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Proceedings ArticleDOI

Off-Grid Wi-Fi Mesh Systems

TL;DR: In this paper , an off-grid energy Wi-Fi mesh system for remote areas is proposed, and the system is self-powered, and to ensure 24 hours energy production, a hybrid solution of vertical wind turbine and the solar cell is used.
Abstract: To transmit information from a source to a destination without interruption from electromagnetic interference, a strong wireless network connection is required. These wireless networks may be powered by direct current from a battery or a direct source. The challenge arises when a wireless network is installed at a remote location. In this paper, an off-grid energy Wi-Fi mesh system for remote areas is proposed. The system is self-powered, and to ensure 24 hours energy production, a hybrid solution of vertical wind turbine and the solar cell is used. Dedicated routers are designed using Raspberry Pi, and other supporting electronic circuitry and results are analyzed. To avoid bandwidth issues, the network offloading concept is exploited using a novel concept of power used by each node. The proposed system is portable and suitable for remote areas where grid-connected energy availability is an issue.
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Journal ArticleDOI
TL;DR: The problem of network-wide energy consumption minimization under the network throughput constraint is formulates as a mixed-integer nonlinear programming problem by jointly optimizing routing, rate control, and power allocation and the min-max fairness model is applied to address the fairness issue.
Abstract: The increasing demand for wireless services has led to a severe energy consumption problem with the rising of greenhouse gas emission. While the renewable energy can somehow alleviate this problem, the routing, flow rate, and power still have to be well investigated with the objective of minimizing energy consumption in multi-hop energy renewable wireless mesh networks (ER-WMNs). This paper formulates the problem of network-wide energy consumption minimization under the network throughput constraint as a mixed-integer nonlinear programming problem by jointly optimizing routing, rate control, and power allocation. Moreover, the min-max fairness model is applied to address the fairness issue because the uneven routing problem may incur the sharp reduction of network performance in multi-hop ER-WMNs. Due to the high computational complexity of the formulated mathematical programming problem, an energy-aware multi-path routing algorithm (EARA) is also proposed to deal with the joint control of routing, flow rate, and power allocation in practical multi-hop WMNs. To search the optimal routing, it applies a weighted Dijkstra's shortest path algorithm, where the weight is defined as a function of the power consumption and residual energy of a node. Extensive simulation results are presented to show the performance of the proposed schemes and the effects of energy replenishment rate and network throughput on the network lifetime.

85 citations

Journal ArticleDOI
TL;DR: By considering the first and second order statistics of the energy charging and discharging processes at each mesh AP, it is demonstrated that the proposed schemes outperform some existing state-of-the-art solutions.
Abstract: There is a growing interest in the use of renewable energy sources to power wireless networks in order to mitigate the detrimental effects of conventional energy production or to enable deployment in off-grid locations. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity. The dynamics of energy supply hence impose new challenges for network planning and resource management. In this paper, the sustainable performance of a wireless mesh network powered by renewable energy sources is studied. To address the intermittently available capacity of the energy supply, adaptive resource management and admission control schemes are proposed. Specifically, the goal is to maximize the energy sustainability of the network, or equivalently, to minimize the failure probability that the mesh access points (APs) deplete their energy and go out of service due to the unreliable energy supply. To this end, the energy buffer of a mesh AP is modeled as a G/G/1(/N) queue with arbitrary patterns of energy charging and discharging. Diffusion approximation is applied to analyze the transient evolution of the queue length and the energy depletion duration. Based on the analysis, an adaptive resource management scheme is proposed to balance traffic loads across the mesh network according to the energy adequacy at different mesh APs. A distributed admission control strategy to guarantee high resource utilization and to improve energy sustainability is presented. By considering the first and second order statistics of the energy charging and discharging processes at each mesh AP, it is demonstrated that the proposed schemes outperform some existing state-of-the-art solutions.

63 citations

Journal ArticleDOI
TL;DR: This paper proposes a resource-provisioning algorithm based on the use of temporal shortest-path routing and taking into account the node energy flow for the target deployment time period, and introduces a methodology that incorporates energy-aware routing into the resource-assignment procedure.
Abstract: Solar-powered wireless mesh nodes must be provisioned with a solar panel and battery combination that is sufficient to prevent node outage. This is normally done using historical solar insolation data for the desired deployment location and based on a temporal bandwidth usage profile (BUP) for each deployed node. Unfortunately, conventional methodologies do not take into account the use of energy-aware routing, and therefore, the deployed system may be overprovisioned and unnecessarily expensive. In this paper, we consider this resource assignment problem with the objective of minimizing the network deployment cost for a given energy source assignment. We first propose a resource-provisioning algorithm based on the use of temporal shortest-path routing and taking into account the node energy flow for the target deployment time period. We then introduce a methodology that incorporates energy-aware routing into the resource-assignment procedure. A genetic algorithm (GA) has been developed for this purpose. Our results show the large cost savings that an energy-aware resource assignment can achieve when compared with that done using the conventional methodology. To evaluate the quality of the resource assignments, we also develop a linear programming formulation that gives a lower bound on the total network resource assignment. Our results show that significant resource savings are possible using the proposed algorithms and the potential resource assignment benefits of energy-aware routing.

53 citations

Journal ArticleDOI
07 Feb 2020-Energies
TL;DR: The objective of this work is to analyze the performance of the proposed energy model in routing protocols of diverse nature: reactive, proactive, hybrid and energy-aware.
Abstract: In this study, a Wireless Sensor Network (WSN) energy model is proposed by defining the energy consumption at each node. Such a model calculates the energy at each node by estimating the energy of the main functions developed at sensing and transmitting data when running the routing protocol. These functions are related to wireless communications and measured and compared to the most relevant impact on an energy standpoint and performance metrics. The energy model is validated using a Texas Instruments CC2530 system-on-chip (SoC), as a proof-of-concept. The proposed energy model is then used to calculate the energy consumption of a Multi-Parent Hierarchical (MPH) routing protocol and five widely known network sensors routing protocols: Ad-hoc On-demand Distance Vector (AODV), Dynamic Source Routing (DSR), ZigBee Tree Routing (ZTR), Low Energy Adaptive Clustering Hierarchy (LEACH), and Power Efficient Gathering in Sensor Information Systems (PEGASIS). Experimental test-bed simulations were performed on a random layout topology with two collector nodes. Each node was running under different wireless technologies: Zigbee, Bluetooth Low Energy, and LoRa by WiFi. The objective of this work is to analyze the performance of the proposed energy model in routing protocols of diverse nature: reactive, proactive, hybrid and energy-aware. Experimental results show that the MPH routing protocol consumes 16%, 13%, and 5% less energy when compared to AODV, DSR, and ZTR, respectively; and it presents only 2% and 3% of greater energy consumption with respect to the energy-aware PEGASIS and LEACH protocols, respectively. The proposed model achieves a 97% accuracy compared to the actual performance of a network. Tests are performed to analyze the consumption of the main tasks of a node in a network.

46 citations

Journal ArticleDOI
12 Dec 2019-Energies
TL;DR: In this paper, the design, simulation, and optimization of a stand-alone photovoltaic system (SAPV) to provide non-polluting electrical energy based on a renewable source for a rural house located in Tazouta, Morocco.
Abstract: Access to clean and affordable energy in rural African regions can contribute greatly to social development. Hence, this article proposes the design, simulation, and optimization of a stand-alone photovoltaic system (SAPV) to provide non-polluting electrical energy based on a renewable source for a rural house located in Tazouta, Morocco. Real monthly electrical demands and hourly climatic conditions were utilized. An initial design process indicated that, with a 1080 Wp total capacity of PV modules and 670 Ah of battery storage, the proposed SAPV system was able to meet a considerable part of the dwelling load with an average solar fraction of about 79.1%. The rest of the energy demand was ensured by a diesel generator (DG). Also, a life cycle analysis of the PV system revealed that the life cycle cost is 10,195.56 USD and the unit electricity cost is 0.57 USD/kWh for an initial investment of 4858.68 USD. Thereafter, an optimum design based on Homer Pro software was carried out indicating that lower PV capacity can decrease the unit energy cost to 0.356 USD/kWh while reducing the solar fraction to 54.9%.

38 citations