Showing papers on "Green computing published in 2021"

A Survey of Computational Intelligence for 6G: Key Technologies, Applications and Trends

Abstract: The ongoing deployment of 5G network involves the Internet of Things (IoT) as a new technology for the development of mobile communication, where the Internet of Everything (IoE) as the expansion of IoT has catalyzed the explosion of data and can trigger new eras. However, the fundamental and key component of the IoE depends on the computational intelligence (CI), which may be utilized in the sixth generation mobile communication system (6G). The motivation of this article presents the 6G enabled network in box (NIB) architecture as a powerful integrated solution that can support comprehensive network management and operations. The 6G enabled NIB can be used as an alternative method to meet the needs of next-generation mobile networks by dynamically reconfiguring the deployment of network functions, providing a high degree of flexibility for connection services in various situations. Especially the CI technology such as evolutionary computing, neural computing and fuzzy systems utilized as a part of NIB have inherent capabilities to handle various uncertainties, which have unique advantages in processing the variability and diversity of large amounts of data. Finally, CI technology for NIB, which is widely used is also introduced such as distributed computing, fog computing, and mobile edge computing in order to achieve different levels of sustainable computing infrastructure. This article discusses the key technologies, advantages, industrial scenario applications of CI technology as NIB, typical use cases and development trends based on IoE, which provides directional guidance for the development of CI technology as NIB for 6G.

VLSI Implementation of Green Computing Control Unit on Zynq FPGA for Green Communication

Abstract: The issue of the energy shortage is affecting the entire planet. This is occurring because of massive population and industry growth around the world. As a result, the entire world is attempting to implement green networking systems and manufacture the power/energy efficient products. This research work discusses the green networking system technologies. This work introduces a power-efficient control unit (CU) design and implemented on the Zynq SoC (System on Chip) ultrascale field programmable gate array (FPGA). The VIVADO HLx Design Suite is used to simulate and analyze the CU model which is considered as one of the key components of central processing unit (CPU), used for data communication purposes. The CU is made suitable for the green communication by making it power-efficient. Therefore, the power consumption of the CU is analyzed for the various set frequency value ranging between 100 MHz and 5 GHz, and it is discovered that as the clock frequency rises up, the total power consumption also tends to get increased. The total power of the proposed model is reduced by 77.42%, 21.29%, and 17.93% from three models, respectively, being compared in the present paper. Final results shows that the CU is better suited to run at low frequencies to optimize power consumption.

Green Algorithms: Quantifying the Carbon Footprint of Computation

Abstract: Climate change is profoundly affecting nearly all aspects of life on earth, including human societies, economies, and health. Various human activities are responsible for significant greenhouse gas (GHG) emissions, including data centers and other sources of large-scale computation. Although many important scientific milestones are achieved thanks to the development of high-performance computing, the resultant environmental impact is underappreciated. In this work, a methodological framework to estimate the carbon footprint of any computational task in a standardized and reliable way is presented and metrics to contextualize GHG emissions are defined. A freely available online tool, Green Algorithms (www.green-algorithms.org) is developed, which enables a user to estimate and report the carbon footprint of their computation. The tool easily integrates with computational processes as it requires minimal information and does not interfere with existing code, while also accounting for a broad range of hardware configurations. Finally, the GHG emissions of algorithms used for particle physics simulations, weather forecasts, and natural language processing are quantified. Taken together, this study develops a simple generalizable framework and freely available tool to quantify the carbon footprint of nearly any computation. Combined with recommendations to minimize unnecessary CO2 emissions, the authors hope to raise awareness and facilitate greener computation.

Nexus between energy consumption, information and communications technology, and economic growth: An enquiry into emerging Asian countries

Abstract: The development of every economic sector is significantly affected by information and communication technology (ICT), especially during the liberalization process. Though several studies have focused on economy–environment–financial development nexus, yet very limited literature has highlighted the impact of ICT on the relationship between economic growth, energy consumption, and financial development. We address this gap in the existing literature by investigating the nexus between ICT, energy consumption, and economic growth for a panel of 10 emerging and developing Asian countries selected on the bases of the highest current gross domestic product price (in US dollars), for a span of 17 years ranging from 2000 to 2017. Unlike the previous studies, this study employs the advanced econometric techniques that are robust to heterogeneities across nations and have proven to produce more reliable and efficient results. Our findings opine a bidirectional causality between ICT, energy consumption, and economic growth. Additionally, internet and mobile cellular subscriptions have a positive impact on economic growth, while energy consumption report negative impact, and the results for medium and high technological export reveals an insignificant impact on the economic growth of the 10 countries under study. Overall, the results are consistent for all the countries analyzed in this empirical study. The study provides valuable policy lessons to adopt ICT-enabled technologies that will bring innovative changes and further lead to increased economic growth. It is recommended that the government must promote green ICT technology and enhance the technological industry that shall lead to higher productivity and sustainable development.

WSN-IoT Clustering for Secure Data Transmission in E-Health Sector using Green Computing Strategy

Abstract: Energy was one of the 21st century's most critical components. Electronics and computer technologies have been widely used nowadays to simplify work every day. The crisis and the constant lack of power have popularized and integrated Green Computing algorithms for multidimensional applications on a broad scale. The author attempts to defuse times of crisis related to medical crises using the Green Computing method. Wireless Sensor Networks (WSN) are made up of numerous sensor nodes (SN) that are linked to and play a key part in many applications and the Internet of Things (IoT). To establish a dynamic information exchange network, IoT links physical items like sensors. In a number of areas, the Internet of Things was used. Wearable medical sensors are used to monitor health indicators in patients in this crisis situation. This battery-powered medical sensor has a limited quantity of energy. This is an important hurdle for increased network lifetime. In order to address the current issue effectively, a new technique dubbed Jarvis Patrick regressive resource-efficient gaussian process clustering was suggested to prolong the lifetime of the network. This method is based on the green technology concept that requires the hour. IoT devices are first used in SN to detect and collect patient information. SN is categorized in several clusters using the Jarvis Patrick clustering method after the data collection process. Clustering by Jarvis Patrick is a graphical clustering technique used for dividing SN using the Gaussian process regression function. The regression function reviews the SN and performs the process of grouping based on anticipated bandwidth and energy. The Cluster Head (CH) is selected to enhance data transmission and decrease latency after the clustering process. The information is transmitted to the CH from the source node. Then CH locates the nearest CH using the flight-time method. After then, data are sent through a cluster head from the source node to the sink node. WSN carries out resource-efficient data transmission in this way. Number studies indicate that the REGPRJPC technique successfully enhances the potential and reliability of patient data packets and reduces the incidence of loss and delay.

An efficient power-aware VM allocation mechanism in cloud data centers: a micro genetic-based approach

Abstract: Efficiency in cloud servers’ power consumption is of paramount importance. Power efficiency makes the reduction in greenhouse gases establishing the concept of green computing. One of the beneficial ways is to apply power-aware methods to decide where to allocate virtual machines (VMs) in data center physical resources. Virtualization is utilized as a promising technology for power-aware VM allocation methods. Since the VM allocation is an NP-complete problem, we use of evolutionary algorithms to solve it. This paper presents an effective micro-genetic algorithm in order to choose suitable destinations between physical hosts for VMs. Our evaluations in simulation environment show that micro-genetic approach provides invaluable improvements in terms of power consumption compared with other methods.

Green Computing in Software Defined Social Internet of Vehicles

Abstract: Social Internet of Vehicles (SIoV) is an evolving vehicular networking framework integrating the next generation smart devices with vehicular communications. Green computing and communication under disruptive vehicular environment is one of the challenging tasks for enabling SIoV. In this context, green traffic data dissemination in SIoV environments is modelled as an NP-hard problem focusing on heterogeneous traffic data, transmission distance from next generation smart devices and probabilistic delay in transmissions due to disruptive vehicular environment. An adopted meta-heuristic solution namely Two-Way Particle Swarm Optimization (TWPSO) is developed for the green traffic data dissemination problem in SIoV considering software defined vehicular network architecture. Extensive simulation experiments were performed to assess the performance of TWPSO as compared to the state-of-the-art techniques. The critical analysis of the comparative results attest the green computing oriented benefits of TWPSO under real SIoV environments.

A Robust Energy Optimization and Data Reduction Scheme for IoT Based Indoor Environments Using Local Processing Framework

Abstract: The extensive growth in popularity of Internet of Things (IoT) has led to the generation of massive amount of data from several heterogeneous sensory devices. This has also led to the increase in energy consumption by these connected devices. Smart buildings are one such platform which are equipped with several micro-controllers and sensors, generating a huge amount of redundant information at their data acquisition level. As a result, real-time applications may not be efficiently executed due to latency delays at the cloud service end. This requires several devices at cloud service end to execute the massive amount of data generated by these sensors, which does not satisfy green computing criteria. In this context, a novel local processing mechanism (LPM) is proposed, which favors an improved IoT service architecture for smart buildings. From the perspective of green computing, the proposed LPM framework facilitates reduction of manifolds at data acquisition level of sensor nodes. This paper also addresses the concept of optimal use of sensors in a wireless sensor network (WSN) and estimates costs corresponding to non-Poisson and Poisson arrival of data packets at local processor using the well-known queuing model. We also provide an efficient algorithm for smart buildings using our expert Markov switching (EMS) model, which is a well known probabilistic model in the field of artificial intelligence (AI) for subjectively validating real sensory data sets (viz., temperature, pressure, and humidity). Further, it has been analyzed that the proposed EMS algorithm outperforms several other algorithms conventionally used for determining the state of large-scale dynamic sensor networks. The service cost of proposed model has been compared with conventional model under various stress conditions viz., arrival rate, service rate, and number of clusters. It is observed that the proposed model operates well by leveraging green computing criteria. Thus, in the aforementioned context, this paper provides thing-centric, data-centric, and service-oriented IoT architecture.

An improved thermodynamic simulated annealing-based approach for resource-skewness-aware and power-efficient virtual machine consolidation in cloud datacenters

Abstract: Cloud computing attracted great attention in both industry and research communities for the sake of its ubiquitous, elasticity and economic services. The first class concern of cloud providers is power management for both reducing their total cost of ownership and green computing objectives. To reach the goal, a system framework is presented which has different modules. The main concentration of the paper is on virtual machine (VM) consolidation module which launches users requested VMs on the minimum number of active servers to reduce datacenter total power consumption (TPC). In this paper, the VMs consolidation is abstracted to two-dimensional bin-packing problem and also is formulated to an integer linear programming. Since the papers in the literature scarcely are aware of skewness in resources of requested VMs and for discrete nature of search space, this paper presents the resource skewness-aware VMs consolidation algorithm based on improved thermodynamic simulated annealing approach because resource skewness potentially compels the algorithm to activate additional servers. The proposed SA-based algorithm is validated in extensive scenarios with different resource skewness in comparison with two heuristics and two meta-heuristics. The average results reported from different scenarios proves superiority of proposed algorithm in comparison with other approaches in terms of the number of used servers, TPC, and total resource wastage of datacenter.

The Green Blockchains of Circular Economy

Abstract: Eco-friendly systems are necessitated nowadays, as the global consumption is increasing. A data-driven aspect is prominent, involving the Internet of Things (IoT) as the main enabler of a Circular Economy (CE). Henceforth, IoT equipment records the system’s functionality, with machine learning (ML) optimizing green computing operations. Entities exchange and reuse CE assets. Transparency is vital as the beneficiaries must track the assets’ history. This article proposes a framework where blockchaining administrates the cooperative vision of CE-IoT. For the core operation, the blockchain ledger records the changes in the assets’ states via smart contracts that implement the CE business logic and are lightweight, complying with the IoT requirements. Moreover, a federated learning approach is proposed, where computationally intensive ML tasks are distributed via a second contract type. Thus, “green-miners” devote their resources not only for making money, but also for optimizing operations of real-systems, which results in actual resource savings.

Towards green computing

Abstract: With the emergence of the Internet of Things (IoT) and machine to machine (M2M) communications, massive growth in the IoT-enabled wireless sensor node deployment is expected in the near future. The...

Mobile Cloud Computing: A Green Perspective

Abstract: Green computing is a technology that focuses mostly on finding alternative solutions (recycling) to protect the natural resources on earth like energy, etc. In this matter, it can be observed that mobile computing technologies like mist, edge, cloud, and fog computing can support this technology by providing services that help in efficient utilization of resources and reducing energy consumption. In fact, fog computing is an extended version of cloud computing, where data moves from the mist and edge devices to the cloud, passing through the fog layer, which helps in improving some cloud computing features, adding privacy, reduce latency, and location awareness, since it is closer to the end user. As a result, cloud computing can significantly reduce the utilization of resources, which helps in making the overall computing process better and green. This paper aims to highlight the areas and the extent to which the mist, edge, fog, and cloud computing technologies can support the green technology and ways to increase this support.

Green Computing and Carbon Footprint Management in the IT Sectors

Abstract: The focus of the current research is on making computers as energy-efficient as possible, and applying innovative ideas to energy-related computer technology. It is anticipated that green information technology (IT) will rapidly become a reality and official organizational policy. Thus, green IT is not merely restricted to environmental strategies but is concerned with the overall development of people and society as a whole. In this regard, collaboration is to be explored to optimize business. This article examines the importance of green computing in sectors such as IT, networking, industries, and corporations.

3D-TTN: a power efficient cost effective high performance hierarchical interconnection network for next generation green supercomputer.

Abstract: Green computing is an important factor to ensure the eco-friendly use of computers and their resources. Electric power used in a computer converts into heat and thus, the system takes fewer watts ensuring less cooling. This lower energy consumption allows to be less costly to run as well as reduces the environmental impact of powering the computer. One of the most challenging problems for the modern green supercomputers is the reduction of current power consumptions. Consequently, regular conventional interconnection networks also show poor cost performance. On the other hand, hierarchical interconnection networks (like-3D-TTN) can be a possible solution to those issues. The main focus for this paper is the estimation of power usage at the on-chip level for 3D-TTN with the various other networks along with the analysis of static network performance. In our analysis, 3D-TTN requires about 32.48% less router power usage at the on-chip level and can also achieve near about 21% better diameter performance as well as 12% better average distance performance than the 5D-Torus network. Similarly, it also requires only about 14.43% higher router power usage; however, can achieve 23.21% better diameter performance and 26.3% better average distance than recent hierarchical interconnection network- 3D-TESH. The most attractive feature of this paper is the static hop distance parameter and per watt analysis (power-performance). According to our power-performance results, 3D-TTN can also show better result than the 3D-Mesh, 2D-Mesh, 2D-Torus and 3D-TESH network even at the lowest network level. Moreover, this paper is also featured with the static effectiveness analysis, which ensures cost and time efficiency of 3D-TTN.

Green Computing Approaches - A Survey

Abstract: The upsurge in global warming and release of greenhouse gases is a major issue that intensified over the past years due to the increasing usage of technological resources in our daily routines. That is why a call for going green in the technological field is highly recommended. This paper reviews various approaches of green computing in five main models - software engineering model, cloud computing, mobile computing, data centers, and the educational sector.

Governance and Management of Green IT: A Multi-Case Study

Abstract: Context The changes that are taking place with respect to environmental sensitivity are forcing organizations to adopt a new approach to this problem. Implementing sustainability initiatives has become a priority for the social and environmental awareness of organizations that want to stay ahead of the curve. One of the business areas that has, more than others, proven to be a vital asset and a potential ally of the environment, is the area of Information Technology (IT). Through this area, Green IT practices advocate sustainability in and by IT. However, organizations have a significant handicap in this regard, due to the lack of specific Green IT standards and frameworks that help them carry out this type of sustainability practices. Objective We have developed the “Governance and Management Framework for Green IT” (GMGIT), which establishes the necessary characteristics to implement Green IT in organizations, from the point of view of the governance and management of this area. After developing and validating a first version of this framework, we have performed a set of improvements, obtaining the GMGIT 2.0, which we want to validate. Method We have conducted a series of empirical validations at international level based on case studies, whose characteristics and results are presented in this study. Results The results of this multi-case study show an example of the current situation of organizations in Green IT, as well as the resolution of problems encountered during the validations conducted with the GMGIT 1.0. Conclusion The findings obtained demonstrate the usefulness, applicability, and validity of the framework when implementing, auditing, and improving Green IT in organizations in a systematic and progressive manner.

Going green: strategic evaluation of green ICT adoption in the textileindustry by using bipolar fuzzy MULTIMOORA method

Abstract: The widespread use of information and communication technologies in all fields has a direct impact on the way the world is viewed. In today’s competitive international business environment, companies are increasingly investing in the search for new ideas and approaches in production. The use of information and communication technologies (ICT) is increasingly gaining in importance, especially in the situation of a dynamic market and increasingly demanding consumers. Today’s business of contemporary organizations is not conceivable without the support of modern ICT systems. Therefore ICT has a great influence on modern society because the ways in which information and data are exchanged are higher than ever. Green information and communication technologies as one area that is new and in development tend to establish a balance between these technologies and the environment. Adoption of green information and communication technologies is not an easy task and is often related to certain limitations. Therefore, the aim of the paper is a strategic evaluation of green ICT and their implementation in the textile industry by using newly-developed bipolar fuzzy MULTIMOORA method. Effectiveness and efficacy of the proposed approach is demonstrated in the conducted illustrative case study.

Green Computing and Internet of Things for Smart Cities: Technologies, Challenges, and Implementation

Abstract: Green computing as well as Internet of Things (IoT) are becoming attractive technologies for building smart cities. Statistics has shown that the use of Information and Communication (ICT) devices will increase 41.6 billion by the year 2023(2019). While there are numerous applications and benefits of using IoT enable devices, studies have shown that the potential number and intensity of serious environmental issues including high consumption of energy, emission of carbon and other electronic waste. To deal with the adverse effects of such huge usage of ICT devices, the research community has started exploring the area of Green IoT and Networking much more exhaustedly. Fortunately, technologies like IoT can be used with green networking to reduce electronic waste and relatively use of less power/energy for future applications and in return help in achieving better results for our ecosystem. This chapter provides a survey of green computing and IoT for smart cities highlighting the importance and real-world implementation challenges.

Energy Management and Monitoring Using IoT with CupCarbon Platform

Abstract: Green computing is an Eco-Friendly usage of resources in terms of designing, displaying and manufacturing in the field of Engineering. Main purpose of green computing is reducing the environmental impact such as hazardous materials, energy efficiency during the lifetime of product and recyclability of product wastage. The main approaching fields of green computing are data center design, cloud computing, edge computing, IoT, super Computer and smart cities etc. The one of the main approaches of green computing with smart cites is collect and manage various recourses and use efficiently and effectively. In smart cities data storing, processing and using take more usage of resources are wasted. In Energy management and effectively usage is big challenging issues in recent days in the world. The Green computing with energy efficiency in a smart cities research help to improve the energy effectively. The Energy management in smart cities is tracking and monitoring the energy to use effectively in building and smart cities. In smart build and smart cities around 25–35% cost is spent to energy operations. Energy managing purpose different techniques and methodologies are introduced. Internet of things (IoT) is one of the main techniques to sense and optimize the unrelated events. In this chapter mainly concentrated integration of IoT and CupCarbon and implementation. Specially first, IoT Smart Road Network Energy management using CupCarbon is implemented with the help of Road Side Unit (RSU) and IoT protocol (MQTT). Using this implementation, we can Manage the power in the street light in road network (power optimization), Analysis the traffic in one particular and Emergency services we can take the decision. The second, Case Study with IoT Energy Management with CupCarbon in VANET environment. Finally presented various challenges and research direction for future.

Smart SDN Management of Fog Services to Optimize QoS and Energy.

Abstract: The short latency required by IoT devices that need to access specific services have led to the development of Fog architectures that can serve as a useful intermediary between IoT systems and the Cloud. However, the massive numbers of IoT devices that are being deployed raise concerns about the power consumption of such systems as the number of IoT devices and Fog servers increase. Thus, in this paper, we describe a software-defined network (SDN)-based control scheme for client–server interaction that constantly measures ongoing client–server response times and estimates network power consumption, in order to select connection paths that minimize a composite goal function, including both QoS and power consumption. The approach using reinforcement learning with neural networks has been implemented in a test-bed and is detailed in this paper. Experiments are presented that show the effectiveness of our proposed system in the presence of a time-varying workload of client-to-service requests, resulting in a reduction of power consumption of approximately 15% for an average response time increase of under 2%.

A decisional smart approach for the adoption of the IT green

Abstract: The new IT governance practices have emerged to adopt a responsible attitude within the company to question its mode of operation, its mode of consumption and its relationship with every IT service. The objective of our research is to ensure that the functions of the company should follow the criteria of coherence and of consonance, in order to develop a corporate culture oriented toward the restoration of the environment, green IT. Knowing how to make information and communication technologies as a catalyst for sustainable development and deploying a specific green framework to the company by using the powers of the artificial intelligence are the aim of our proposed approach. According to the four ecological aspects, the proposed approach, firstly it diagnoses the maturity of the company by grouping the existing processes and the IT needs processes. Secondly it unifies all the processes by using a prototype process. Finally, it evaluates the company’s processes by using a suite of performance indicators then it lists a set of the best ecological recommendations.

Energy Efficiency Analysis of Post-Quantum Cryptographic Algorithms

Abstract: Classical cryptographic schemes in use today are based on the difficulty of certain number theoretic problems. Security is guaranteed by the fact that the computational work required to break the core mechanisms of these schemes on a conventional computer is infeasible; however, the difficulty of these problems would not withstand the computational power of a large-scale quantum computer. To this end, the post-quantum cryptography (PQC) standardization process initiated by the National Institute of Standards and Technology (NIST) is well underway. In addition to the evaluation criteria provided by NIST, the energy consumption of these candidate algorithms is also an important criterion to consider due to the use of battery-operated devices, high-performance computing environments where energy costs are critical, as well as in the interest of green computing. In this paper, the energy consumption of PQC candidates is evaluated on an Intel Core i7-6700 CPU using PAPI, the Performance API. The energy measurements are categorized based on their proposed security level and cryptographic functionality. The results are then further subdivided based on the underlying mechanism used in order to identify the most energy-efficient schemes. Lastly, IgProf is used to identify the most energy-consuming subroutines within a select number of submissions to highlight potential areas for optimization.

Energy-efficient cloud data center with fair service level agreement for green computing

Abstract: More and more cloud data centers provide numerous cloud computing services. However, how to meet customer needs, improve efficiency and reduce costs are important issues that cloud service providers must deal with. For customers, it is very important to consider the quality of service requirements provided by the data center providing public cloud services. Besides, data center operators should consider how to reduce energy consumption. Therefore, for these important issues, we propose a possible balance between service quality and energy conservation strategy. We find the relationship between the minimal service resources and the required level of services. Under conditions consistent with the SLA, our strategy quantifies the quality of service and calculates the required computing resources according to changes in workload to achieve an energy-saving goal. Also, the policy approximate function is derived and can achieve efficient decision-made goals.

A Systematic Literature Review on Virtual Machine Consolidation

Abstract: Virtual machine consolidation has been a widely explored topic in recent years due to Cloud Data Centers’ effect on global energy consumption. Thus, academia and companies made efforts to achieve green computing, reducing energy consumption to minimize environmental impact. By consolidating Virtual Machines into a fewer number of Physical Machines, resource provisioning mechanisms can shutdown idle Physical Machines to reduce energy consumption and improve resource utilization. However, there is a tradeoff between reducing energy consumption while assuring the Quality of Service established on the Service Level Agreement. This work introduces a Systematic Literature Review of one year of advances in virtual machine consolidation. It provides a discussion on methods used in each step of the virtual machine consolidation, a classification of papers according to their contribution, and a quantitative and qualitative analysis of datasets, scenarios, and metrics.

Individual and organizational factors affecting the implementation of Green IT: a case study of an Indian business school

Abstract: Green Information Technology (Green IT) emerged as a critical research agenda for reducing organizations' carbon footprints to achieve environmental sustainability. This paper aims to understand the factors that affect the adoption of Green Information Technology in the context of a developing country. Studies that have focused on both individual and organizational level factors (multi‐level approach) remain limited. The Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), and Technology‐Organization‐Environment (TOE) framework was used as a theoretical lens to address the gap in the literature. The theoretical background and participatory case study (qualitative) as the methodology was used to investigate the factors at multiple levels that could affect Green IT implementation in the developing country context (Indian business school). The findings reveal that three key dimensions affect the implementation of Green IT‐ Need, Scope, and the Inclination to adopt Green IT. Each dimension includes a mix of factors at the individual and organizational levels. This paper contributes to the theory by proposing a framework for multi‐level Green IT adoption. It also provides guidelines to the practitioners for considering the intervention factors at the individual and organizational levels.

Social and Economic Contribution of 5G and Blockchain With Green Computing: Taxonomy, Challenges, and Opportunities

Abstract: In recent years Fifth Generation (5G) technology is the most recent advancement in a wireless communication network. There is the advent of using the 5G with diverse data structures. The Blockchain (BC) has become an approving adoption for decentralized, peer-to-peer, distributed transparent ledger systems with a diverse data structure. The use of 5G with BC is an emerging trend in communication technology. The elasticity of 5G with BC enables many applications to reciprocity information molds it a fast, transparent, consequential, and safe for transportation of data in this smart era. Green computing (GC) is presently the intense optimistic tactic for the integration of smart technology in a diverse and distributed world of power consumption. This Systematic Mapping Study (SMS) has been analyzed by cautiously elected publications between 2016 and 2020 in well-putative venus. This study analyzed the advanced research on power consumption solutions for BC-based 5G communication, Moreover, a taxonomy of 5G based on green BC and GC in various areas is presented. Furthermore, Green energy renewable communication (GERC) problems are being observed in this research by integrating three discrete technologies such as 5G with green BC and GC also along with smart systems. Lastly, the research gaps had been bestowed to render future directions for the researchers in 5G with green BC and GC as the solution for rechargeable data packets.

The Impact of Green ICT Adoption in Organizations of Developing Countries

Abstract: Green information and communication technology (Green ICT) is a new term that follows purchasing and using though into how ICT is possible used to minimize various aspects of our environmental impact and goes on to address how the use of smart technology could make many other processes more efficient. This paper describes the factors that influence on organizations that adopt (Green ICT) in Iraq. Many questionnaires were distributed among managers of Iraqi organizations, where fuzzy logic system is used for analyzing them. the researchers find many results in this paper, the most significant result is the adoption of Green ICT by organizations in Iraq are probably affected by several factors which are costs, government legislation, political and social pressures, enlighten self-interest, the responsibility of environmental system business, and new opportunities of the market and this effect can be negative or positive according to the environmental and political conditions.