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The purpose of this paper is to search an energy balance routing in the wireless sensor networks (WSN) and lengthen the life of the networks.

To save energy in the WSN, some routing protocols search routing with the minimum total energy consumption of the network, and others reduce data redundancy by data aggregation. But if the distribution of energy consumption was not even, the energy of some nodes would be exhausted rapidly and thus the whole network would break down. Thus, an energy balance routing notion, including communication energy cost of the routing, remaining energy of communication sensors and sensor load have been involved. Then a new algorithm, mouse colony optimization and simulated annealing (SA), is advanced to solve the problem of energy balance routing in the network.

The energy balance routing, based on mouse colony optimization and SA, performs well and yields better performance than other congener algorithms.

The appointed times of the algorithm is the main limitation which increase the complexity of the algorithm.

A very useful routing in wireless sensor networks.

The new approach of energy balance routing notion, including communication energy cost of the routing, remaining energy of communication sensors and sensor load. The new algorithm, mouse colony optimization algorithm, simulated mice action, was proposed to solve the energy balance routing of the network.

The purpose of this paper is to compare well‐known technologies of sludge utilization on the basis of energy and economical balances of real processes. The calculations are based on pilot tests in the Central Waste Water Treatment Plant (CWWTP) in Prague, the biggest waste water treatment plant in the Czech Republic.

A key issue for the comparison of mass and energy flow of sludge management is the attainable level of sludge dewaterability. Results of dewatering of anaerobic digested sludge are available from real applications since most sewage plants use digesters. The existing limited knowledge about mixed raw sludge (MRS) dewaterability have driven authors to make pilot tests targeted to establishment of an attainable level of MRS dewaterability. To get as close results as possible even anaerobic stabilized sludge was dewatered and various other data were collected to obtain a comprehensive data set for energy balance of the sludge management calculation. The pilot tests took place at CWWTP in 2005. Measured data were used to calculate energy balance of a number of different sludge managements.

To produce self‐reliant combusting sludge, a dry matter content of 35‐45 per cent for MRS and 45‐55 per cent for digested sludge has to be achieved by means of dewatering and potentially drying. In recent measurements at CWWTP a dry matter content of about 33 per cent was achieved by dewatering of MRS. This value is very close to the range of the dry matter content at which a self reliant combustion can be expected.

This comparison together with investment cost analysis should be one of the most important parameters in case of design a new or revamp an old waste water treatment plant.

The paper provides results from pilot tests at CWWTP together with three different energy balances comparison.

Renewable energy is at the forefront of countries’ concerns due to its global economic and environmental impacts. Previous studies have thoroughly examined the impact of renewable energy on overall national income, and this paper aims to shed light on an indicator that has received insufficient attention in research regarding its impact on economic growth, using data from 2000 to 2018.

This study examines the causal relationship between trade balance, renewable energy consumption and CO₂ emissions per capita in Organization for Economic Cooperation and Development (OECD) countries using an auto regression distributed lag model (ARDL) and Johansen Cointegration Test.

The findings reveal that there is evidence of a long-run and short-run cointegrating relationship and that renewable energy consumption in the long run impacts the trade balance positively and in the short run negatively.

Therefore, bioenergy trade between countries and local investment should be prioritized to increase the trade balance surplus, since many of OECD countries suffer from deficit problems.

This paper presents a new discretization technique of the hydrodynamic energy balance model based on a finite‐element formulation. The concept of heat source lumping is introduced, and the thermal conductivity model includes the effect of varying both carrier concentrations and temperatures. The energy balance equation is formulated to account for kinetic energy as a convective flow. The new discretization method has the advantage that it allows for assembling the functions out of elementary variables available over elements instead of along element links. Therefore, theoretically, calculation of the Jacobian should be three times faster than by the classic method. Results are given for three examples. The method suffers from mathematical instabilities, but provides a good basis for future work to solve these problems.

Wireless sensor networks (WSNs) have emerged as one of the most promising technology in our day-to-day life. Limited network lifetime and higher energy consumption are two most critical issues in WSNs. The purpose of this paper is to propose an energy-efficient load balanced cluster-based routing protocol using ant colony optimization (LB-CR-ACO) which ultimately results in enhancement of the network lifetime of WSNs.

The proposed protocol performs optimal clustering based on cluster head selection weighing function which leads to novel cluster head selection. The cluster formation uses various parameters which are remaining energy of the nodes, received signal strength indicator (RSSI), node density and number of load-balanced node connections. Priority weights are also assigned among these metrics. The cluster head with the highest probability will be selected as an optimal cluster head for a particular round. LB-CR-ACO also performs a dynamic selection of optimal cluster head periodically which conserves energy, thereby using network resources in an efficient and balanced manner. ACO is used in steady state phase for multi-hop data transfer.

It has been observed through simulation that LB-CR-ACO protocol exhibits better performance for network lifetime in sparse, medium and dense WSN deployments than its peer protocols.

The proposed paper provides a unique energy-efficient LB-CR-ACO for WSNs. LB-CR-ACO performs novel cluster head selection using optimal clustering and multi-hop routing which utilizes ACO. The proposed work results in achieving higher network lifetime than its peer protocols.

Energy use in buildings needs to be reduced to meet political goals; however, reducing energy use can conflict with heritage preservation objectives. The purpose of this paper is to demonstrate a method that combines quantitative and qualitative analyses of the potential of energy savings in an historic building stock. Specifically, this study examines how requirements of historic building preservation affect the energy saving potential on a building stock level.

Using the World Heritage Town of Visby, Sweden as a case study, this paper illustrates a step-by-step method as a basis for implementing energy savings techniques in an historic building stock. The method contains the following steps: categorisation of a building stock, definition of restriction levels for energy renovation scenarios and life cycle costs optimisation of energy measures in archetype buildings representing the building stock. Finally, this study analyses how different energy renovation strategies will impact heritage values and energy saving potentials for different categories of buildings.

The outcome of the study is twofold: first, the method has been tested and proven useful and second, the results from the application of the method have been used to formulate differentiated energy renovation strategies for the case study.

The study shows that it is possible to integrate techno-economic analysis with assessment of heritage values in a given building stock in order to facilitate a strategic discussion balancing policies and targets for energy savings with policies for the preservation of heritage values. The findings will contribute to sounder policy development and planning for historic building stocks.

This paper aims to develop the Dragonfly-based exponential gravitational search algorithm to VMM strategy for effective load balancing in cloud computing. Due to widespread growth of cloud users, load balancing is the essential criterion to deal with the overload and underload problems of the physical servers. DEGSA-VMM is introduced, which calculates the optimized position to perform the virtual machine migration (VMM).

This paper presents an algorithm Dragonfly-based exponential gravitational search algorithm (DEGSA) that is based on the VMM strategy to migrate the virtual machines of the overloaded physical machine to the other physical machine keeping in mind the energy, migration cost, load and quality of service (QoS) constraints. For effective migration, a fitness function is provided, which selects the best fit that possess minimum energy, cost, load and maximum QoS contributing toward the maximum energy utilization.

For the performance analysis, the experimentation is performed with three setups, with Setup 1 composed of three physical machines with 12 virtual machines, Setup 2 composed of five physical machines and 19 virtual machines and Setup 3 composed of ten physical machines and 28 virtual machines. The performance parameters, namely, QoS, migration cost, load and energy, of the proposed work are compared over the other existing works. The proposed algorithm obtained maximum resource utilization with a good QoS at a rate of 0.19, and minimal migration cost at a rate of 0.015, and minimal energy at a rate of 0.26 with a minimal load at a rate of 0.1551, whereas with the existing methods like ant colony optimization (ACO), gravitational search algorithm (GSA) and exponential gravitational search algorithm, the values of QoS, load, migration cost and energy are 0.16, 0.1863, 0.023 and 0.29; 0.16, 0.1863, 0.023 and 0.28 and 0.18, 0.1657, 0.016 and 0.27, respectively.

This paper presents an algorithm named DEGSA based on VMM strategy to determine the optimum position to perform the VMM to achieve a better load balancing.

Load balancing is an effective enhancement to the proposed routing protocol, and the basic idea is to share traffic load among cluster members to reduce the dropping probability due to queue overflow at some nodes. This paper aims to propose a novel hierarchical approach called distributed energy efficient adaptive clustering protocol (DEACP) with data gathering, load-balancing and self-adaptation for wireless sensor network (WSN). The authors have proposed DEACP approach to reach the following objectives: reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network, the clustering must be completely distributed, the clustering should be efficient in complexity of message and time, the cluster-heads should be well-distributed across the network, the load balancing should be done well and the clustered WSN should be fully connected. Simulations show that DEACP clusters have good performance characteristics.

A WSN consists of large number of wireless capable sensor devices working collaboratively to achieve a common objective. One or more sinks [or base stations (BS)] which collect data from all sensor devices. These sinks are the interface through which the WSN interacts with the outside world. Challenges in WSN arise in implementation of several services, and there are so many controllable and uncontrollable parameters (Chirihane, 2015) by which the implementation of WSN is affected, e.g. energy conservation. Clustering is an efficient way to reduce energy consumption and extend the life time of the network, by performing data aggregation and fusion to reduce the number of transmitted messages to the BS (Chirihane, 2015). Nodes of the network are organized into the clusters to process and forwarding the information, while lower energy nodes can be used to sense the target, and DEACP makes no assumptions on the size and the density of the network. The number of levels depends on the cluster range and the minimum energy path to the head. The proposed protocol reduces the number of dead nodes and the energy consumption, to extend the network lifetime. The rest of the paper is organized as follows: An overview of related work is given in Section 2. In Section 3, the authors propose an energy efficient level-based clustering routing protocol (DEACP). Simulations and results of experiments are discussed in Section 4. In Section 5, the authors conclude the work presented in this paper and the scope of further extension of this work.

The authors have proposed the DEACP approach to reach the following objectives: reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network, the clustering must be completely distributed, the clustering should be efficient in complexity of message and time, the cluster-heads should be well-distributed across the network, the load balancing should be done well, the clustered WSN should be fully connected. Simulations show that DEACP clusters have good performance characteristics.

The increasing energy shortage leads to worldwide attentions. This paper aims to develop a mathematical model and optimization algorithm to solve the energy-oriented U-shaped assembly line balancing problem. Different from most existing works, the energy consumption is set as a major objective.

An improved flower pollination algorithm (IFPA) is designed to solve the problem. The random key encoding mechanism is used to map the continuous algorithm into discrete problem. The pollination rules are modified to enhance the information exchange between individuals. Variable neighborhood search (VNS) is used to improve the algorithm performance.

The experimental results show that the two objectives are in conflict with each other. The proposed methodology can help manager obtain the counterbalance between them, for the larger size balancing problems, and the reduction in objectives is even more significant. Besides, the experiment results also show the high efficiency of the proposed IFPA and VNS.

The main contributions of this work are twofold. First, a mathematical model for the U-shaped assembly line balancing problem is developed and the model is dual foci including minimized SI and energy consumption. Second, an IFPA is proposed to solve the problem.

The purpose of this study was to determine body composition, energy balance and tendencies towards eating disorders of female competitive athletes in two countries, USA and Greece. Data were collected using similar methodology in both countries during the non‐competitive (training) and the competitive seasons. Forty‐two athletes and 11 controls in the USA and 35 athletes and ten controls in Greece participated in the study. Comparison of the results between the countries showed that US athletes weighed more than Greek athletes but there was no significant difference in the percentage of body fat between the two groups. No significant differences were found in the energy intakes between athletes in either country. Athletes appeared to be in negative energy balance (‐380 to ‐580 kcals daily) in both seasons, in both countries.