Green IT Engineering: Components, Networks and Systems Implementation

The paper describes an approach to improve energy efficiency of low power devices for Internet of Things (IoT). Energy efficiency of IoT is one from the main challenges in this domain as well as security with big scale systems and data management. The proposed approach is based on using of fast computation algorithms like Vedic Mathematic. IoT architecture for experiments with different applications and features is proposed and described. The Device Layer of this architecture is based on Arduino platform. A measurement of power consumption of Device Layer in conditions of constant power supply voltage can be done with Hall Effect sensors which are able to measure a current. Dependencies of operation cycle time and consumed device memory from computations algorithms and variables types are experimentally investigated. Future research directions in area of IoT energy efficiency in conjunction with safety and security are formulated.

The Internet of Things processing paradigm arises from the ever increasing tendency for decentralization of the hardware used for processing. Innovative services combine the use of cloud and mobile computational resources in order to provide intuitive and agreeable user experiences. Furthermore, the internet of things paradigm extends to include sensor networks and distributed data collection infrastructures. The essential implication is the necessity to handle big volumes of possibly streaming data. For the case of streaming data, storage in a data warehouse is in general not feasible; a real-time initial processing phase is necessary that will sample, select, organize or summarize the available information. Such systems are categorized in the Big Data Processing paradigm. The two paradigms are correlated, since Internet of Things applications are beneficial when there are “a lot of Things” and hence the amount of data classifies as “Big Data”. The internet of things information processing paradigm is one of the rare occasions where the demand for Green Computing systems does not compete with the need for performance. Indeed, the volumes of data that need to be processed are overwhelming to such an extent that approaches which use unlimited amounts of power, for processing, storage and the associated hardware cooling are simply not feasible. Additionally, remotely operating components that form the distributed processing network, such as smart mobile devices or remote interconnected sensors, need to be Green if they are to be viable. This research focuses on algorithmic developments that make the real-time collection, summarization, analysis and decision making based on streaming data greener.

In this chapter, methods for securely performing the calculations required for fundamental modular arithmetic operations, namely multiplication and exponentiation using mobile, embedded, remote or distant computational resources, are proposed that offer the possibility for green information processing system development. These methods are targeted to the distributed paradigms of cloud computing resources and Internet of Things applications. They provide security by avoiding the disclosure to the cloud resource of either the data or the user secret key. Simultaneously, environmental effects of processing are minimized by the simplifications of the operations and by transferring demanding calculations to energy efficient data centers. Hence the proposed methods are also shown to serve the green IT engineering paradigm. An algorithm for the software implementation of modular multiplication is proposed, which uses pre-computations with a constant modulus to reduce the computational load imposed upon the processor. The developed modular multiplication algorithm provides faster execution on low complexity hardware in comparison with the existing algorithms and is oriented towards the variable value of the modulus, especially with the software implementation on micro controllers and smart cards whose architectures include a small number of bits. The proposed technique for modular exponentiation is based on performing simple operations on the user computational resources, shifting the remaining complex operations to high performance, energy-efficient cloud resources and operates by separating the procedure for modular exponentiation in two components. Security is maintained by maintaining the purpose-specific secret key information exclusively in user resources. The details of the pre-calculation of the secret keys are described. Hence the procedure for transferring the most demanding part of the calculation to the cloud resources is given. It is therefore shown that a potential attacker receives no information by intercepting the data existing in the cloud. The overall process is illustrated by a simple numerical example. The use of the new algorithm in Information Society applications that demand security is investigated. Such applications include e-Government, e-Banking, e-Commerce etc. The algorithm is shown to be adequate both for the applications for which it was originally intended, as well as for applications that are much more demanding in the level of security they require, such as military applications.

Green cyber culture of micro, macro, cosmological, and virtual computing, which formulates, explains and predicts the current processes and phenomena monitoring and control technology in the physical and virtual space, is proposed. The verbal and structural definitions of the main types of computing based on current trends evolution of planet cyber ecosystem are represented. The universal model of MAT-computing: (Memory, Address, Transactions), which leverages three components to create a computational structure in technologically acceptable matter environment is proposed. The info-quantum direction of human expansion into space and the possibility of a similar penetration unearthly biotech objects in the ecosystem of our planet is shown. Computing model, which defines the structure of quasi-optimal digital monitoring and cloud control of scalable technical, biological, social and virtual processes is proposed.

Crises are complex phenomena, whereby a long-term situation produces short-term but extremely alerting incidents. Such a crisis is caused by the wave of Middle Eastern refugees and immigrants, attempting to find refuge in European countries. This crisis exhibits an obvious humanitarian component, but also severely adverse environmental effects. A systematic crisis and disaster management process that involves big data analytics with principal goal to minimize the negative impact or consequences of crises and disasters, thus protecting societal and natural environment. Green IT engineering principles are here translated as a need to analyze data in order to detect early warnings of evolving environmental effects. Big Data analytics in the context of crisis management involves efficient solutions in four fundamental aspects of the related technology: Data Volume, measuring the amount of data available, with typical data sets occupying many terabytes. Data velocity is a measure of the rate of data creation, streaming and aggregation. Data variety is a measure of the heterogeneity of data sources, together with the richness of data representation—text, images, videos etc. Data value, measures the usefulness of data in making decisions. This chapter aims to present appropriate solutions in all aspects of distributed data analysis of social media data, so as to define the enabling technologies for high performance decision support for the purpose of crisis management. The presentation will include both existing and innovative appropriate technologies and existing state of the art systems and will aim to propose the advantages and disadvantages of different possibilities for alternative integrated solutions. Additionally, sources of data related to the Syrian refugee crisis are identified in the context of the social media platforms Facebook and Twitter with effects in both the humanitarian and the environmental fronts.

The main source of power consumption in a digital system is dynamic power dissipation. The chapter shows that program optimization has the positive influence on power consumption. The system level optimization has the greatest effect on potential power consumption gains. The chapter is focused on the transformations of program loops as the point where the most of computational load exists. Some optimized and parallelized software are analyzed from the point of power consumption. These results show the influence of program optimization on the power consumption and possibility of high-quality low-power design of embedded systems. The loop fusion algorithm for programs optimization is presented and its influence to the power consumption is shown. The experiments show that the loop fusion optimization may decrease the current consumption by more than 20%. The real applications are considered as examples of embedded systems use. A program of contour extraction in medical images is considered as the example of usage of multidimensional loops fusion algorithm. The example shows that the decrease in the activity of elements leads to reduction of energy consumption. The authors propose the loop fusion method for high level language code-to-code transformations and demonstrate its efficiency in terms of power consumption.

This paper is an extended version of Azmi et al. (The 2015 International Conference on Embedded Systems and Applications, 2015 [1]). This research aims to compare the energy efficiency in between two generations Intel processors; the 4th Gen Intel^® Core™ Processor and 3rd Gen Intel^® Core™ Processor. It also surveys the technologies that provide better energy performance for both of the processors. The methodology used for this research is a physical experiment conducted in an Intel production plant. The results obtained from the experiment show that the 4th Gen Intel^® Core™ Processor is more energy efficient than the 3rd Gen Intel^® Core™ Processor.

The computer programs, which provide malefactors with the data concerning the usage of an infected mobile device can be referred to malicious software. As a rule, the information is as follows: device location, keys and passwords entered by a user, SMS and telephone conversations contents, e-mail contents and many other. Malicious software can be secretly input to a mobile device, e.g. with the help of Internet. On inputting such kind of Software adjusts the system data in order to conceal its presence in an infected device. At the same time the malicious software cannot be recognized as a computer virus since it does not include the program codes realizing the virus multiplication and infection of other devices. That is why the popular antivirus software does not react to the presence of the malicious software in a device. Thus, we can say that there exists an issue of detection of malicious software presence in a mobile device. To solve the problem a method of indirect detection of malicious software developed by the authors is described in the Chapter. The method is based on a hypothesis of power consumption increase in a mobile device after its being infected by malicious software. Because malicious software taps such power-consuming functions of a device as usage of GPS, Wi-Fi and mobile Internet. To experimentally verify the assumption represented an appropriate experiment was made. It provides the comparison of the smartphone power consumption level in the case of the normal uninfected condition to the one in the case of inputting a spy malicious program. The experiment demonstrated the correctness of the hypothesis and showed that after the input of malicious software the smartphone power consumption increases. The proposed method is a universal one and can be used for any mobile devices running under the control of any operating systems.

The article presents substantiation for the necessity of improving the aircraft flights safety due to reducing the flight costs by using green technology and intellectualizing the technologies that provide diagnosis and recovery of control systems operability. The typical reasons for operability failure of three aircraft types: airplanes, unmanned aerial vehicles and spacecraft are presented. The analysis results of the classical control principles for countering malfunction of aircraft are described. A new approach standing on the diagnosis-based control principle and providing for operability of aircraft control systems is suggested. The usage of the principle requires supplementing intelligent control functions: diagnosis and recovery of operability. A block diagram of a rational control system implementing the principle of control on diagnosis is presented. The features of formation of the algorithmic support for recovering the operability with the use of the signal and parametric customizations, algorithms and hardware reconfiguration in real-time are described. An example of forming the algorithm for sensor operability recovery in the heading channel of a flying model is presented. The potential resource effects of the proposed approach on the example of the course channel of the model are reviewed. The directions for further research on increasing resource security through the rational intellectualization aircraft control are suggested.

New FPGA-based devices with a high degree of reconfigurability that allow dynamic to change architecture and structure are created. These devices improve the efficiency of reconfigurable devices and systems according to the optimal criteria of hardware resources and power consumption, which are decisive for the Green IT Engineering. This class of devices for the implementation of technology the “Reconfigurable computing” is viewed. It is showed that in the dynamic logical structure devices, the configuration dynamically changing depending on the specific solving problem by transmitting information about any given current configuration. As a basic structure for construction of such devices the adaptive logical networks (ALN) are considered. ALN designed for solving of a wide class of problems by means of directly implementing algorithms and by direct mapping of the input data into output data. Unlike already known methods for the synthesis of multilevel logic scheme, two new approaches to the synthesis of such schemes are proposed. The first approach is based on the description of Boolean network by polynomials. In this case coefficients of the polynomial are given by Hadamard matrix. The second approach is based on the description of Boolean network by means Zhegalkin polynomials. An algorithm for partition of the range of Boolean functions is developed. This algorithm (for input data of arbitrary length and a threshold value) allows determining the types of logical functions for each level of ALN. The algorithm is based on the analysis of bit-by-bit of the threshold value for a predetermined threshold relation. The correctness of implementation this algorithm is proved. An example of solving the XOR problem in neural networks by means of a two-layer network is adduced. This network uses proposed by the threshold device and implemented on FPGA chip.

The opportunity of the modern CAD and feature of FPGA for development of the power-efficient digital components of computer systems are examined experimentally. Possibilities of a preliminary estimate of energy consumption in the project implemented in Altera FPGA are analyzed. The possibility of an assessment of energy consumption distribution between parts of the project circuit by control of signals activity is shown. Influence of the partial failure of circuits of the general signals on energy consumption of the FPGA circuit is researched. The possibility of monitoring of the general signals in the circuit according to its energy consumption is shown. A problem of the glitches caused by signal races with parasitic transitions leading to essential power losses is considered. The program model developed for an assessment of glitches in the iterative array multiplier shows repeated exceeding of number of parasitic transitions in comparison with the number of functional ones. The matrix parallelism which is widely used in the FPGA circuits is the cornerstone of the problem of glitches. Experiments with FPGA show solution this problem by simplification of array structures in use of additional and natural pipelining and in execution of the truncated operations.

Green computing includes FPGA computing, which largely determined by millions so-called LUTs (Look up Tables). But for one FPGA configuration each LUT FPGA calculates only one logic function in the Perfect Disjunctive Canonical Forms (PDCF). The chapter proposed the concept of Green LUT FPGA in three main areas. The first area is Double LUT (DLUT), which computes two functions simultaneously through the using of inactive transmission transistors LUT’s subtree. The second Green Logic area is LUT—Decoder (DC LUT). It we may obtain by rotating LUT’s tree to calculate not one, but system of the logic functions. Such technique can significantly reduce hardware complexity and power consumption by taking into account the using of millions logic elements. The third Green Logic area is DNF-LUT, which allows the calculations of the logic systems in Disjunctive Normal Form (DNF) and else more significantly reduces complexity of the large number variables LUT. The models of the proposed concepts were explored in the NI Multisim 10 by National Instruments Electronics Workbench Group. The chapter analyzes the Green LUT assessments and formulates the conclusions about the effectiveness of the proposed solutions for the Green Computing.

This paper focuses on the idea of virtual enterprise (VE) creation, deployment and functioning support through the use of Green IT concept. The Green IT is regarded as a complex of innovative techniques, processes and materials used in material production and based on the principles of sustainable development. Specifically, the VE requires the implementation of the Green IT as a basic concept because the vast majority of business processes on VE are based on information search, collection, storage, delivery and dissemination. The comprehensive use of the concept of Green IT is directly related to increasing the efficiency of business processes mentioned above. A VE is formed via selection of the appropriate organizational and manufacturing resources at different enterprises and their integration with web-based technologies. The VE members possess their production assets and perform the correspondent operations within the chain of the production process. Thus, one of the problems is to allocate these operations between individual VE members in the most effective way possible with respect to a predetermined criterion. The authors describe informational support for the main lifecycle (LC) stages of the VE from the standpoint of the Green IT that decreases the environmental stress during the VE operation. The evaluation of economic efficiency of the developed approach for managing VE LC within Green IT concept is given. Constructed a spiral model for evaluation of VE LC, which allows to making quick and flexible management decisions of whether or not to invest into further upgrades and continue production. It is shown that in this case integrated resource production efficiency increases, economic risks and damage caused to the environment during production decreases.

Thermoacoustic devices (TAD) are the newest type of unconventional heat machines. Their work is based on the mutual transformation of heat and acoustic energies. This heat machines are characterized by high sensitivity to the working fluid properties (viscosity, density) as well as the environment effects (temperature, pressure, etc.). An effective work of TAD is possible only if the different nature values of the internal parameters (acoustic, hydrodynamic, thermal) are stabilized. The prospective area for thermoacoustic heat machines is their use in the waste energy recovery systems due to their ability to work with both high potential and low potential supplied heat. As the source of waste heat in such systems can be used the exhaust gases after the catalytic converters, or, taking into account latest results in low potential energy utilization with TAD, even the temperature of cooling water (about 90 °C). This paper is devoted to the synthesis of intelligent digital system for control of thermoacoustic plant with providing optimal working conditions for increasing its efficiency. Authors synthesize the fuzzy controllers of Mamdani and Sugeno types for the created control system. Designed fuzzy controllers are compared with a traditional PD controller in terms of their operation speed and accuracy. Special attention is paid to green-IT approach for design of embedded fuzzy systems by the optimization of fuzzy controllers based on the different type and parameters of linguistic terms for input and output signals as well as on minimization of fuzzy rules quantity in the preliminary synthesized fuzzy rule bases. The results of comparative analysis of initial and optimized fuzzy controllers are discussed in detail.

Changes in approaches to safety-critical Instrumentation and Control (I&C) systems traffic control results in changes in system power consumption. Thus, timely detection of traffic anomalies allows significant reducing of power consumption due to effective redistribution of the data flows. Well-balanced traffic allows reducing the power consumption of the network compared to the same network, but without such traffic balancing. In this chapter we consider appropriate approaches intended to solve the problem of traffic control in safety-critical I&C systems in order to reduce data flows transmission time. Method of rapid identification of traffic parameters on the basis of the current samples for timely detection of traffic anomalies is proposed. The method allows reducing time of traffic main parameters identification by 15–20%. This makes it possible to determine the behavior of the existing traffic. Moreover, method for short-term prediction of traffic behavior is also proposed. Standard tools are used for flexible and poorly aggregated traffic. An original approach is proposed for the prediction of fractal traffic. Such approach is based on certain properties of fractal processes, including self-similarity and linearity of autocorrelation function. The results of the prediction are used for dynamic control of load distribution in virtual connections, and methods of its effective redistribution allow reducing system power consumption. It is significant that minimal power consumption was achieved when alternative routes were used to reroute the traffic, which was previously flowing through network bottlenecks. Simulation results proved that proposed approach allowed reducing power consumption during appearance anomalies in traffic behavior, compared to standard approaches, by approximately 20%. Moreover, even if traffic behavior is free from anomalies, proposed approach allows increase energy efficiency of the system. Thus, due to well-balanced load caused by data flows into physical links, power consumption of safety-critical I&C systems can be reduced by 7%.

One of the most important components of smart grid digital substation is the merging unit (MU). A possibility to consider the MU as a recovered multi-state system (RMSS) is shown. It is also shown that the MU can be considered as a system, which consists of one “core” and one “shell”. The “core” of the MU is its part, which provides functions for performing analog-to-digital (digital) conversion. The “shell” of the MU is its part which provides synchronous measurements of vector functions. Existing approaches to RMSS assessment based on Markov models are considered. Degradation levels for MU are obtained and degradation diagrams (DD) are developed. On the basis of the DD, the models of RMSS availability with using Markov chains (MC) are proposed and analysed. The main feature of the proposed MC-based models is consideration of testing and recovery errors caused by problems of checking coverage and faults of checking means. The models also take into account two different preventive maintenance policies (PMP). According to the first policy (PMP1), preventive maintenance is performed through exponentially distributed time. According to the second one (PMP2), preventive maintenance is performed both through exponentially distributed time and when failures are detected in the current testing. The features of the models applications for RMSS with proposed PMP are shown. Recommendations based on the research results for improving maintenance policy and availability of the MU are formulated. Future research directions can be related to development of MC-based models for smart grid with two and more “core” and “shell”. Besides, development and research of smart grid models for cases of its components multiple failures are important as well.