Green Data Centers Research Articles

Smart-Middleware for Establishing Fault-Tolerant And Smart Monitoring Systems For Green Data Centers

Monitoring systems can become more robust, flexible, scalable and smart through the implementation of a smart software layer. Such a software can be termed as middleware as it filters and provides data to applications and is independent of how data is propagated from source to a remote data-repository such as a database. The data is collected from a set of possibly heterogeneous sensors, among which some sensors can have processing capabilities to run the proposed middleware. Smart-rules are used to process and filter the sensed data and to initiate appropriate reactive routines according to the sensed data. All these features, make the proposed middleware as a smart-middleware. The capable sensors with such a smart-middleware can filter data according to smart rules. Additionally, with the help of the proposed smart-middleware, the capable sensors can collect, filter as well as aggregate data from other sensors in a hierarchical manner. This also results in reduced data volume and overall power consumption to process this data. Complemented with smart algorithm for fault tolerance and scalability, this paper presents the architecture of a middleware for smart monitoring systems in green data centers.

I Q R based Approach for Energy Efficient Dynamic VM Consolidation for Green Cloud Data Centers

the advent of cloud computing in the arena of IT field energy consumption and service level agreement (SLA) violation emerge as a major problem, which reduces the profit of cloud service providers (CSP) and affect the cloud customers by fencing the reusability and scalability of the cloud data center services. This problem needs to be eradicate for the efficient resource provisioning in cloud data center. To satisfy the customer need virtual machine (VM) migration technique is required to balance the load of entire data center. Therefore we need to transfer the virtual machine of the overloaded host to the light weighted host using virtual machine migration technique. Due to frequent load balancing of cloud data center enormous amount of energy consumption takes place. This enhances the overall energy cost and degrades the performance of cloud data center. This paper proposes an Energy Efficient Dynamic VM Consolidation algorithm for reducing energy consumption. Keywordscomputing, Cloud service provider (CSP), Energy consumption, SLA violation, Load balancing, VM migration.

Green Business Practices for Software Development Companies

This paper reports the findings of a text analysis of the corporate sustainability reports of eleven large scale Indian Software Development Businesses for the period of 2012 to 2014. The results shows that there are twenty two reported components of software development sustainability namely green buildings, green energy, green factory, green data centres, green infrastructure, green initiatives, green innovation, green packaging, green portfolio, green power, green practices, green procurement, green products, green program, green rating, green solutions, green space, green team, green tech and green supply chain which are addressed in the published reports of Indian software development businesses. The reports were further analysed to infer some knowledge on how the software development companies could contribute to green environment and the possible environmental impacts of these contributions. Finally a number of generalised conclusions were derived and followed by a set of implications for best practices in green software development as the outcome of the research reported in this paper.

Pricing Bilateral Electricity Trade between Smart Grids and Hybrid Green Datacenters

Datacenter demand response is envisioned as a promising approach for mitigating operational instability faced by smart grids. It enables significant potentials in peak load shedding and facilitates the incorporation of distributed generation and intermittent energy sources. This work considers two key aspects towards realtime electricity pricing for eliciting demand response: (i) Two-way electricity flow between smart grids and large datacenters with hybrid green generation capabilities. (ii) The geo-distributed nature of large cloud systems, and hence the potential competition among smart grids that serve different datacenters of the cloud. We propose a pricing scheme tailored for geo-distributed green datacenters, from a multi-leader single-follower game point of view. At the cloud side, in quest for performance, scalability and robustness, the energy cost is minimized in a distributed manner, based on the technique of alternating direction of multipliers (ADMM). At the smart grid side, a practical equilibrium of the pricing game is desired. To this end, we employ mathematical programming with equilibrium constraints (MPEC), equilibrium problem with equilibrium constraints (EPEC) and exact linearization, to transform the multi-leader single-follower pricing game into a mixed integer linear program (MILP) that can be readily solved. The effectiveness of the proposed solutions is evaluated based on trace-driven simulations.

Service-Oriented Virtual Machine Placement Optimization for Green Data Center

The first service-oriented virtual machine (VM) placement for green data center is designed in this work. Integer Linear Programming (ILP) is the problem design basis. The Tree algorithm is propose...

Green data centers for cloud-assisted mobile ad hoc networks in 5G

Cloud-assisted mobile ad-hoc networks are expected to be so popular in future fifth generation (5G) mobile network because the significantly faster performance of 5G communications enables clouds to provide realistic services. On the other hand, the energy consumption problem will become serious due to the highly increased cloud computing speed. Mobile communication link loss occurs when a mobile device leaves the network. Link loss can cause serious energy consumption when the lost link is directly connected to a cloud data server, which is required to do excessive searching and link routing transactions. None of the existing normal methods have solved the problem. We show how this problem can be solved using our proposed mechanism. The experimental results demonstrate that our proposed mechanism saves nine times more energy than normal methods.

Green Cloud and reduction of energy consumption

By using global application environments, cloud computing based data centers growing every day and this exponentially grows definitely effect on our environment. Researchers that have a commitment to their environment and others which was concerned about the electricity bills came up with a solution which called “Green Cloud”. Green cloud data centers based on how consume energy are known as high efficient data centers. In green cloud we try to reduce number of active devices and consume less electricity energy. In green data centers toke an advantage of VM and ability of copying, deleting and moving VMs over the data center and reduce energy consumption. This paper focused on which parts of data centers may change and how researchers found the suitable solution for each component of data centers. Also with all these problems why still the cloud data centers are the best technology for IT businesses.

Thermal-Aware Scheduling in Green Data Centers

Data centers can go green by saving electricity in two major areas: computing and cooling. Servers in data centers require a constant supply of cold air from on-site cooling mechanisms for reliability. An increased computational load makes servers dissipate more power as heat and eventually amplifies the cooling load. In thermal-aware scheduling, computations are scheduled with the objective of reducing the data-center-wide thermal gradient, hotspots, and cooling magnitude. Complemented by heat modeling and thermal-aware monitoring and profiling, this scheduling is energy efficient and economical. A survey is presented henceforth of thermal-ware scheduling and associated techniques for green data centers.

Thermal-aware relocation of servers in green data centers

Rise in inlet air temperature increases the corresponding outlet air temperature from the server. As an added effect of rise in inlet air temperature, some active servers may start exhaling intensely hot air to form a hotspot. Increase in hot air temperature and occasional hotspots are an added burden on the cooling mechanism and result in energy wastage in data centers. The increase in inlet air temperature may also result in failure of server hardware. Identifying and comparing the thermal sensitivity to inlet air temperature for various servers helps in the thermal-aware arrangement and location switching of servers to minimize the cooling energy wastage. The peak outlet temperature among the relocated servers can be lowered and even be homogenized to reduce the cooling load and chances of hotspots. Based upon mutual comparison of inlet temperature sensitivity of heterogeneous servers, this paper presents a proactive approach for thermal-aware relocation of data center servers. The experimental results show that each relocation operation has a cooling energy saving of as much as 2.1 kW·h and lowers the chances of hotspots by over 77%. Thus, the thermal-aware relocation of servers helps in the establishment of green data centers.

Energy-Efficient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues

Smart grid has modernized the way electricity is generated, transported, distributed, and consumed by integrating advanced sensing, communications, and control in the day-to-day operation of the grid. Electricity is a core utility for the functioning of society and for the services provided by information and communication technologies (ICTs). Several concepts of the smart grid, such as dynamic pricing, distributed generation, and demand management, have significantly impacted the operation of ICT services, in particular, communication networks and data centers. Ongoing energy-efficiency and operational expenditures reduction efforts in communication networks and data centers have gained another dimension with those smart grid concepts. In this paper, we provide a comprehensive survey on the smart grid-driven approaches in energy-efficient communications and data centers, and the interaction between smart grid and information and communication infrastructures. Although the studies on smart grid, energy-efficient communications, and green data centers have been separately surveyed in previous studies, to this end, research that falls in the intersection of those fields has not been properly classified and surveyed yet. We start our survey by providing background information on the smart grid and continue with surveying smart grid-driven approaches in energy-efficient communication systems, followed by energy, cost and emission minimizing approaches in data centers, and the corresponding cloud network infrastructure. We discuss the open issues in smart grid-driven approaches in ICTs and point some important research directions such as the distributed renewable energy generation capability-coupled communication infrastructures, optimum energy-efficient network design for the smart grid environment, the impact of green communication techniques on the reliability and latency requirements of smart grid data, workload consolidation with smart grid-awareness, and many more.

Green Internet of Things for Smart World

Smart world is envisioned as an era in which objects (e.g., watches, mobile phones, computers, cars, buses, and trains) can automatically and intelligently serve people in a collaborative manner. Paving the way for smart world, Internet of Things (IoT) connects everything in the smart world. Motivated by achieving a sustainable smart world, this paper discusses various technologies and issues regarding green IoT, which further reduces the energy consumption of IoT. Particularly, an overview regarding IoT and green IoT is performed first. Then, the hot green information and communications technologies (ICTs) (e.g., green radio-frequency identification, green wireless sensor network, green cloud computing, green machine to machine, and green data center) enabling green IoT are studied, and general green ICT principles are summarized. Furthermore, the latest developments and future vision about sensor cloud, which is a novel paradigm in green IoT, are reviewed and introduced, respectively. Finally, future research directions and open problems about green IoT are presented. Our work targets to be an enlightening and latest guidance for research with respect to green IoT and smart world.

A Tree Regression-Based Approach for VM Power Metering

Cloud computing is developing so fast that more and more data centers have been built every year. This naturally leads to high-power consumption. Virtual machine (VM) consolidation is the most popular solution based on resource utilization. In fact, much more power can be saved if we know the power consumption of each VM. Therefore, it is significant to measure the power consumption of each VM for green cloud data centers. Since there is no device that can directly measure the power consumption of each VM, modeling methods have been proposed. However, current models are not accurate enough when multi-VMs are competing for resources on the same server. One of the main reasons is that the resource features for modeling are correlated with each other, such as CPU and cache. In this paper, we propose a tree regression-based method to accurately measure the power consumption of VMs on the same host. The merits of this method are that the tree structure will split the data set into partitions, and each is an easy-modeling subset. Experiments show that the average accuracy of our method is about 98% for different types of applications running in VMs.

Toward Low-Cost Workload Distribution for Integrated Green Data Centers

This paper aims at maximizing the utilization of green energy and cutting the cost of electricity associated in provisioning computing services across a group of data centers. To this end, we propose the notion of green workload and green service rate, versus brown workload and brown service rate, respectively, to facilitate the separation of green energy utilization maximization and brown energy cost minimization problems. Accordingly, a workload distribution algorithm is designed such that the cost of electricity is reduced as compared with the existing workload distribution schemes.

Security and Optimization Challenges of Green Data Centers

Energy consumption in data centers has grown out of proportion in regard to the state of energy that’s available in the universe. Technology has improved services and its application. The need for eco-friendly energy and increase in data centers performance brought about Green Computing into the energy consumption of data centers. Information technology has grown and eaten deep into the society that almost all the sectors if not all are dependent on information technology to move on. The consumption of power has increased greatly. In this research paper the techniques for optimizing energy in data centers for Green Computing would be discussed. This study intends to expose the limitations of existing security solutions for securing data centers by taking into consideration of limitations of existing security frameworks that cannot enhance the security of data centers.

Optical interconnects at the top of the rack for energy-efficient data centers

The growing popularity of cloud and multimedia services is dramatically increasing the traffic volume that each data center needs to handle. This is driving the demand for highly scalable, flexible, and energy-efficient networks inside data centers, in particular for the edge tier, which requires a large number of interconnects and consumes the dominant part of the overall power. Optical fiber communication is widely recognized as the highest energy- and cost-efficient technique to offer ultra-large capacity for telecommunication networks. It has also been considered as a promising transmission technology for future data center applications. Taking into account the characteristics of the traffic generated by the servers, such as locality, multicast, dynamicity, and burstiness, the emphasis of the research on data center networks has to be put on architectures that leverage optical transport to the greatest possible extent. However, no feasible solution based on optical switching is available so far for handling the data center traffic at the edge tier. Therefore, apart from conventional optical switching, we investigate a completely different paradigm, passive optical interconnects, and aim to explore the possibility for optical interconnects at the top of the rack. In this article, we present three major types of passive optical interconnects and carry out a performance assessment with respect to the ability to host data center traffic, scalability, optical power budget, complexity of the required interface, cost, and energy consumption. Our results have verified that the investigated passive optical interconnects can achieve a significant reduction of power consumption and maintain cost at a similar level compared to its electronic counterpart. Furthermore, several research directions on passive optical interconnects have been pointed out for future green data centers.

On the feasibility of collaborative green data center ecosystems

The increasing awareness of the impact of the IT sector on the environment, together with economic factors, have fueled many research efforts to reduce the energy expenditure of data centers. Recent work proposes to achieve additional energy savings by exploiting, in concert with customers, service workloads and to reduce data centers’ carbon footprints by adopting demand-response mechanisms between data centers and their energy providers. In this paper, we debate about the incentives that customers and data centers can have to adopt such measures and propose a new service type and pricing scheme that is economically attractive and technically realizable. Simulation results based on real measurements confirm that our scheme can achieve additional energy savings while preserving service performance and the interests of data centers and customers.

Matching renewable energy supply and demand in green datacenters

In this paper, we propose GreenSlot, a scheduler for parallel batch jobs in a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot predicts the amount of solar energy that will be available in the near future, and schedules the workload to maximize the green energy consumption while meeting the jobs’ deadlines. If grid energy must be used to avoid deadline violations, the scheduler selects times when it is cheap. Evaluation results show that GreenSlot can increase solar energy consumption by up to 117% and decrease energy cost by up to 39%, compared to conventional schedulers, when scheduling three scientific workloads and a data processing workload. Based on these positive results, we conclude that green datacenters and green-energy-aware scheduling can have a significant role in building a more sustainable IT ecosystem.

The Design and Implementation of Data Center Autonomous System Based on Zigbee

Network is the foundation of education informationization, supporting campus teaching and scientific research. Data center functions as the nerves center of the whole network that plays the crucial role for the stable operation of the network. Thus it should be guaranteed stable operation. Regarding to the problem that high-precision air conditioner remains high energy consumption of the entire data center, embedded web system - based technology is put forward in this paper. The technology uses MSP430 microprocessor, CS8900A network chip and temperature humidity sensor to construct long-distance intelligent monitoring system based on Zigbee terminal node equipment. Consequently it can be realized that high-precision air conditioner can be conducted quadratic optimal control through the system of the sum of environment temperature acquisition and control, and air condition linkage feedback. It is stated by the results that PUE of data center is reduced and a green and energy-efficient data center can be built by deploying the system.

Energy-Efficiency Classifying Mechanism for Green IT Framework of Big Data

Compared with the distributed processing, large data center focuses on information and communication tasks and has already made huge improvement on energy efficiency. But large data center includes tens of millions of servers, and its energy consumption can be ever larger than one small town. Huge energy consumption and tons of greenhouse gas emission bring many challenges to large data center in terms of energy efficiency and emission reduction. Therefore, the establishment of green and efficient large data center is imperative. This paper provides a framework of green IT for large data, focusing on energy efficiency classification and proposes an energy efficiency classification mechanism based on measurement model. According to the workload and energy consumption, this paper classifies the equipment and services seamlessly into different resource pool. Power efficiency, data center efficiency and carbon dioxide emissions are calculated and measured. This paper also formulates energy efficiency standards which could be realized and followed. The standards make the drawing of the big data center carbon trace possible and provide scheme for energy efficiency evaluation.

Green Cloud: An Energy Efficient Load Balancing Approach Using Global Load Optimization

High Performance Green Cloud Computing is an emerging field in the upcoming IT industry. With the main focus on balancing resource utilization in green cloud environment, IT applications need a highly rapid and scalable access services. Cyber Guarder Approach (CGA) based on trust management in green cloud facilitates access control to resources pool but the energy expenditure is of higher rate while balancing the load. One of the important aspects of green cloud being optimization of energy utilization, Energy-aware Allocation Policies (EAP) maximized the revenues. However, EAP policies increased the running server, resulting in higher amount of frequency and imbalance in running server during resource utilization in green cloud. For balancing the load on the Infrastructure as a Service (IaaS), an energy efficient load balancing approach using global load optimization (GC-GLO) method is presented on the green cloud data center in this paper. The energy efficient load balancing approach uses the Global Load Optimization (GLO) method to allocate the resources in a dynamic manner using the load factor in two ways. First, GC-GLO approach uses the logical hierarchy process to allocate the resources in the servers present in green cloud zone. The logical hierarchy process in GC-GLO selects the task in a hierarchical manner and allocates the task between cloud severs’ based on the resource need. With the exact form of resource utilization in GC-GLO, improves the utilization rate in the green cloud environment. Based on the resource utilization, the GC-GLO approach then uses the global load optimization algorithm to measure the load rate of each green cloud server. The energy expenditure on the resource allocation and the IaaS maintenance on the green cloud are eventually measured. The approach, GC-GLO has been validated by conducting careful performance measure study using CloudSim platform in terms of factors such as energy expenditure rate on IaaS maintenance, resource utilization rate and running time. The results demonstrate that global load optimization has extensive potential as it offers significant performance gains to load balancing efficiency and false positive rate under dynamic workload scenarios.