Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Frequency domain features of inertial movement enables multi-resolution analysis for fall detection, yet they are computationally intensive. This paper proposes a computationally light frequency domain feature extraction method based on lifting wavelet transform (LWT) which provides computational efficiency suitable for real-time low power devices such as wearable sensors for human fall detection...
Wireless healthcare monitoring sensor networks are multi-hop Zigbee-based systems which usually use broadcast or multicast to reliably deliver vital diagnostics information or event detection to the sink. However, such schemes typically lead to high network traffic and large path search delay. This paper presents an efficient, adaptive, distributed routing mechanism, called anycast Q-routing to route...
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 framework has been proposed in conjunction with...
The main function of biomedical sensor network is to guarantee that the data packets from patients can be delivered reliably to the destination node or medical center. Attached to patients, these nodes can be mobile, thus forming a mobile wireless sensor network (mWSN). Moreover, non-cooperative nodes may also be present in the network. This paper therefore proposes a routing method for non-cooperative...
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 anomaly detection algorithm in WSNs which can...
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 (CVCP). We also studied their effects on...
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 process (POMDP) and is solved using an actor-critic...
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 revenue function than existing routing methods...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.