Green IT: Everything starts from the software

In this position paper we discuss the importance of Green IT as a new research field that investigates all the environmental and energy issues related to IT and information systems in general. In particular we focus on the energy consumption of software applications, which is amplified by all the above IT layers in a data center and thus is worth a greater attention. By adopting a top-down approach, we address the problem from a logical perspective and try to identify the original cause that leads to energy consumption, i.e. the elaboration of information. We propose a research roadmap to identify a set of software complexity and quality metrics that can be used to estimate energy consumption and to compare specific software applications

Cyber Physical Energy Systems Modules for Power Sharing Controllers in Inverter Based Microgrids

The Microgrids (MGs) are an effective way to deal with the smart grid challenges, including service continuity in the event of a grid interruption, and renewable energy integration. The MGs are compounded by multiple distributed generators (DGs), and the main control goals are load demand sharing and voltage and frequency stability. Important research has been reported to cope with the implementation challenges of the MGs including the power sharing control problem, where the use of cybernetic components such as virtual components, and communication systems is a common characteristic. The use of these cybernetic components to control complex physical systems generates new modeling challenges in order to achieve an adequate balance between complexity and accuracy in the MG model. The standardization problem of the cyber-physical MG models is addressed in this work, using a cyber-physical energy systems (CPES) modeling methodology to build integrated modules, and define the communication architectures that each power sharing control strategy requires in an AC-MG. Based on these modules, the control designer can identify the signals and components that eventually require a time delay analysis, communication requirements evaluation, and cyber-attacks’ prevention strategies. Similarly, the modules of each strategy allow for analyzing the potential advantages and drawbacks of each power sharing control technique from a cyber physical perspective

How to select measures for decision support systems - An optimization approach integrating informational and economic objectives

It is still an open issue of designing and adapting (data-driven) decision support systems and data warehouses to determine relevant content and in particular (performance) measures. In fact, some classic approaches to information requirements determination such as Rockart’s critical success factors method help with structuring decision makers’ information requirements and identifying thematically appropriate measures. In many cases, however, it remains unclear which and how many measures should eventually be used. Therefore, an optimization model is presented that integrates informational and economic objectives. The model incorporates (statistic) interdependencies among measures – i. e. the information they provide about one another –, decision makers’ and reporting tools’ ability of coping with information complexity as well as negative economic effects due to measure selection and usage. We show that in general the selection policies of all-or-none or themore- the-better are not reasonable although they are often conducted in business practice. Finally, the model’s application is illustrated by the German business-to-business sales organization of a global electronics and electrical engineering company as example. In this position paper we discuss the importance of Green IT as a new research field that investigates all the environmental and energy issues related to IT and information systems in general. In particular we focus on the energy consumption of software applications, which is amplified by all the above IT layers in a data center and thus is worth a greater attention. By adopting a top-down approach, we address the problem from a logical perspective and try to identify the original cause that leads to energy consumption, i.e. the elaboration of information. We propose a research roadmap to identify a set of software complexity and quality metrics that can be used to estimate energy consumption and to compare specific software application

Risk Management in the Arctic Offshore: Wicked Problems Require New Paradigms

Recent project-management literature and high-profile disasters—the financial crisis, the BP Deepwater Horizon oil spill, and the Fukushima nuclear accident—illustrate the flaws of traditional risk models for complex projects. This research examines how various groups with interests in the Arctic offshore define risks. The findings link the wicked problem framework and the emerging paradigm of Project Management of the Second Order (PM-2). Wicked problems are problems that are unstructured, complex, irregular, interactive, adaptive, and novel. The authors synthesize literature on the topic to offer strategies for navigating wicked problems, provide new variables to deconstruct traditional risk models, and integrate objective and subjective schools of risk analysis

A holistic multi-methodology for sustainable renovation

A review of the barriers for building renovation has revealed a lack of methodologies, which can promote sustainability objectives and assist various stakeholders during the design stage of building renovation/retrofitting projects. The purpose of this paper is to develop a Holistic Multi-methodology for Sustainable Renovation, which aims to deal with complexity of renovation projects. It provides a framework through which to involve the different stakeholders in the design process to improve group learning and group decision-making, and hence make the building renovation design process more robust and efficient. Therefore, the paper discusses the essence of multifaceted barriers in building renovation regarding cultural changes and technological/physical changes. The outcome is a proposal for a multi-methodology framework, which is developed by introducing, evaluating and mixing methods from Soft Systems Methodologies (SSM) with Multiple Criteria Decision Making (MCDM). The potential of applying the proposed methodology in renovation projects is demonstrated through a case study

A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks

Cell Switch-Off (CSO) is recognized as a promising approach to reduce the energy consumption in next-generation cellular networks. However, CSO poses serious challenges not only from the resource allocation perspective but also from the implementation point of view. Indeed, CSO represents a difficult optimization problem due to its NP-complete nature. Moreover, there are a number of important practical limitations in the implementation of CSO schemes, such as the need for minimizing the real-time complexity and the number of on-off/off-on transitions and CSO-induced handovers. This article introduces a novel approach to CSO based on multiobjective optimization that makes use of the statistical description of the service demand (known by operators). In addition, downlink and uplink coverage criteria are included and a comparative analysis between different models to characterize intercell interference is also presented to shed light on their impact on CSO. The framework distinguishes itself from other proposals in two ways: 1) The number of on-off/off-on transitions as well as handovers are minimized, and 2) the computationally-heavy part of the algorithm is executed offline, which makes its implementation feasible. The results show that the proposed scheme achieves substantial energy savings in small cell deployments where service demand is not uniformly distributed, without compromising the Quality-of-Service (QoS) or requiring heavy real-time processing

From Knowledge, Knowability and the Search for Objective Randomness to a New Vision of Complexity

Herein we consider various concepts of entropy as measures of the complexity of phenomena and in so doing encounter a fundamental problem in physics that affects how we understand the nature of reality. In essence the difficulty has to do with our understanding of randomness, irreversibility and unpredictability using physical theory, and these in turn undermine our certainty regarding what we can and what we cannot know about complex phenomena in general. The sources of complexity examined herein appear to be channels for the amplification of naturally occurring randomness in the physical world. Our analysis suggests that when the conditions for the renormalization group apply, this spontaneous randomness, which is not a reflection of our limited knowledge, but a genuine property of nature, does not realize the conventional thermodynamic state, and a new condition, intermediate between the dynamic and the thermodynamic state, emerges. We argue that with this vision of complexity, life, which with ordinary statistical mechanics seems to be foreign to physics, becomes a natural consequence of dynamical processes.Comment: Phylosophica