Abdelhay Ali

An energy consumption model for wireless sensor networks

Energy consumption and energy modeling are important issues in designing and implementing of Wireless Sensor Networks (WSNs), which help the designers to optimize the energy consumption in WSN nodes. Good knowledge of the sources of energy consumption in WSNs is the first step to reduce energy consumption. Therefore, an accurate energy model is required for the evaluation of communication protocols. In this paper, we provide an energy model for WSNs considering the physical layer and MAC layer parameters by determining the energy consumed per payload bit transferred without error over AWGN channel. We show how the transmission power must be chosen in order to achieve energy-efficient communications over AWGN channel. We also find that, for each modulation scheme, there are optimal transmission power at which the energy consumption is minimized. Moreover, we investigated the energy saving gained from optimizing the constellation size.

C20. Energy consumption and lifetime analysis for Wireless Sensor Networks

Energy consumption and energy modeling are important issues in designing and implementing of Wireless Sensor Networks (WSNs), which help the designers to optimize the energy consumption in WSN nodes. Good knowledge of the sources of energy consumption in WSNs is the first step to reduce energy consumption. Therefore, an accurate energy model is required for the evaluation of communication protocols. In this paper, we present an energy analysis technique for WSNs considering the physical layer parameters by determining the energy consumed per payload bit transferred without error over AWGN channel. We show how the transmission power must be chosen in order to achieve energy-efficient communications over AWGN channel and provide a closed-form expression for optimum transmission power. We also find that, for each modulation scheme, there are optimal transmission power at which the energy consumption is minimized. The proposed model can be used to analyse the WSNs energy consumption, to evaluate communication protocols, and it can also use to estimate energy consumption and network lifetime which used for on-line energy accounting.

Design and implementation of building energy monitoring and management system based on wireless sensor networks

Wireless sensor networks (WSNs) play a key role in extending the smart grid implementation towards residential premises and energy management applications. Efficient supply and demand balance, and consequently reducing the electricity expenses and carbon emissions, is an immediate benefit of implementing smart grids. In this paper, design and implementation of an energy management system (EMS) for efficient load management are proposed. The EMS reduces the consumption of the consumers at the peak load hours and thus reduces the carbon emissions of the household. The proposed system consists of two main parts. The first part is an Energy Management Unit (EMU) which has a graphical user interface for runtime monitoring and control. The second part is sensor nodes which measure the power consumption of the different loads and transfer it to the EMU via multi-hop network. The EMU is implemented using NI LABVIEW software and XBee-PRO ZigBee module to communicate with sensor nodes. Hardware model is implemented using Arduino Uno microcontroller, XBee-PRO ZigBee module and the ACS712 current sensor. The EMS is applied to building of Electrical Engineering Department at Assiut University as a case study.

Optimization of Transmitted Power and Modulation Level for Minimizing Energy Consumption in Wireless Sensor Networks

Energy saving is one of the most important issues of wireless sensor networks (WSNs) that are gaining a lot of attention. In other words, energy modeling plays a greater role in energy optimization that helps designers to produce an economical and practical design of sensor nodes. In this paper, the issue of energy-efficient WSNs design is investigated by focusing on the setting of physical layer parameters. This is achieved by deriving an energy consumption model that considers most of the parameters of the physical layers. The proposed model is validated with real measurements to measure the accuracy of the proposed model. Results show good agreement between proposed model and experimental measurements with mean absolute percentage error less than 6%. The validated model is used to optimize transmitted power and modulation level to achieve minimum energy consumption. Finally, closed-form expressions for optimum transmitted power and modulation level are derived for different modulation schemes.

A fast accurate method for calculating symbol error probabilities for AWGN and Rayleigh fading channels

In order to improve the quality of communications systems, network researchers and designers need to understand the error performance of radio channels that influence the choice of coding and modulation schemes, and network architectures. Symbol and bit error probabilities are great methods to measure the performance of the radio channels. However, in many cases the exact expressions of symbol and bit error probabilities are very complex due to the diversities of error environments in a wireless channel. Thus, it is beneficial to have simple approximate expressions, to simplify expression manipulations. In this paper, simplified expressions for the symbol error probability over AWGN and Rayleigh fading channels are presented which are found to be in good agreement with the original expressions. More precisely, the simplified expressions are in the form of one term exponential and rational functions for AWGN and Rayleigh fading channels, respectively.

Modeling and minimization of energy consumption in wireless sensor networks

Design of energy-efficient wireless sensor networks (WSNs) has become an important area of scientific research. In this regard, modeling and minimizing of energy consumption are the main objectives for designing WSNs. In this paper, an energy consumption model for WSNs based on physical layer parameters is proposed by calculating the total energy that is required for successfully received one bit over Rayleigh fading channels. The proposed energy consumption model is validated with real measurements. Results show a good agreement between proposed model and experimental measurements with a mean absolute percentage error less than 5.5%. The validated model is used to optimize transmitted power to achieve minimum energy consumption. Finally, a closed-form expression for optimum transmitted power is derived for M-QAM modulation scheme.

Modeling and optimization of energy consumption in Wireless Sensor Networks

Energy consumption and energy modeling are important issues in designing and implementing of Wireless Sensor Networks (WSNs), which help the designers to optimize the energy consumption in WSN nodes. Good knowledge of the sources of energy consumption in WSNs is the first step to reduce energy consumption. Therefore, an accurate energy model is required for the evaluation of communication protocols. In this paper, an energy model for WSNs is provided considering the physical layer and MAC layer parameters by determining the energy consumed per payload bit transferred without error over AWGN channel. This model has been tested with real data and and NS-2 simulator. Results show good agreement between proposed model, experimental measurements and NS-2 simulator with mean absolute percentage error less than 5.18%. Furthermore, the proposed model is exploited to optimize transmitted power to achieve minimum energy consumption. Finally, a closed-form expression for optimum transmitted power is derived for M-QAM modulation scheme.