Biblio

Cloud computing is a model of service provisioning in heterogeneous distributed systems that encourages many researchers to explore its benefits and drawbacks in executing workflow applications. Recently, high-quality security protection has been a new challenge in workflow allocation. Different tasks may and may not have varied security demands, security overhead may vary for different virtual machines (VMs) at which the task is assigned. This paper proposes a Security Oriented Deadline-Aware workflow allocation (SODA) strategy in an IaaS cloud environment to minimize the risk probability of the workflow tasks while considering the deadline met in a deterministic environment. SODA picks out the task based on the highest security upward rank and assigns the selected task to the trustworthy VMs. SODA tries to simultaneously satisfy each task’s security demand and deadline at the maximum possible level. The simulation studies show that SODA outperforms the HEFT strategy on account of the risk probability of the cloud system on scientific workflow, namely CyberShake.

Bus factor is a metric that identifies how resilient is the project to the sudden engineer turnover. It states the minimal number of engineers that have to be hit by a bus for a project to be stalled. Even though the metric is often discussed in the community, few studies consider its general relevance. Moreover, the existing tools for bus factor estimation focus solely on the data from version control systems, even though there exists other channels for knowledge generation and distribution. With a survey of 269 engineers, we find that the bus factor is perceived as an important problem in collective development, and determine the highest impact channels of knowledge generation and distribution in software development teams. We also propose a multimodal bus factor estimation algorithm that uses data on code reviews and meetings together with the VCS data. We test the algorithm on 13 projects developed at JetBrains and compared its results to the results of the state-of-the-art tool by Avelino et al. against the ground truth collected in a survey of the engineers working on these projects. Our algorithm is slightly better in terms of both predicting the bus factor as well as key developers compared to the results of Avelino et al. Finally, we use the interviews and the surveys to derive a set of best practices to address the bus factor issue and proposals for the possible bus factor assessment tool.

This paper presents a brief introduction to Cyber-IR@MIT—a dynamic, interactive knowledge and networking system focused on the evolving, diverse, and complex interconnections of cyberspace and international relations. The goal is to highlight key theoretical, substantive, empirical and networking issues. Cyber-IR@MIT is anchored in a multidimensional ontology. It was initially framed as an experiment during the MIT-Harvard collaboration on Explorations in Cyber International Relations (MIT, 2009-2014) to serve as a forum for quality-controlled content and materials generated throughout the research project. The vision for Cyber-IR@MIT is shaped by the research for Cyberpolitics in International Relations, a book written by Nazli Choucri and published by MIT Press in 2012. The operational approach to the knowledge system is influenced by the Global System for Sustainable Development (GSSD), developed earlier and focused on challenges of system sustainability. Cyber-IR@MIT gradually evolved into a knowledge-based system of human interactions in cyberspace and international relations, all embedded in the overarching natural system. The method consists of differentiating among the various facets of human activity in (i) cyberspace, (ii) international relations, and (iii) the intersection of the cyber and “real.” It includes problems created by humans and solution strategies, as well as enabling functions and capabilities, on the one hand, and impediments to behavior and associated barriers, on the other. See https://cyberir.mit.edu for functions. The value of this initiative lies in its conceptual foundations and method of knowledge representation – embedded in an interactive system for knowledge submission, with f search and retrieval functions.

Development of large-scale and complex software systems requires multiple teams, including software development teams, domain experts, user representatives, and other project stakeholders, to work collaboratively to achieve software development goals. These teams rely on the use of agreed software development processes, knowledge management tools, and communication channels collaboratively in the software development project. Software testing is an important and complicated process due to reasons such as difficulties in achieving testing goals with the given time constraint, absence of efficient data sharing policies, vague testing acceptance criteria at various levels of testing, and lack of trusted coordination among the teams involved in software testing. The efficiency of the software testing relies on efficient, reliable, and trusted information sharing among these teams. Existing approaches to software testing for collaborative software development use centralized or decentralize tools for software testing, knowledge management, and communication channels. Existing approaches have the limitations of centralized authority, a single point of failure/compromise, lack of automatic requirement compliance checking and transparency in information sharing, and lack of unified data sharing policy, and reliable knowledge management repositories for sharing and storing past software testing artifacts and data. In this paper, a software testing approach for collaborative software development using private blockchain is presented, and the desirable properties of private blockchain, such as distributed data management, tamper-resistance, auditability and automatic requirement compliance checking, are incorporated to greatly improve the quality of software testing for collaborative software development.

Information Technology (IT) is a complex domain. In order to properly manage IT related processes, several frameworks including ITIL (Information Technologies Infrastructure Library), COBIT (Control OBjectives for Information and related Technologies), IT Service CMMI (IT Service Capability Maturity Model) and many others have emerged in recent decades. Meanwhile, the prevalence of Agile methods has increased, posing the coexistence of Agile approach with different IT frameworks already adopted in organizations. More specifically, the pursuit of being agile in the area of digitalization pushes organizations to go for agile transformation while preserving full compliance to IT frameworks for the sake of their survival. The necessity for this coexistence, however, brings its own challenges and solutions for harmonizing the requirements of both parties. In this paper, we focus on harmonizing the requirements of COBIT and Scrum in a same organization, which is especially challenging when a full compliance to COBIT is expected. Therefore, this study aims to identifying the challenges of and possible solutions for the coexistence of Scrum and COBIT (version 4.1 in this case) in an organization, by considering two case studies: one from the literature and the case of Akbank delivered in this study. Thus, it extends the corresponding previous case study from two points: adds one more case study to enrich the results from the previous case study and provides more opportunity to make generalization by considering two independent cases.

The aim of this research paper is to highlight the intellectual property place and role within an industrial knowledge-based organization which performs design activities. The research begins by presenting the importance of integrating intellectual property policy implementation with quality policy. The research is based on the setting of objectives in the intellectual property field. This research also establishes some intellectual property strategies, and improvement measures for intellectual property protection management. The basis for these activities is correlation of the quality policy with an intellectual property policy, as well as the point of strength identified in the studied organization. The issues discussed in this scientific paper conclude on the possibility of the implementation of standards in the intellectual property field.

Agile methods frequently have difficulties with qualities, often specifying quality requirements as stories, e.g., "As a user, I need a safe and secure system." Such projects will generally schedule some capability releases followed by safety and security releases, only to discover user-developer misunderstandings and unsecurable agile code, leading to project failure. Very large agile projects also have further difficulties with project velocity and scalability. Examples are trying to use daily standup meetings, 2-week sprints, shared tacit knowledge vs. documents, and dealing with user-developer misunderstandings. At USC, our Parallel Agile, Executable Architecture research project shows some success at mid-scale (50 developers). We also examined several large (hundreds of developers) TRW projects that had succeeded with rapid, high-quality development. The paper elaborates on their common Critical Quality Factors: a concurrent 3-team approach, an empowered Keeper of the Project Vision, and a management approach emphasizing qualities.

As we are living in the era of big data, high volumes of wide varieties of data which may be of different veracity (e.g., precise data, imprecise and uncertain data) are easily generated or collected at a high velocity in many real-life applications. Embedded in these big data is valuable knowledge and useful information, which can be discovered by big data science solutions. As a popular data science task, frequent pattern mining aims to discover implicit, previously unknown and potentially useful information and valuable knowledge in terms of sets of frequently co-occurring merchandise items and/or events. Many of the existing frequent pattern mining algorithms use a transaction-centric mining approach to find frequent patterns from precise data. However, there are situations in which an item-centric mining approach is more appropriate, and there are also situations in which data are imprecise and uncertain. Hence, in this paper, we present an item-centric algorithm for mining frequent patterns from big uncertain data. In recent years, big data have been gaining the attention from the research community as driven by relevant technological innovations (e.g., clouds) and novel paradigms (e.g., social networks). As big data are typically published online to support knowledge management and fruition processes, these big data are usually handled by multiple owners with possible secure multi-part computation issues. Thus, privacy and security of big data has become a fundamental problem in this research context. In this paper, we present, not only an item-centric algorithm for mining frequent patterns from big uncertain data, but also a privacy-preserving algorithm. In other words, we present- in this paper-a privacy-preserving item-centric algorithm for mining frequent patterns from big uncertain data. Results of our analytical and empirical evaluation show the effectiveness of our algorithm in mining frequent patterns from big uncertain data in a privacy-preserving manner.

Climate change has affected the cultivation in all countries with extreme drought, flooding, higher temperature, and changes in the season thus leaving behind the uncontrolled production. Consequently, the smart farm has become part of the crucial trend that is needed for application in certain farm areas. The aims of smart farm are to control and to enhance food production and productivity, and to increase farmers' profits. The advantages in applying smart farm will improve the quality of production, supporting the farm workers, and better utilization of resources. This study aims to explore the research trends and identify research clusters on smart farm using bibliometric analysis that has supported farming to improve the quality of farm production. The bibliometric analysis is the method to explore the relationship of the articles from a co-citation network of the articles and then science mapping is used to identify clusters in the relationship. This study examines the selected research articles in the smart farm field. The area of research in smart farm is categorized into two clusters that are soil carbon emission from farming activity, food security and farm management by using a VOSviewer tool with keywords related to research articles on smart farm, agriculture, supply chain, knowledge management, traceability, and product lifecycle management from Web of Science (WOS) and Scopus online database. The major cluster of smart farm research is the soil carbon emission from farming activity which impacts on climate change that affects food production and productivity. The contribution is to identify the trends on smart farm to develop research in the future by means of bibliometric analysis.

Transportation costs for road transport companies may be intensified by rising fuel prices, levies, traffic congestion, etc. Of particular concern to the Mpact group of companies is the long waiting times in the queues at loading and offloading points at three processing mills in the KZN (KwaZulu-Natal) province in South Africa. Following a survey among the drivers who regularly deliver at these sites, recommendations for alleviating the lengthy waiting times are put forward. On the strength of one of these recommendations, namely the innovative use of ICTs, suggestions on how cloud-based technologies may be embraced by the company are explored. In the process, the value added by a cloud-based supply chain, enterprise systems, CRM (Customer Relationship Management) and knowledge management is examined.

Identity verification plays an important role in creating trust in the economic system. It can, and should, be done in a way that doesn't decrease individual privacy.