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Demand for digital services is increasing significantly. Addressing energy efficiency at the data center mechanical and electrical infrastructure level is starting to suffer from the law of diminishing returns. IT equipment, specifically servers, account for a significant part of the overall facility energy consumption and environmental impact, and thus, present a major opportunity, not the least from a circular economy perspective. To reduce the environmental impact of servers, it is important to realize the effect of manufacturing, operating, and disposing of servers on the environment. This work presents new insights into the effect of refreshing servers with remanufactured and refurbished servers on energy efficiency and the environment. The research takes into consideration the latest changes in CPU design trends and Moore’s law. The study measures and analyzes the use phase energy consumption of remanufactured servers vs new servers with various hardware configurations. Case studies are used to evaluate the potential impact of refurbished server refresh from an economic as well as environmental perspectives.

Data centers have been highlighted as a major energy consumer and there has been an increasing trend towards the consolidation of smaller data centers into larger facilities. Yet, small data centers exist for a variety of reasons and account for a significant portion of the total number of servers in the US. Frequent refreshes of IT hardware has emerged as a trend in hyper-scale data centers but little attention has been paid to how these savings can be achieved in small data centers. This work provides a comprehensive framework for the energy saving opportunities, while determining when a return on investment can be achieved to enable small data center operators to create credible business cases for hardware refreshes. Various data center deployment scenarios are used as case studies (based on real-life datasets) to validate the proposed concepts.

Rapid changes in security threat landscapes cause uncertainty for IT operations and security professionals and may force changes to organizations’ security strategy. Decision support data that help reduce ambiguity or even predict future developments in this regard can thus be of economic value. Based on over 200 security predictions published in 2015, we use a topic modeling approach to identify 17 underlying predicted threat developments. To verify the extent to which these predicted threat topics were realized in 2016, we solicited opinions from respondents with varying experience of IT and information security. In addition, we reviewed secondary sources to corroborate the survey results. Based on the presented findings, we conclude that the security predictions for 2016 did foresee notable developments in that year. The identified latent predictions were related to hacking political campaigns, large-scale data breaches of personal data and health records, increasing threats from various types of malware, specifically ransomware, and large-scale DDoS attacks. The findings of this research are relevant to IT executives and security professionals, who can apply this approach to improve the effectiveness of organizations’ technology and cyber security strategy.

As part of our software architecture research and practice we have found that a common difficulty for new architects is knowing where to focus their attention to maximise their effectiveness. This led us to wonder whether successful experienced architects have any common techniques or heuristics that they use to help them achieve this. In an earlier study where, having interviewed experienced architects, we found that in fact there were some common heuristics that they use, we created a simple model based on an analysis of their advice. In this paper we explain how we validated that model with a wider survey of experienced enterprise and software architects and, from the findings of that study, extended the model with an additional dimension. This resulted in our model having four primary guidelines, which are: focus on stakeholder needs and priorities, prioritise time according to risks, delegate as much as possible, and ensure team effectiveness.

The environmental impact of data centers has become a major concern. In their Q1 2021 report, Intel estimated that there are around 100 million servers deployed globally. In this paper we provide an overview of Interact, a machine learning tool that helps data center operators easily analyze, manage, and optimize the energy, cost, and Carbon footprint of their current servers and infrastructure. We discuss in detail the machine learning algorithms and the energy models used. We also demonstrate the key features of the tool and how it can help data centers become more sustainable by reducing server inefficiencies.

Data is rapidly becoming one of the most important assets in global markets, and criminals are spotting opportunities to exploit new potential income sources. In response to this, organizations are dedicating increasing resources to information security programs. However, faced with unrelenting breach reports and rising costs, decision makers inevitably wonder which type of security investment is economically viable. In this article, the authors present an empirically tested model describing the underlying key constructs for assessing information security value in an organization. Based on identified latent variables previously put forward in the literature, the authors use a partial least squares structural equation modeling approach to verify the model's soundness. They identify five crucial variables for value-focused information security investment. The relationships among these latent variables are then investigated and contributions of the structural model assessed. The key findings are finally presented to highlight opportunities for security practitioners to apply the proposed model.

This article describes how with information security steadily moving up on board room agendas, security programs are found to be under increasing scrutiny by practitioners. This level of attention by senior business leaders is new to many security professionals as their field has been of limited interest to non-executive directors so far. Currently, they have to regularly report on efficiency and value of their security capabilities whilst being measured against business priorities. Based on the Grounded Theory approach, the authors analysed the data gathered in a series of interviews with senior professionals in order to identify key factors in the context of information security investment decisions. The authors present detailed findings in context of a simplified framework that security practitioners can utilise for critical review or improvements of investment decisions in their own environments. Extensive details for each category as extracted through a qualitative data analysis are provided along with a category network analysis that highlights strong relationships within the framework.

Optimizing the energy consumption of today's Internet-scale systems will require a radical approach that considers the whole system. To address system-level energy efficiency, software architects can follow three simple design principles. A case study illustrates the possible savings.

Software product lines (SPL) aim at reducing time-to-market and increasing software quality through extensive, planned reuse of artifacts. An essential activity in SPL is variability management, i.e., defining and managing commonality and variability among member products. Due to the large scale and complexity of today's software-intensive systems, variability management has become increasingly complex to conduct. Accordingly, tool support for variability management has been gathering increasing momentum over the last few years and can be considered a key success factor for developing and maintaining SPLs. While several studies have already been conducted on variability management, none of these analyzed the available tool support in detail. In this work, we report on a survey in which we analyzed 37 existing variability management tools identified using a systematic literature review to understand the tools’ characteristics, maturity, and the challenges in the field. We conclude that while most studies on variability management tools provide a good motivation and description of the research context and challenges, they often lack empirical data to support their claims and findings. It was also found that quality attributes important for the practical use of tools such as usability, integration, scalability, and performance were out of scope for most studies.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) This chapter presents the authors’ work for the Case Study entitled “Delivering Social Media with Scalability” within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the aforementioned action. The ease of user content generation within social media platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges: derivation of real-time meaningful insights from effectively gathered social information, a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general, etc. In this article we present the methodology we followed, the results of our work and the outline of a comprehensive survey, that depicts the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centers supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. The challenges of enabling better provisioning of social media data have been identified and they were based on the context of users accessing these resources. The existing literature has been systematized and the main research points and industrial efforts in the area were identified and analyzed. In our works, in the framework of the Action, we came up with potential solutions addressing the problems of the area and described how these fit in the general ecosystem.

Research on technological aspects of information security risk is a well-established area and familiar territory for most information security professionals. The same cannot be said about the economic value of information security investments in organisations. While there is an emerging research base investigating suitable approaches measuring the value of investments in information security, it remains difficult for practitioners to identify key approaches in current research. To address this issue, we conducted a systematic literature review on approaches used to evaluate investments in information security. Following a defined review protocol, we searched several databases for relevant primary studies and extracted key details from the identified studies to answer our research questions. The contributions of this work include: a comparison framework and a catalogue of existing approaches and trends that would help researchers and practitioners navigate existing work; categorisation and mapping of approaches according to their key elements and components; and a summary of key challenges and benefits of existing work, which should help focus future research efforts.

Purpose – This study aims to examine the influence of one or more information security breaches on an organisation’s stock market value as a way to benchmark the wider economic impact of such events. Design/methodology/approach – An event studies-based approach was used where a measure of the event’s economic impact can be constructed using security prices observed over a relatively short period of time. Findings – Based on the results, it is argued that, although no strong conclusions could be made given the current data constraints, there was enough evidence to show that such correlation exists, especially for recurring security breaches. Research limitations/implications – One of the main limitations of this study was the quantity and quality of published data on security breaches, as organisations tend not to share this information. Practical implications – One of the challenges in information security management is assessing the wider economic impact of security breaches. Subsequently, this helps drive investment decisions on security programmes that are usually seen as cost rather than moneymaking initiatives. Originality/value – This study envisaged that as more breach event data become more widely available because of compliance and regulatory changes, this approach has the potential to emerge as an important tool for information security managers to help support investment decisions.

Given environmentalism's rising tide and increasing energy prices and IT workloads, architects must determine whether they can continue designing systems without considering energy and power efficiency.

Information security is a main concern for many organisations with no signs of decreasing urgency in the coming years. To address this a structured approach is required, with the ISO 27000 series being one of the most popular practices for managing Information Security. In this work, we used a combination of qualitative research methods to conduct a SWOT analysis on the ISMS. The findings from the SWOT were then validated using a survey instrument. Finally, the results were validated and analysed using statistical methods. Our findings show that there was a generally positive view on the 'Strengths' and 'Opportunities' compared to that of 'Weaknesses' and 'Threats'. We identified statistically significant differences in the perception of 'Strengths' and 'Opportunities' across groups but also found that there is no significant variance in the perception of 'Threats'. The SWOT produced will help practitioners and researchers tailor ways to enhance ISMS using existing techniques such as TOWS matrix.

Purpose – This paper aims to focus on applying a range of traditional classification- and semantic reasoning-based techniques to recognise activities of daily life (ADLs). ADL recognition plays an important role in tracking functional decline among elderly people who suffer from Alzheimer’s disease. Accurate recognition enables smart environments to support and assist the elderly to lead an independent life for as long as possible. However, the ability to represent the complex structure of an ADL in a flexible manner remains a challenge. Design/methodology/approach – This paper presents an ADL recognition approach, which uses a hierarchical structure for the representation and modelling of the activities, its associated tasks and their relationships. This study describes an approach in constructing ADLs based on a task-specific and intention-oriented plan representation language called Asbru. The proposed method is particularly flexible and adaptable for caregivers to be able to model daily schedules for Alzheimer’s patients. Findings – A proof of concept prototype evaluation has been conducted for the validation of the proposed ADL recognition engine, which has comparable recognition results with existing ADL recognition approaches. Originality/value – The work presented in this paper is novel, as the developed ADL recognition approach takes into account all relationships and dependencies within the modelled ADLs. This is very useful when conducting activity recognition with very limited features.

We report on the experience gained using an ADL to model a large information system.Specialised ADL can have benefits over a general modelling language like UML.The ADL's graphical notation plays an important role in its adoption and acceptance.Familiar tool support and availability of guide material directly impact uptake. An organisation that had developed a large information system wanted to embark on a programme that would involve large-scale evolution of it. As a precursor to this, it was decided to create a comprehensive architectural description to capture and understand the system's design. This undertaking faced a number of challenges, including a low general awareness of software modelling and software architecture practices. The approach taken by the software architects tasked with this project included the definition of a simple, very specific, architecture description language. This paper reports our experience of the project and a simple ADL that we created as part of it.

With the rising energy demand in ICT services and its associated environmental impact, the need for energy efficient Enterprise ICT solutions is growing. As data centres account for a large part of energy consumption in ICT, data centre operators strive to create opportunities to put more emphasis on reducing energy consumption. However, creating ICT Systems that are energy efficient by design remains a key challenge. In this paper, we identify and map contextual energy information about data centre operations in order to model their power related components. This contextual modelling is then mapped to deployment diagram where we introduce greenUML (gUML), an extension to UML diagrams to improve energy efficiency through energy analysis at design time. gUML will allow system architects to reason about the energy footprint of their applications at design time.