Energy Efficient Resource Allocation and Deployment Strategies for Wireless Networks

As the extension of cloud computing, multi-access edge computing (MEC) can better support applications to accomplish larger tasks. Existing works on energy optimization of MEC systems fail to utilize multi-relay diversity, which plays a vital role to reduce the computing power consumption of mobile devices by leveraging different offloading modes. In this paper, we propose a novel computing architecture with multi-source, multi-relay, and a single edge server in an orthogonal frequency division multiplexing access (OFDMA) wireless network. The application task on a mobile device can be calculated locally, offloaded to the relay device and completed on the relay device, offloaded to the edge server directly or via a relay device with cooperative communication and executed in the edge server. The two optimization targets are total energy consumption minimization problem, and maximum energy consumption per source-relay pair devices minimization problem. For the first sub-problem, we design an optimal total energy consumption algorithm (OTCA) based on bipartite matching. The optimal energy consumption assignment algorithm (OECAA) is designed for the second sub-problem with an approximation ratio of (1+e). Extensive simulation results show that OTCA outperforms random algorithm by 53.14% on the reduction of total energy consumption, and algorithm OECAA outperforms OTCA by 30.58% on the reduction of maximum energy consumption per source-relay pair devices.

Energy intensity is one of the most important energy feature that has a dramatic value in energy system of Iran. Indeed, Iran is one of the most energy intensive countries in the world and its main reason is related to high energy consumption in household section. In this article, we present a non-linear model that considers three scenarios in management of household energy demand reducing. Therefore, a rational percentage of energy consumption reduction in the household sector, which firstly eliminates the imbalance between energy production and consumption, and secondly, derives a rational amount of profit from various reduction scenarios, will be presented. The mentioned rational profits in this article are obtained from three scenarios. In the first scenario, it is assumed that the percentage reduction in household energy consumption will be allocated to reducing energy demand in the industrial sector, resulting in profits from value-added creation in this sector. In the second scenario, all benefits from reducing energy consumption in the household sector will be devoted to energy exports, yielding profits from this source. Finally, in the third scenario, the reduction in energy consumption will lead to a decrease in energy supply and consequently a reduction in energy supply costs. To conduct a comprehensive study, a combination of the mentioned scenarios has also been modeled and investigated. The model results indicate that with a 25% reduction in household energy consumption in the 2024-2034 timeframe, the energy imbalance will be eliminated, and allocating 5% of this reduction entirely to the industrial sector will result in profits equivalent to $164.18 billion. However, it should be noted that in the considered combined scenarios, the greater the share of the first scenario, the higher the resulting profit, and the optimal point is achieved in the first scenario.

The total energy consumption in the U.S. has been rising steadily for decades, and it currently amounts to ~98,000 TBtu/yr, with approximately 30% of this total attributable to the industrial sector. Reasonable estimates indicate that 45–55% of total industry energy consumption derives from chemical separations, and for example, over 120 TBtu/yr alone is used in carrying out olefin/paraffin separations via energy-intensive cryogenic distillation. Therefore, the pursuit of new, even radically different approaches to some of the most energy-intensive industrial separations processes is an imperative scientific pursuit for reducing energy consumption toward a more sustainable future. Adsorbent and membrane-based separations can require a fraction of the energy needed for distillation methods, and as such are considered promising solutions for balancing increasing energy demand in the U.S. with the need for a massive reduction in energy consumption. Although considerable research effort has been devoted to the design of materials capable of carrying out various gas separations, usually operating through size-selective, chemisorptive, or physisorptive mechanisms, it remains a great challenge to design materials that function adequately for real-world applications. Indeed, the chemical and physical differences between molecules in gas mixtures of interest are often small, and therefore it is necessary, through the use of nanoscience and synthetic chemistry, to engineer unprecedented molecular-level control in adsorbate–adsorbent interactions. The overarching mission of the Center for Gas Separations (CGS) was to discover fundamental innovations that have the potential to dramatically reduce the energy associated with critical gas separations. In particular, the CGS developed novel synthetic routes, guided by molecular chemistry principles, as well as advanced characterization and computational methods, that have enabled the discovery of new materials and membranes tailor-made to exhibit exceptional performance for a range of gas separations processes, as required in the clean use of fossil fuels and in reducing CO2 emissions from industry. A challenge of this magnitude required the collaboration and synergy of a large team of researchers with expertise in materials synthesis, characterization, and computations. During the 11-year project period, the CGS created a range of new materials within the family of highly-tunable, porous solids known as metal–organic frameworks (MOFs). These new frameworks demonstrate novel mechanisms for key industrial gas separations, including revolutionary new cooperative adsorption processes that enable low-energy CO2 and CO capture, and are capable of efficiently separating olefins from paraffins, O2 from air, and the shape-selective separation of alkane isomers. In addition, the CGS developed new strategies for incorporating these materials into composite membranes toward highly efficient and selective membrane-based separations. As a testament to the success of the CGS, two start-up companies, Mosaic Materials,4 Inc. and Flux Technology, Inc., grew out of these research efforts, and these companies are seeking to commercialize MOF and composite membranes materials for key separations in industry, including large-scale CO2 capture and hydrocarbon separations, respectively. Another company, framergy, Inc., licensed IP resulting from CGS research toward the commercialization of adsorbents for various energy-relevant applications.

The Global energy consumption and carbon footprint related to operating mobile phones in wireless networks is increasing significantly. In order to determine the overall energy consumption of a wireless network, both the operation of the network infrastructure and the devices connected to that network must be considered. Although the larger part of the global energy consumption of wireless networks is consumed at base station sites and access points, a significant part is consumed from the operation of mobile phones. In this paper, system level power consumption models for mobile phones in terms of 2G, 3G and Wi-Fi are presented. The developed model increases the accuracy of the current power profiles by considering different stages of a single transmission, including the variables affecting each stage. The power states of wireless interfaces, maintenance, network attachment/detachment and network resource allocation policies of different network operators are also considered to obtain a complete model that can accurately predict that power consumption at every stage of connectivity. A comparison between power consumption of different radio access technologies is also included to promote energy efficient use of spectrum. Using the system level power models presented in this paper, the contribution of the operation of mobile phones to overall energy consumption of wireless communication networks can be determined.

The high quality of life in the modern sense is directly related to energy consumption and associated with the provision of «clean» food products and environment, comfortable housing, public and private transport. Increasing the availability of energy for the developing countries allows their residents to live longer and more comfortably. At the same time, in the developed European countries with high quality of life, energy consumption is decreasing due to the implementation of energy efficiency and energy saving policies. The Human Development Index, the world’s best-known and most widely used integrated assessment of quality of life, does not include energy consumption indicators. The aim of our research is to study the relationship between energy consumption and quality of life, and prove the need to consider energy consumption indicators in order to improve the methodology framework for assessing quality of life. Using the method of cluster analysis, 77 countries of the world are grouped according to a set of indicators that characterize income, energy consumption, use of renewable energy sources, and CO2 emissions. As a result, the relationship between the level of human development, which is a universal characteristic of quality of life, and these indicators was identified and evaluated. It has been proved that the most prosperous countries in terms of quality of life and energy use are those in which relatively low indicators of primary energy consumption and CO2 emission are combined with high incomes and human development level. The progressive structure of energy consumption ensures the achievement of a higher quality of living, while high energy consumption is not a sufficient condition for this. Against the background of low levels of total primary energy consumption and GDP per capita, CO2 emissions, as well as a low share of renewable energy in total energy consumption, high quality of life is present mainly in the «new» EU member states, which provide it through rational energy consumption. The average level of human development is inherent in a group of countries of the former USSR (which includes Ukraine), as well as some countries in Latin America, the Middle East and Southeast Asia. At the same time, countries such as China and South Korea are reducing energy consumption owing to technological progress and have a positive dynamics of human development indicators. Instead, low levels of energy consumption in the former Soviet Union and Latin America are due to insufficient sustainability of economic and social development, human development in particular. The obtained results substantiate the need to improve the methodology for assessing the quality of life taking into consideration energy consumption indicators.

The rapid development of urbanization has led to a rapid increase in total energy consumption. The proportion of domestic energy consumption to total energy consumption has gradually increased and has become the major driving force for energy consumption. With the pressure from urbanization and domestic energy consumption, it is necessary to study the impact of urbanization on domestic energy consumption of the regional level and to explore the function paths of these two factors. The findings are helpful to realize sustainable development based on the actual situation analysis, horizontal survey data and statistical yearbook panel data. The current situation and changing trends in domestic energy consumption of Shandong Province are systematically examined through field investigation and survey questionnaire. The time-series econometric model is applied to analyze the relationship between urbanization rate and total domestic energy consumption. The research results show that the total domestic energy consumption and urbanization rate of Shandong are generally increasing. The urbanization rate development and domestic energy consumption have a long-term stable and balanced relationship. An increase in urbanization rate can cause an increase in domestic energy consumption. There is a slight difference between the average total energy consumption levels of urban and rural residents, but their energy consumption structures differ a lot. These findings provide basic data support and reference for local governments to formulate energy- conservation and emission-reduction policies.

Recently, the cooperative communication has been explored more and more as an impressing technique to combat the effects of channel fading and to reduce the energy consumption in wireless networks. However, the impact of cooperative communications on transmission rate has not been well-addressed yet. In this paper, we provide an analytical framework for transmission rate enhancement issue in wireless communications. For a given transmit power and a desired probability of success, we investigate how much average transmission rate can be increased by cooperative communications. Three transmission models have been compared: the direct transmission, the cooperative transmission without maximal ratio combiner (MRC), and cooperative transmission with MRC. The analytical and numerical results show that around 1 - 3b/s/Hz transmission rate can be improved when the source-destination distance is 20m. We also reveal that the MRC scheme is not always beneficial, especially when the source-destination distance is short and the relay is close to the destination.

Water quality is a crucial factor in maintaining the survival and growth of shrimp. Manual water quality monitoring in shrimp ponds is no longer effective due to the need for periodic monitoring to maintain stable water quality. Therefore, online monitoring using various sensors installed in each pond is necessary. However, there are several challenges to overcome, such as the large expanse of the shrimp ponds, which may lead to data loss due to signal disruptions, and limited energy to power the sensors. To address these issues, this paper proposes the cooperative Wireless Sensor Network (WSN) technique with a multi-hop method for communication in the monitoring process. The system consists of five sensor nodes: temperature sensor, pH sensor, water level sensor, intake water flow sensor, and drain water flow sensor. The cooperative WSN multi-hop technique helps reduce energy consumption in the sensor nodes during measurement and data transmission, while also preventing data packet loss. This is achieved through the use of relay nodes that strengthen signals and forward data to the sink node. As a result, the battery life is extended, and energy usage in the monitoring process can be optimized. The system enables real-time online monitoring and can be accessed through a smartphone application. The results of this study show that the total energy consumption for data transmission in the sensor nodes is 9.64 J, while the total energy consumption for data forwarding in the relay nodes is 9.15 J. The total energy consumption in the transmit and receive processes is 18.79 J or 5.2 mWh. Therefore, it can be concluded that the energy savings of the proposed system is 4.3 mWh or approximately 45%, and is more efficient than the previous system.

Currently in China, the energy consumption of buildings is increasing rapidly. In this study, we used a macro-model to forecast the energy consumption of buildings in Shanghai through 2050. Total energy consumption from 2000 to 2050 and the potential energy savings were projected for both the residential and commercial sectors. For urban residential buildings, we developed a forecast model for 2050 to estimate the potential energy savings of residential measures. Compared to the business-as-usual (BaU) scenario, implementation of residential measures achieved a 24% reduction in energy consumption. The reduction rate rose to 65% by combining the implementation of residential and electrical measures. For commercial buildings, we first used official statistical data to determine the energy intensities of air conditioning, lighting, computing, and other thermal uses for the base year 2000. Then, estimates of the labor force, GDP, and floor area were predicted through 2050 according to past growth patterns and the literature. Likewise, estimates for energy intensities through 2050 were projected. Energy-saving scenarios also were integrated into the commercial model. Compared to BaU scenario, implementation of commercial measures achieved an 80% reduction in energy consumption. The reduction rate increased to 99% by combining commercial and electrical measures.

To better construct an energy consumption model for the asphalt mixture production stage, this study divides the production process into four phases: aggregate dust removal, aggregate drying, asphalt heating, and mixture blending. Utilizing measured data from various regions in Anhui Province, the model considers factors such as season, mixture type, and energy consumption type. The study quantitatively compares and analyzes the energy consumption results obtained from three calculation methods: the theoretical method, the quota method, and the energy consumption model method. The results indicate that the total energy consumption shares of the aggregate dust removal, aggregate drying, asphalt heating, and mixture blending phases are 4.23%, 69.50%, 17.75%, and 8.52%, respectively. The primary energy consumption during the asphalt mixture production stage is concentrated in the aggregate drying and asphalt heating phases. The energy consumption model based on on-site measurements effectively reflects the actual energy consumption levels during the asphalt mixture production stage. Moreover, the total energy consumption calculated by the three methods follows the order quota method > energy consumption model method > theoretical method. By constructing an energy consumption model based on measured data, it is possible to more accurately assess the energy usage during the asphalt mixture production process. This helps optimize production techniques, reduce energy consumption and carbon emissions, and provide a scientific basis for sustainable road construction.

Process planning can be deemed as an important component in manufacturing systems. It bridges the gap between designing and manufacturing by specifying the manufacturing requirements and details to convert a part from raw materials to the finished form. For the purpose of low carbon emission, this paper pays attention to both technical performance measures and environmental impact criteria. In this problem, a part may have more than one process plans and only one process plan can finally be adopted. Due to the non-deterministic polynomial-hardness, it is rather difficult to conduct operation selection, machine determination, operation sequencing, and energy consumption reduction simultaneously with various constraints from technical requirements or the shop floor status. A novel position-based mixed integer linear programming model is developed to reduce total production time and the total energy consumption. The energy consumption coefficient matrix is proposed to evaluate the energy consumption in process planning. Because of the complexity in solving the model, this research proposes dynamic programming-like heuristic algorithm to tackle this problem. The weighted sum method is applied in multi-objective optimization and three typical instances with operation flexibility, sequencing flexibility, and processing flexibility are used to test the proposed algorithm. According to the results, both the total production time and the energy consumption criteria are optimized; in the best case, the energy consumption after optimization takes only 21.2% of the one before optimization. On average, about 40.9% of the total energy consumption can be reduced after optimization. Computational results also show that the proposed algorithm is generally better than the genetic algorithm. This research gives a novel perspective to reduce energy consumption in the process planning stage.

Energy retrofit analysis of cross-laminated timber residential buildings in Seoul, Korea: Insights from a case study of packages

An effective technique to reduce energy consumption in wireless sensor networks (WSNs) is to make use of cooperative communications between nodes. In this technique, all nodes contribute to the transmission of data as senders and may transmit their data through relay nodes instead of sending directly to the receivers. This paper has the goal of reducing energy consumption. In this way, two wasted energies are considered, including the consumption for data transfer between any given pair of nodes and the same for end-to-end data transfer. In practice, the problem can be modeled as an optimization problem. However, finding the solution for this problem needs large resources such as memory and processing units. We propose a multi-objective genetic algorithm to solve this problem. The proposed algorithm balances the per-hop energy consumption with the end-to-end ones using the Pareto analysis. The simulations show that the proposed method offers acceptable results in comparison with the optimization model. However, the proposed algorithm can be solved in a shorter time.

A quantitative analysis of the impact of residential cluster layout on building heating energy consumption in cold IIB regions of China

Ensuring the efficiency of the use of nutrients of grain, protein, vitamin and mineral feeds in the composition of complete feed mixtures in animal husbandry and crop production, as well as the corresponding reduction in the cost of manufacturing of these products, is the relevance of the presented research and prospects for their development. Therefore, the purpose of the study is to substantiate the effective regime parameters for the preparation of premixes of feed mixtures based on the assessment of the energy parameters of the vibration mixing process. This assessment was carried out by comparing the results of applying vibration, blade, and vibroblade technological operations. Under the conditions of low-frequency vibrations, a decrease in the working resistance of the loosened layer of the mixture is observed, which provided the effect of reducing energy consumption in this process. Therefore, in comparison with conventional vibrating mixers have a higher specific productivity of 5-6 times, provide a reduction in the mixing time by 2-3 times, metal consumption – by 17%, energy consumption – by 30%, capital costs for manufacturing – by 18%, and drive power – by 30-35%, which leads to a reduction in total energy consumption by 3-4 times. As a result, the zone of minimal energy consumption was substantiated, in which the reduction of the resistance of the technological medium allowed radically reducing the friction forces during mixing, while ensuring uniform distribution with the concentration of the components of the mixture required by technological requirements. An increase in the oscillation amplitude is accompanied by a quadratic increase in power consumption, which is conditioned by an increase in energy dissipation in the mass of the mixture in the form of heat. The implementation of reasonable operating mixing modes allowed reducing the energy consumption of the proposed vibro-blade mixing by 2.0-2.5 times compared to conventional blade processing. The practical value of these developments includes the use of vibro-blade working bodies and the vibration-free operation of the drive shaft, which, together with the minimisation of energy consumption for the process, reduces dynamic loads on the support units of the developed mixer