organizing map (SOM) to monitor traffic measurement anomalies collected from an actual cellular network service provider.(More)
This paper proposes to promote cooperative routing for homogeneous mobile wireless sensor networks (mWSNs) using a scalable, distributed incentive-based mechanism with reasonable resource requirements using reinforcement learning (RL). In particular, Q-learning which is a well-known RL method was integrated an existing Continuous Value Cooperation Protocol(More)
This paper proposes a sensor selection scheme for data acquisition which supports probabilistic confidence requirements in wireless sensor networks (WSNs). The aim of the scheme is to optimize the long-term performance criterion in data collection while maintaining data reliability under error-prone WSNs. We formulate the problem as a partially observable(More)
This paper proposes the performance comparison for optimal traffic signal controls based on the following two frameworks: M/M/1 and D/D/1 queueing models, and Q-learning approach. Firstly, using the M/M/1 and D/D/1 models, the optimal split derivation has been obtained to minimise the mean waiting time of an intersection. Additionally, the Q-learning(More)
In this paper, a path discovery scheme which supports QoS routing in mobile ad hoc networks (MANETs) in the presence of imprecise information is investigated. The aim is to increase the probability of success in finding feasible paths and reduce average path cost of a previously proposed ticket based probing (TBP) path discovery scheme. The proposed scheme(More)