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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 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 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)
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)
– This paper proposes an enhancement to an existing reputation method for indicating and avoiding malicious hosts in wireless ad hoc networks. The proposed method combines a simple reputation scheme with a reinforcement learning technique called the on-policy Monte Carlo method where each mobile host distributedly learns a good policy for selecting(More)
This paper addresses the call admission control (CAC) problem for multiple services in the uplink of a cellular system using direct sequential code division multiple access (DS-CDMA) when taking into account the physical layer channel and receiver structure at the base station. The problem is formulated as a semi-Markov decision process (SMDP) with(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)
This paper proposes a data acquisition scheme which aims to satisfy probabilistic confidence requirements of the acquired data in an error prone wireless sensor networks (WSNs). Given a statistical model of real-world sensor data and a user's query, the aim of the scheme is to find a sensor selection scheme which best refines the query answer with(More)