相关论文: FLBRA: Fuzzy Logic Based Routing Algorithm for Ind…

In this study, we propose a fuzzy system for conducting short-term transactions in the forex market. The system is designed to enhance common strategies in the forex market using fuzzy logic, thereby improving the accuracy of transactions.…

Federated learning (FL) offers a privacy-preserving collaborative approach for training models in wireless networks, with channel estimation emerging as a promising application. Despite extensive studies on FL-empowered channel estimation,…

As a promising technology in the Internet of Underwater Things, underwater sensor networks have drawn a widespread attention from both academia and industry. However, designing a routing protocol for underwater sensor networks is a great…

Carrier sensing multiple access/collision avoidance (CSMA/CA) is the backbone MAC protocol for IEEE 802.11 networks. However, tuning the binary exponential back-off (BEB) mechanism of CSMA/CA in user-dense scenarios so as to maximize…

An indoor, real-time location system (RTLS) can benefit both hospitals and patients by improving clinical efficiency through data-driven optimization of procedures. Bluetooth-based RTLS systems are cost-effective but lack accuracy and…

Estimation problems in wireless sensor networks typically involve gathering and processing data from distributed sensors to infer the state of an environment at the fusion center. However, not all measurements contribute significantly to…

Federated Learning (FL) allows devices to train a global machine learning model without sharing data. In the context of wireless networks, the inherently unreliable nature of the transmission channel introduces delays and errors that…

This paper investigates efficient distributed training of a Federated Learning~(FL) model over a wireless network of wireless devices. The communication iterations of the distributed training algorithm may be substantially deteriorated or…

This paper presents mathematical framework and study of proactive routing Protocols. The performance analysis of three major proactive routing protocols: Destination-Sequenced Distance Vector (DSDV), Fish-eye State Routing (FSR) and…

Load balancing is the process of improving the Performance of a parallel and distributed system through is distribution of load among the processors [1-2]. Most of the previous work in load balancing and distributed decision making in…

Fuzzy controllers are efficient and interpretable system controllers for continuous state and action spaces. To date, such controllers have been constructed manually or trained automatically either using expert-generated problem-specific…

Nowadays, demands for high performance keep on increasing in the wireless communication domain. This leads to a consistent rise of the complexity and designing such systems has become a challenging task. In this context, energy efficiency…

Effective traffic signal control (TSC) is crucial in mitigating urban congestion and reducing emissions. Recently, reinforcement learning (RL) has been the research trend for TSC. However, existing RL algorithms face several real-world…

To leverage massive distributed data and computation resources, machine learning in the network edge is considered to be a promising technique especially for large-scale model training. Federated learning (FL), as a paradigm of…

Current Gigabit-class passive optical networks (PONs) evolve into next-generation PONs, whereby high-speed 10+ Gb/s time division multiplexing (TDM) and long-reach wavelength-broadcasting/routing wavelength division multiplexing (WDM) PONs…

This paper develops a distributed algorithm for rate allocation in wireless networks that achieves the same throughput region as optimal centralized algorithms. This cross-layer algorithm jointly performs medium access control (MAC) and…

Volume and movement of data rapidly increasing in every type of data communications and networking, and ad hoc networks are not spared from these challenges. Traditional Multipath routing protocols in Mobile Ad-hoc Networks (MANETs) did not…

We advocate a new resource allocation framework, which we term resource rationing, for wireless federated learning (FL). Unlike existing resource allocation methods for FL, resource rationing focuses on balancing resources across learning…

We investigate cross-layer optimization to route information across distributed wireless body-to-body networks, based on real-life experimental measurements. At the network layer, the best possible route is selected according to channel…

One of the most vital activities to reduce energy consumption in wireless sensor networks is clustering. In clustering, one node from a group of nodes is selected to be a cluster head, which handles majority of the computation and…