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In this paper the optimal surface area of an air-to-air plate heat exchanger is determined. The analysis is based on input data obtained by measurement in real operating conditions in board producing paper machine in Belgrade, Serbia. For that purpose effectiveness-NTU method together with previously defined cost functions was applied, taking into account seasonal variations in the parameters of exhaust and fresh atmospheric air. In addition, the total net savings in the consumption of primary energy sources in the factory that can be achieved by applying an optimised system for the use of waste heat were calculated and a simple payback period of the investment was determined.

The last decade has witnessed an impressive paradigm shift in practically all networking fields: from hardware-based appliances to software-based infrastructures. Network functions traditionally hard-coded in the network devices have been redesigned in software and deployed in virtualized networking scenarios, with impressive advantages in terms of management flexibility and upgradable capability. Still, at a time in which we strive for more and more network processing and computing resources, such a softwarization process risks to bring about a severe toll in terms of performance and energy consumption. We believe, and posit, that programmable hardware architectures tailored for supporting high performance network processing tasks may come to the rescue. With this position paper, after motivating our position, we further briefly review the past and present of programmable hardware for networking, and we discuss its possible evolution towards more comprehensive "higher layer" HW-accelerated processing tasks.

Pulp and paper industry is a highly energy intensive and the drying section of the paper machine consumes 64 % of total energy. The heat of the humid hot air resulting from the drying process has a usable energy potential which has to be recovered and represents a secondary energy resource. This paper analyses efficiency of introducing a complex heat recovery, in three stages, integrated into the drying process of the paper production technology line. The type of recovery used is an interior recuperation in the first and third stage due to the fact the energy contained by the secondary energy resources, namely the heat of the exhausted hot air from the drying process, is recovered within the process itself. In the second stage, the secondary energy resource has an energetic potential since it is used to maintain the microclimate in the industrial hall. The performed energy analysis is leading to conclusions regarding the methodology for establishing the optimal regime of operation.

Internet-of-Things (IoT) devices can only afford very small batteries due to the size, weight, power and cost constraints. On the other hand, long battery life is expected for such devices, either for improving user experience or due to charging limitations. Therefore, it is critical to reduce the energy consumption of IoT devices. A good opportunity is to save energy on the system level, by letting the system to sleep occasionally. In this paper, we introduce Image Partitioning and Incremental Loading (IPIL), an operating-system-level sleep mechanism used in Huawei LiteOS to reduce the energy consumption of an IoT device. IPIL powers off both the CPU and the main memory during sleep to save as much energy as possible. Thus, system data have to be reloaded after the system wakes up, which may take a long time and thus reduce real-time responsiveness. To solve this problem, IPIL partitions the system image into clusters and incrementally loads the clusters on-demand, reducing the amount of data loading and time overhead in the wake-up step. Experimental results show that IPIL outperforms two widely adopted sleep approaches in terms of energy consumption. At the same time, IPIL offers satisfactory responsiveness with very short wake-up delay. We also present a case study on smart watch to demonstrate how battery life, as a core value of wearable devices, can be improved with IPIL provided by LiteOS.

Employee's green behavior plays a pivotal role in reducing waste in the environment and sustaining the natural resources for the next generation. It is also significant in scientific labs due to the substantial energy consumption and waste generated in labs. Based on the existing literature, this paper re-caps the definitions of green behavior in workplace stated by various researchers. Scales developed by previous researchers to measure the employee's green behavior are discussed in this paper.

Intermittent systems enable continuous and accumulative process execution under constraint or unstable power supply. To enable intermittent computing, process status and data are typically checkpointed from volatile memory (VM) to nonvolatile memory (NVM) before running out of power. After power resumes, these logged data can be loaded back from NVM to VM for continuous execution. Nevertheless, existing approaches rarely considered the energy consumed during moving data and may waste precious power resource over data movement, instead of computation. Such observation motivates us to propose an energy-reduction on-chip memory management (ERCM2) scheme to utilize the high cell density and non-volatility of SpinTransfer Torque RAM (STT-RAM) for enabling a hybrid on chip memory architecture. The experimental results show that the proposed scheme can achieve the access performance close to conventional SRAM-based on-chip memory architecture with lower energy consumption.

This work considers sustainable scheduling of manufacturing operations and preventive maintenance activities in a single-machine environment where the machine works continuously in three eight-hour shifts per day. The jobs can be produced at different processing speeds, which reduces energy consumption and/or processing times. In a tri-objective mixed integer linear programming model, sustainability is attained through minimizing total weighted earliness/ tardiness - economic pillar, total energy consumption - environmental pillar, and number of undesired activities - social pillar. Moreover, a multi-objective genetic algorithm finds near optimal solutions in a timely manner. Numerical results will be presented at the conference.

Based on the sequential batch reactor (SBR) simulation model of the wastewater treatment process for a secondary fiber paper mill that we have developed, two control strategies, a neural network (BP-PID controller) and a fuzzy logic system (Fuzzy-PID controller), were separately combined with PID to control the dissolved oxygen (DO) concentration in the SBR process of paper mill. Two cases, without and with the presence of noise, have been studied and evaluated using the criteria considered in BSM1. For the case without noise, both two-control strategies demonstrated better control indices than that of the traditional PID control; for the case with noise, the Fuzzy-PID controller possessed the good control indices at almost the same expense of aeration energy. The results under two cases showed that the Fuzzy-PID controller demonstrated better performance than that of BP-PID controller, in the DO control of SBR process in the paper mill, Fuzzy-PID controller improved the control performance without increasing the aeration energy consumption.

Modern society relies on smart systems like internet of things (IoT) and cyber physical systems (CPS) to monitor and control physical processes. The widespread deployment of IoT and CPSs result in fast growth of sensor data as physical processes are constantly monitored by billions of IP-enabled sensors (44 zettabytes by 2020). Hence, fog nodes are deployed to make network edge rich in computing resources to enable real-time data analytics using artificial intelligence/machine learning (AI/ML) for Big data generated from IoT and CPSs. This paper proposes IoT/CPS ecosystem for smart grid (SG) utilizing industry 4.0 concept to manage and control the loads using an intelligent predictive controller based on artificial neural network (ANN). The ANN is trained to predict the loads in certain districts based on previous smart meter readings installed at consumers and substations. This is a novel approach which integrates IoT/CPSs ecosystem into electric power system to deliver energy to consumers with high efficiency, reduce the cost, optimize the energy consumption, improve the reliability and enable real-time monitoring of power consumption.

Aggressive use of low power modes in embedded systems using emerging non-volatile or low power compute state retainable devices can greatly reduce its power consumption of idle-state[1]. However, in general, non-volatile devices require comparatively large power to switch between the stable states. Therefore, to realize extremely low power mobile platforms with powerful multimedia application processor running solely on photovoltaic-power, mitigating power consumption of its active-state is the next issue. Replacing power hungry conventional LCDs with non-volatile displays is inevitable in realizing such low power platforms, but naive replacement is insufficient. As such, low power control cognizant of non-volatile device properties is necessary[2]. We propose a display update request scheduling scheme designed for a promising non-volatile display: Electronic Paper Display(EPD) and give deep analysis of power consumption. Proposed scheme dynamically rearranges update requests ill-suited for EPDs to localized and collision-free low power consuming requests at the device driver level, reducing EPD-based tablet's energy consumption by up to 49% without requiring application specific modifications.

Mobile crowdsensing (MCS) is a distributed sensing paradigm that uses a variety of built-in sensors in smart mobile devices to enable ubiquitous acquisition of sensory data from surroundings. However, non-dedicated nature of MCS results in vulnerabilities in the presence of malicious participants to compromise the availability of the MCS components, particularly the servers and participants' devices. In this paper, we focus on Denial of Service attacks in MCS where malicious participants submit illegitimate task requests to the MCS platform to keep MCS servers busy while having sensing devices expend energy needlessly. After reviewing Artificial Intelligence-based security solutions for MCS systems, we focus on a typical location-based and energy-oriented DoS attack, and present a security solution that applies ensemble techniques in machine learning to identify illegitimate tasks and prevent personal devices from pointless energy consumption so as to improve the availability of the whole system. Through simulations, we show that ensemble techniques are capable of identifying illegitimate and legitimate tasks while gradient boosting appears to be a preferable solution with an AUC performance higher than 0.88 in the precision-recall curve. We also investigate the impact of environmental settings on the detection performance so as to provide a clearer understanding of the model. Our performance results show that MCS task legitimacy decisions with high F-scores are possible for both illegitimate and legitimate tasks.

Mobile edge computing (MEC) systems face unevenly distributed communication and computation traffics over both time and space. In order to match with the traffics, it is beneficial for different neighboring MEC systems to cooperate in sharing their distributed communication and computation resources. This paper considers two neighboring MEC systems each with one access point (AP) serving one user, where each user can offload the computation tasks to the respective AP for remote execution. We propose a new joint computation and spectrum cooperation approach, such that the two systems can share their computation and spectrum resources to enhance their respective system performance. In particular, we minimize the weighted sum energy consumption (for both communication and computation) of the two MEC systems, by jointly optimizing the task offloading decisions at the users (for computation resource sharing) and the spectrum bands shared between the two systems. We obtain the optimal solution to the formulated problem in a semi-closed form by applying standard convex optimization techniques. Numerical results show that the proposed joint cooperation design significantly reduces the energy consumption of the two systems, as compared to other benchmark schemes without such joint cooperation.

Recent advances in technologies have allowed the design of small-size low-power and low-cost devices that can be connected to the Internet, enabling the emerging paradigm of Internet-of-things (IoT). IoT covers an ever-increasing range of applications, e.g., health-care monitoring, smart homes and buildings, etc. In this invited paper, we discuss and summarize the IoT paradigm with a special focus on energy consumption and methodologies for its minimization. Furthermore, we also discuss about reliability in the context of IoT devices. In all, this paper attempts to be a starting point for readers interested in developing energy-efficient IoT devices.

In this work, a detailed experimental characterization of GPRS and 3G data transmission energy consumption, in a custom Remote Telemetry Unit (RTU) is presented. This comparison results valuable for the design of low data-rate, battery-powered, RTUs until reliable and wide spread IoT networks specifically developed for this type of application in suburban areas are available (probably not before 2 years). The proposed RTU is aimed at illegal logging detection in protected forests, by acoustic signal processing. The RTU sends daily data and alarms to a host server through the GPRS or 3G network and the Internet, and is powered for 3 years from a single 2200mAh primary battery.

This article summarizes our current studies aiming at a better understanding of the energy consumption of a microprocessor during the execution of an application through a combination of theoretical results and experimental validations, The analysis of the transient thermal behavior and energy gains (ranging from 20 to 40% in some cases) via the adaptation of the clock frequency are of obvious practical interest. A general Passive Cooling Rule (PCR) for an isothermal object subjected to radiation, convection and internal heat generation is proposed. This power-temperature model is observed on an Exynos 5410 processor. Several approximations to this cooling rule are formulated for practical use, particularly online. They are accompanied by general rules for assessing when passive cooling becomes non-negligible compared to active cooling in embedded systems. On another hand, a theoretical framework for the existence of an Energy/Frequency Convexity Rule (EFCR) of program consumption is established. It is validated both by the state of the art and by experimental measurements. Power consumption models are then explained. The novelty of these models is that they take into account certain characteristics of the program execution and that they can be directly reused in any simulation for other processors of similar architecture.

The global marine fleets have been reported to consume approximately 300 million tons of fuel annually and contribute 2.8% of global greenhouse gases emissions (GHG). It is widely projected that the numbers will continue to grow, predominantly driven by the increase in global trades and energy demand from emerging countries. In recent years, enabling technologies, such as hybrid electrical propulsion system and advanced power management strategies, have been developed and introduced to the marine industries not only to reduce fuel consumption, but also to adhere to the increasingly stringent regulations on emissions by the International Maritime Organization (IMO). Such technologies are especially critical for vessels that operate in the water near urban areas, such as ferries and tugs, which may contribute up to 15% of the global marine fleet fuel consumption. In this paper, the design and integration of hybrid electrical propulsion systems, with the use of modern DC distribution and energy storage systems, will be discussed and compared to conventional systems. The benefits of hybrid all-electric power and propulsion system in terms of fuel and energy consumption, emission reduction, performance, as well as system redundancy are presented in this paper.

Digital technology can make cities smart. City managements can make use of information that can be extracted from databases in which data is collected about energy consumption, traffic behavior, waste management, human behavior in public environments and opinions of the general public, for example as they can be collected from social media. But can this digital technology and the data collected from it help to make living in a city more enjoyable? How can digital technology and information provided by digital technology make cities playful, allow citizens to engage in playful and entertaining activities that help to enjoy their daily and sometimes boring activities such as travelling, working, child care, house-keeping? This paper investigates how sensors and actuators in an urban environment can be introduced and used to design playful applications. We observe how ideas about playable cities emerge and develop. Interactive digital installations can provide fun, urban games can provide fun, but the experiences obtained from them can as well provide urban designers, architects, gamification and public media designers about public behavior and preferences.

Proactively pushing content to users has emerged as a promising way of coping with the explosively growing traffic demand of next-generation mobile networks. However, it is still unclear whether content pushing can improve the energy efficiency of hard delay-constrained communications over additive white Gaussian noise (AWGN) channels. With pushing, the energy consumption can be reduced by increasing the available transmission time. But if the user never needs the pushed content, pushing may result in wasted energy. Based on the random content request delay, this paper derives the content request probability threshold that determines whether a content file should be pushed under the hard delay constraint. Moreover, an optimal strategy to allocate transmission power in content pushing and on-demand delivery phases is also proposed. It is shown that the energy efficiency of systems with pushing can be significantly improved as the content request probability increases. Numerical results validate the effectiveness of the proposed power allocation strategy, compared with the on-demand scheme.

Enterprise Wi-Fi networks have been increasingly considering energy efficiency. In this paper, we present the Wi-Green project wherein we are investigating new techniques and innovative solutions that will allow the minimization of the energy consumption in Wi-Fi networks. In Wi-Green we will consider an enterprise network, in which there is equipment from different vendors, with different ages and different consumption profiles.

The authors examine the electrical energy usage in the pulp and paper industry for the continental United States. It is noted that the broad picture of energy required and fuel sources used gives a clear indication of a movement away from oil as an energy source. Internally generated fuel sources of spent liquor and hogged fuel have increased. The steam generated from boilers has increased internally generated electricity. It is pointed out that technologies such as high-yield pulping and impulse drying require less chemicals and reduced thermal requirements. The advanced thermal analysis technique of pinch technology focuses on optimum use of thermal requirements. It is concluded that all of these technologies point the way to more efficient thermal usage and increased demand for electricity. >

This paper thoroughly analyzes energy consumption in Time and Wavelength Division Multiplexing (TWDM) PONs by considering energy consumption of installed equipment and not only the one of some components. Moreover, the paper shows that device constraints (e.g., tunable transceiver tuning time), wavelength and bandwidth allocation (WBA), and dynamic reconfiguration triggering might heavily impact energy saving and average frame delay.

Energy audit is a primary step towards a more rational use of primary energy sources in the energy-intensive process such as the production of packaging paper. By the adoption of the Law on efficient use of energy in 2013, energy audits have become mandatory for all industrial companies in Serbia. This paper presents the methodology and results of the one-day energy audit which was conducted in the Paper Factory — Belgrade (FHB). The measures to increase energy efficiency of the production process, together with the quantification of the savings in the primary energy consumption, are proposed based on the results of the study.

Mobile ad-hoc network is a collection of mobile nodes which forms an instant network without fixed topology and can be arranged dynamically. Energy saving and security are important issue in MANET. Network coding technique is used to reduce energy consumption by less transmissions in MANET. To achieve a security, there are many encryption scheme are available. Out of which p-coding technique is lightweight encryption scheme which provides confidentiality. P-coding is to let the source randomly permute the symbol of each packet. So eavesdropper can't obtain the meaningful information without knowing the permutation encryption function and coding vector.

In recent development, the use of Wireless Sensor Network (WSN) to handle more complex functions is increasing drastically which in turns requires their powered battery sensors to efficiently utilise their energy in order to prolong the network lifetime for the heterogeneous nodes. Clustering is one of the techniques used to optimise this energy consumption and increasing the network lifetime as well. In recent years, many clustering protocols have been proposed based on heterogeneity like SEP,LEACH,E-LEACH etc .In these protocols, a Cluster Head (CH) is selected having maximum energy among all the nodes. This paper will survey some of these clustering protocols for heterogeneous wireless sensor network.

Now, more than ever, the time to hasten the efforts made to reduce the energy consumption, especially in the field of radio communications has come. Wireless transmission was often blamed as being energy inefficient. It is well known that, in radio communications, approximatively 80% of the consumed energy is used only to maintain the network connections during standby periods. Moreover, the number of connected devices is continuously growing: as estimated by the International Energy Agency, in 2030 the number of connected devices will be multiplied by eight and, as a consequence, the energy consumption will double.

Building automation is a trusted technology to ensure user comfort in buildings. Today the challenge is not only to provide comfort, but to do it while having a close eye on the energy performance of the building. Distributed, renewable energy sources, advances in IT and tighter legislative constraints offer and demand changes in the way we operate buildings. We look at the core fields that enable building operation: monitoring of operation data, controls, automation and the management organization to show that innovation can be achieved by integrating cross-domain knowledge and getting inspirations from other domains, where existing approaches and technologies can be used and transferred to the domain of building automation.

In a cognitive radio network (CRN), when the secondary users (SUs) are battery-powered devices, the concept of energy-efficient design is very important. In this paper, we propose an energy utility function by formulating the achievable data rate of a cooperative CRN in terms of the energy consumption by the CRN. The maximization of the energy utility function is obtained by jointly designing the sensing time, sensing threshold and number of cooperative SUs with the constraint of sufficient protect for primary users (PUs). Numerical results show that the CRN can achieve almost the maximum achievable data rate with significant energy saving.

In this paper, we study how to deploy different kinds of base stations (BSs) in green cellular networks. Unlike previous studies which deploy BSs only based on the peak traffic load, we propose an optimal deployment scheme to minimize the total power consumption over time and spatial domain based on the traffic variation characteristics. Our method can be decomposed of two steps: how to achieve limit suboptimal deployment scheme according to peak rate and how to operate BSs on/off in low load for the given deployment. A greedy heuristic deployment algorithm is proposed to additionally deploy micro BSs and separately replace macro BS. Simulations based on the regular BS topologies and real traffic profiles show that the proposed algorithms can significantly reduce the energy consumption.

In many application scenarios, such as traffic guidance or ambient living, services need to notify mobile applications about status changes. Such notifications to mobile devices can be realized using two principal approaches, namely push- and pull-based. Apart from functional differences, the two options likely result in different energy consumption, which is an important aspect due to the battery constraints of contemporary mobile devices. This paper provides a detailed assessment of energy consumption in pull- and push-based notification scenarios, considering different payload sizes and notification intervals. Our results indicate that an educated choice among both options may, depending on the specific application scenario, facilitate energy savings of up to 19%.

Due to the increasing cost of energy and the demand of reducing the environmental footprints, energy saving is becoming an important subject in the industry operation. To realize the energy consumption optimization of papermaking, the energy model should be established while the product quality and process model also need to be constructed, which are taken as the constraints for optimization. This paper describes the identification of a forming section of paper machines with Multilayer Perception (MLP) Neural Networks. The process model, product quality model and energy consumption model are established for the energy saving in papermaking. The real industrial step tests are performed and the data are used to model training and validation. The models are validated by means of mean-squared error (MSE), fit measure and Akaike's Final Prediction Error (FPE). The results show the effectiveness of the established models, which are suitable for the next work of energy optimization.

In this paper, Multi-Agent system is used to design "three- links" energy structure optimization management model for energy saving in paper-making process. As a core module for energy saving platform, the designed model deals the entire energy flow structure of paper-making process with the optimization and scheduling management, which is feasible for the industrial applications. The system design includes the policies for "three- links" MAS model, function of Multi-agent, the classification of agents, and the theoretical model of a single energy agent in the context of paper-making process. Keywords-component; industry process system; three-links model; Agent; MAS; TLMM

Due to the high energy consumption in a paper mill, energy cost is an important part of the overall production cost of paper. Papermaking is a continuous process. Ensuring a continuous energy supply for this process would avoid production losses and supplementary energy consumption for restarting the installations. In this paper we develop an optimization model of the energy supply system from the perspectives of reliability and energy loss. Subsequently we use this model to analyze the energy supply system in order to find some solutions for increasing the energy efficiency and for reducing the cost of accidental outages.

This paper describes wireless sensor network (WSN) and sensor fusion technology designed for ubiquitous smart living space applications. With respect to the WSN technology, a new standard from the Zigbee alliance is introduced. This new standard is designed to help constructing the network infrastructure by integrating with the TCP/IP network with the ZigBee network. A new approach for WSN deployment based on this new standard is also presented. With respect to the sensor fusion technology, this paper presents a smart sensing and control algorithm that naturally adjusts the thermal quality of the environment according to the interior and exterior environmental factors and the behavior of the inhabitants in a smart skin environment. The experiment results indicate that the proposed algorithm significantly improves the thermal comfort and effectively reduces energy consumption.

In this paper we justify the need for a common architecture for heterogeneous wireless sensor networks. We briefly review various proposed protocols in sensor networks, aggregate them into different groups, which we classify into different layers of the protocol stack i.e. application, networking, medium access control (MAC) and physical layer hardware. This protocol stack also includes cross-layer entities such as power management and security, because they need to be addressed at all layers of the stack. We introduce the concept of protocol stack tree (PST) that is a subset of protocols in different layers to satisfy a given class of application requirements. For example, a QoS, traffic intensive application and routing protocol would not work well with a MAC layer protocol such as S-MAC, whose primary concern is to save energy. We also propose our own solutions for a set of network layer protocols to be part of the new common sensor network architecture. Our solutions offer a wide and scalable tradeoff space between QoS and energy consumption. Our proposal would lead to flexible protocol stack trees on a compact and robust architecture

Energy consumption by pulp and paper mills in North America represents a large percentage of the total electrical energy consumption of industrial plants. There are several new technologies available to make it possible to save energy. Current information indicates that few businesses are taking advantage of these technology advancements. With the addition of electric utility rebates, businesses have an added incentive to update facilities in order to be more efficient and cost effective. This document updates the user with the different rebate programs available, the type of equipment available for rebates, and the basic methods which need to be followed to obtain the rebates. >

The information technology (IT) industry has recently been estimated to have the same carbon footprint (that is, energy consumption) as the airline industry. Airlines have invested heavily for decades in more efficient engines, lighter airplanes and optimized scheduling to save energy consumption. Meanwhile, the energy usage per compute server rack has grown from about 2 kW/rack in 2000 to an estimated 30 kW/rack in 2010, to the point where the cooling and power issues are now a major factor in system design. In the last several years, the IT industry has begun to develop new strategies for "greening" traditional data centers, yet the physical reality of modern university campus Cyberlnfrastructure (CI) is a complex network of ad hoc and sub-optimal energy environments housed in departmental facilities. But because the value of computational and data-intensive approaches to research is increasingly embraced, this number of departmental facilities is swelling fast and creating campus-wide crises of space, power, and cooling.