OF-EC: A novel energy consumption aware objective function for RPL based on fuzzy logic.

2018 ◽  
Vol 117 ◽  
pp. 42-58 ◽  
Author(s):  
Hanane Lamaazi ◽  
Nabil Benamar
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Objective Function

scholarly journals An Optimization Scheme Based on Fuzzy Logic Control for Efficient Energy Consumption in Hydroponics Environment

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 289 ◽  
Author(s):  
Azimbek Khudoyberdiev ◽  
Shabir Ahmad ◽  
Israr Ullah ◽  
DoHyeun Kim
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Objective Function ◽  
Fuzzy Logic Control ◽  
World Population ◽  
Optimization Scheme ◽  
Efficient Energy ◽  
Logic Control ◽  
The World ◽  
The Cost

As the world population is increasing rapidly, food and water demands are the most crucial problem for humanity. In some areas of the world, water or environment is unsuitable for plant growth; hydroponic systems can provide a suitable environment for crop production with effective management of natural resources. Internet of Things paradigm based automated systems has been creating an excellent opportunity for monitoring and controlling agriculture by minimizing the cost and maximizing the profit significantly over the past decade. The reduction of the cost can be achieved by sufficient usage of resources and setting up optimum operational parameters for agricultural devices. This paper presents an optimization scheme with novel objective function for hydroponics environment parameters management with efficient energy consumption. The proposed approach provides optimal energy and resource utilization in the hydroponics system with setting up a working level and operational duration to the actuators. We have developed an optimization scheme with objective function for optimal humidity and water level control based on fuzzy logic, which can support the optimal measurement for crop growth with energy efficiency. Fuzzy logic control is applied for the compromise between actuators working level and operational duration. A real hydroponics environment has been implemented and presented to evaluate the effectiveness of the proposed approach. It can be assessed through the simulation results that the optimization module achieves a signification reduction (18%) in energy consumption as compared to the other scheme.

Probabilistic and Fuzzy based Efficient Routing Protocol for Mobile Ad Hoc Networks

2020 ◽  
Vol 13 (3) ◽  
pp. 422-432
Author(s):  
Madan Mohan Agarwal ◽  
Hemraj Saini ◽  
Mahesh Chandra Govil
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Routing Protocol ◽  
Queue Length ◽  
Ad Hoc ◽  
Fuzzy Controller ◽  
Second Phase ◽  
Path Distance ◽  
Fixed Threshold ◽  
Multiple Paths

Background: The performance of the network protocol depends on number of parameters like re-broadcast probability, mobility, the distance between source and destination, hop count, queue length and residual energy, etc. Objective: In this paper, a new energy efficient routing protocol IAOMDV-PF is developed based on the fixed threshold re-broadcast probability determination and best route selection using fuzzy logic from multiple routes. Methods: In the first phase, the proposed protocol determines fixed threshold rebroadcast probability. It is used for discovering multiple paths between the source and the destination. The threshold probability at each node decides the rebroadcasting of received control packets to its neighbors thereby reducing routing overheads and energy consumption. The multiple paths list received from the first phase and supply to the second phase that is the fuzzy controller selects the best path. This fuzzy controller has been named as Fuzzy Best Route Selector (FBRS). FBRS determines the best path based on function of queue length, the distance between nodes and mobility of nodes. Results: Comparative analysis of the proposed protocol named as "Improved Ad-Hoc On-demand Multiple Path Distance Vector based on Probabilistic and Fuzzy logic" (IAOMDV-PF) shows that it is more efficient in terms of overheads and energy consumption. Conclusion: The proposed protocol reduced energy consumption by about 61%, 58% and 30% with respect to FF-AOMDV, IAOMDV-F and FPAOMDV routing protocols, respectively. The proposed protocol has been simulated and analyzed by using NS-2.

Type 2 Fuzzy Logic based Unequal Clustering algorithm for multi-hop wireless sensor networks

2020 ◽  
pp. 33-46
Author(s):  
A. Sariga ◽  
◽  
◽  
J. Uthayakumar
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Hot Spot ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Clustering Protocols ◽  
Hot Spot Problem

Wireless sensor network (WSN) is an integral part of IoT and Maximizing the network lifetime is a challenging task. Clustering is the most popular energy efficient technique which leads to increased lifetime stability and reduced energy consumption. Though clustering offers several advantages, it eventually raises the burden of CHs located in proximity to the Base Station (BS) in multi-hop data transmission which makes the CHs near BS die earlier than other CHs. This issue is termed as hot spot problem and unequal clustering protocols were introduced to handle it. Presently, some of the clustering protocols are developed using Type-2 Fuzzy Logic (T2FL) but none of them addresses hot spot problem. This paper presents a Type-2 Fuzzy Logic based Unequal Clustering Algorithm (T2FLUCA) for the elimination of hot spot problem and also for lifetime maximization of WSN. The proposed algorithm uses residual energy, distance to BS and node degree as input to T2FL to determine the probability of becoming CHs (PCH) and cluster size. For experimentation, T2FLUCA is tested on three different scenarios and the obtained results are compared with LEACH, TEEN, DEEC and EAUCF in terms of network lifetime, throughput and average energy consumption. The experimental results ensure that T2FLUCA outperforms state of art methods in a significant way.

scholarly journals A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1023 ◽  
Author(s):  
Khadak Singh Bhandari ◽  
Gi Hwan Cho
Keyword(s):  
Fuzzy Logic ◽  
Objective Function ◽  
Smart City ◽  
Contextual Information ◽  
Network Dynamics ◽  
Residual Energy ◽  
Smart Devices ◽  
Route Selection ◽  
Network Simulator ◽  
Lossy Networks

Internet of Things (IoT) is expected to have a significant impact on city’s service provisioning and make a smart city more accessible and pragmatic since the deployment of heterogeneous smart devices in each infrastructure of cities is increasing. So far, the IPv6 routing protocol for low power and lossy networks (RPL) is considered to fit on IoT infrastructure for achieving the expected network requirements. While RPL meets the IoT network requirements quite well, there are some issues that need to be addressed, such as adaptability to network dynamics. This issue significantly limits the use of RPL in many smart city application scenarios, such as emergency alerts with high traffic flows. As part of a smart city vision, IoT applications are becoming more diverse, which requires context-awareness in routing protocols to support the behavior of the network. To address this issue, we design an objective function that performs the route selection based on fuzzy logic techniques while using contextual information from the application. For this, we present a new context-oriented objective function (COOF) that comprises both nodes as well as link metrics. Further, we suggest two new routing metrics, known as queue fluctuation index (QFI) and residual energy index (REI), which consider the status of queue utilization and remaining energy, respectively. The metrics used are designed to respond to the dynamic needs of the network. The proposed approach has been examined and evaluated in different scenarios when compared to other similar approach and default RPL objective functions. Simulation experiments are conducted in Cooja network simulator for Contiki OS. The evaluation results show that COOF can cope with network dynamics and IoT-based smart city application requirements.

Decision support for evaluating energy demand in vinification processes using fuzzy sets theory

2006 ◽  
Vol 17 (4) ◽  
pp. 4-18 ◽  
Author(s):  
N Musee ◽  
L Lorenzen ◽  
C Aldrich
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Current Trend ◽  
High Energy ◽  
Production Costs ◽  
Wine Industry ◽  
Process Industries ◽  
Industrial Growth

The current trend associated with high energy demand, depletion of energy reserves and low potential of renewable energy sources linked with strong industrial growth, is increasingly becoming unsustainable. As a result, production costs have increased considerably in the process industries, mainly owing to skewed energy demand and supply realities. A feasible strategy for meeting these challenges is to reduce energy consumption per unit throughput. However, to obtain a workable solution, decision makers may have to deal with energy management variables that are ambiguous, which makes solving the energy minimization problem with conventional numerical approaches very difficult. In this paper, we consider an alternative approach based on fuzzy logic to qualitatively evaluate the energy demand associated with an industrial cooling process. The model was formulated based on Mamdani fuzzy logic inferencing and implemented in MATLAB 6.5 via the Fuzzy Logic toolbox. The energy demands pertaining to specific variables were independently estimated, followed by an estimate of the overall energy consumption. The procedure is demonstrated via a case study of cooling at the maceration stage of a vinification process in the wine industry.

scholarly journals A Novel Clustering Approach in Wireless Sensor Network Using Genetic Algorithm and Fuzzy Logic

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Fatemehzahra Gholami Tirkolaei ◽  
Faramarz E. Seraji
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Challenge ◽  
Clustering Approach ◽  
Reduce Energy Consumption ◽  
Reduction Of Energy Consumption

<p>Wireless sensor network consists of hundred or thousand sensor nodes that are connected together and work simultaneously to perform some special tasks. The restricted energy of sensor nodes is the main challenge in wireless sensor network as node energy depletion causes node death. Therefore, some techniques should be exerted to reduce energy consumption in these networks. One of the techniques to reduce energy consumptions most effectively is the use of clustering in wireless sensor networks.</p><p>There are various methods for clustering process, among which LEACH is the most common and popular one. In this method, clusters are formed in a probabilistic manner. Among clustering strategies, applying evolutional algorithm and fuzzy logic simultaneously are rarely taken into account. The main attention of previous works was energy consumption and less attention was paid to delay.</p><p>In the present proposed method, clusters are constructed by an evolutional algorithm and a fuzzy system such that in addition to a reduction of energy consumption, considerable reduction of delay is also obtained. The simulation results clearly reveal the superiority of the proposed method over other reported approaches.</p>

scholarly journals The Methodology of the Department of Fuel and Energy Resources of the Enterprise Based on Fuzzy Logic

2019 ◽  
pp. 153-158 ◽  
Author(s):  
Valeriya Е. Osipova ◽  
Dmitrij А. Yakovlev
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Energy Resources ◽  
Effective Model ◽  
Model Of Management

The paper proposed an effective model of management of fuel and energy enterprises, developed on the basis of fuzzy logic, allowing to minimize the risks associated with incorrect forecasting of energy consumption, allowing to consider not only quantitative but also qualitative indicators of the enterprise

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