Chapter Efficient Node Placement for Congestion Control in Wireless Sensor Networks

Geology & the lithospher

Efficient Node Placement for Congestion Control in Wireless Sensor Networks

Geology & the lithospher

Distributed Artificial Intelligence Solution for D2D Communication in 5G Networks

Device to Device (D2D) Communication is one of the technology components of the evolving 5G architecture, as it promises improvements in energy efficiency, spectral efficiency, overall system capacity, and higher data rates. The above noted improvements in network performance spearheaded a vast amount of research in D2D, which have identified significant challenges that need to be addressed before realizing their full potential in emerging 5G Networks. Towards this end, this paper proposes the use of a distributed intelligent approach to control the generation of D2D networks. More precisely, the proposed approach uses Belief-Desire-Intention (BDI) intelligent agents with extended capabilities (BDIx) to manage each D2D node independently and autonomously, without the help of the Base Station. The paper includes detailed algorithmic description for the decision of transmission mode, which maximizes the data rate, minimizes the power consumptions, while taking into consideration the computational load. Simulations show the applicability of BDI agents in jointly solving D2D challenges.Comment: 10 pages,9 figure

Utilizing Mobile Nodes for Congestion Control in Wireless Sensor Networks

Congestion control and avoidance in Wireless Sensor Networks (WSNs) is a subject that has attracted a lot of research attention in the last decade. Besides rate and resource control, the utilization of mobile nodes has also been suggested as a way to control congestion. In this work, we present a Mobile Congestion Control (MobileCC) algorithm with two variations, to assist existing congestion control algorithms in facing congestion in WSNs. The first variation employs mobile nodes that create locally-significant alternative paths leading to the sink. The second variation employs mobile nodes that create completely individual (disjoint) paths to the sink. Simulation results show that both variations can significantly contribute to the alleviation of congestion in WSNs.Comment: 9 pages, 12 figures, 1 tabl

A Simulation tool to evaluate Radio Resource Management algorithms for Enhanced UMTS

Abstrac

Joint Radio Resource Allocation and Beamforming Optimization for Industrial Internet of Things in Software-Defined Networking-Based Virtual Fog-Radio Access Network 5G-and-Beyond Wireless Environments

Fog computing-based radio access network (Fog-RAN) leveraging the software-defined networking (SDN) and network function virtualization (NFV) is the most promising solution to offer real-time support for the massive number of connected devices in the industrial Internet of Things (IIoT) networks. However, designing an optimal dynamic radio resource allocation to handle the fluctuating traffic loads is critical. In this article, a novel architectural design of an SDN-based virtual Fog-RAN is proposed, in which we jointly study radio resource allocation and transmit beamforming to improve resource utilization and IIoT users’ satisfaction, by minimizing the network power consumption (NPC) and maximizing the achievable sum-rate (ASR), simultaneously. To this end, we first formulate a mixed-integer nonlinear problem to optimize the physical resource block allocation, the assignment of user equipments, and radio unit, and the downlink transmit beamforming, by considering imperfect channel state information. To solve the ntractable MINLP, we exploit the successive convex approximation approach. Then, we formulate a multiple knapsack problem (MKP) to optimize the assignment between RUs and virtual baseband units, by exploiting the set of active RUs minimized in the previous problem. We solve the formulated MKP by decomposing the dual problems and solving them through the dual descent method. Through performance analysis, we show the proposed approach provides a high users’ satisfaction rate, maximizes the ASR and minimizes the NPC, and provides better savings, in terms of the number of radio and baseband resources utilized, than its counterparts

Performance Control in Wireless Sensor Networks

Most of the currently deployed wireless sensor networks applications do not require performance control. The goal of the GINSENG project is sensor networks that meet application-specific performance targets, in particular with respect to latency and reliability. We present scenarios within the GALP oil re¿nery where the system will be deployed and some initial technical insights with respect to deterministic communication

On the use of programmable metasurfaces in vehicular networks

Metasurface-based intelligent reflecting surfaces constitute a revolutionary technology which can serve the purpose of alleviating the blockage problem in mmwave communication systems. In this work, we consider the hypersurface paradigm complementing the software defined metasurface with an embedded controller network in order to facilitate the dissemination of reconfiguration directives to unit cell controllers. For the first time, we describe the methodology with which to characterize the workload within this embedded network in the case of the metasurface tracking multiple users and we use a vehicular communications setting to showcase the methodology. Beyond that, we demonstrate use cases of the workload analysis. We show how the workload characterization can guide the design of information dissemination schemes achieving significant reduction in the network traffic. Moreover, we show how the workload, as a measure of the consumed power, can be used in designing energy efficient communication protocols through a multi-objective optimization problem maximizing the achieved utilization while at the same time minimizing the workload incurred.Peer ReviewedPostprint (author's final draft

Intelligent Beam Steering for Wireless Communication Using Programmable Metasurfaces

Reconfigurable Intelligent Surfaces (RIS) are well established as a promising solution to the blockage problem in millimeter-wave (mm-wave) and terahertz (THz) communications, envisioned to serve demanding networking applications, such as 6G and vehicular. HyperSurfaces (HSF) is a revolutionary enabling technology for RIS, complementing Software Defined Metasurfaces (SDM) with an embedded network of controllers to enhance intelligence and autonomous operation in wireless networks. In this work, we consider feedback-based autonomous reconfiguration of the HSF controller states to establish a reliable communication channel between a transmitter and a receiver via programmable reflection on the HSF when Line-of-sight (LoS) between them is absent. The problem is to regulate the angle of reflection on the metasurface such that the power at the receiver is maximized. Extremum Seeking Control (ESC) is employed with the control signals generated mapped into appropriate metasurface coding signals which are communicated to the controllers via the embedded controller network (CN). This information dissemination process incurs delays which can compromise the stability of the feedback system and are thus accounted for in the performance evaluation. Extensive simulation results demonstrate the effectiveness of the proposed method to maximize the power at the receiver within a reasonable time even when the latter is mobile. The spatiotemporal nature of the traffic for different sampling periods is also characterized

An integration framework and a signaling protocol for MPLS/DiffServ/HMIP radio access networks

Ph.D.Henry L. Owe