Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

Critical Management Issues for Implementing RFID in Supply Chain Management

The benefits of radio frequency identification (RFID) technology in the supply chain are fairly compelling. It has the potential to revolutionise the efficiency, accuracy and security of the supply chain with significant impact on overall profitability. A number of companies are actively involved in testing and adopting this technology. It is estimated that the market for RFID products and services will increase significantly in the next few years. Despite this trend, there are major impediments to RFID adoption in supply chain. While RFID systems have been around for several decades, the technology for supply chain management is still emerging. We describe many of the challenges, setbacks and barriers facing RFID implementations in supply chains, discuss the critical issues for management and offer some suggestions. In the process, we take an in-depth look at cost, technology, standards, privacy and security and business process reengineering related issues surrounding RFID technology in supply chains

Report of the Stanford Linked Data Workshop

The Stanford University Libraries and Academic Information Resources (SULAIR) with the Council on Library and Information Resources (CLIR) conducted at week-long workshop on the prospects for a large scale, multi-national, multi-institutional prototype of a Linked Data environment for discovery of and navigation among the rapidly, chaotically expanding array of academic information resources. As preparation for the workshop, CLIR sponsored a survey by Jerry Persons, Chief Information Architect emeritus of SULAIR that was published originally for workshop participants as background to the workshop and is now publicly available. The original intention of the workshop was to devise a plan for such a prototype. However, such was the diversity of knowledge, experience, and views of the potential of Linked Data approaches that the workshop participants turned to two more fundamental goals: building common understanding and enthusiasm on the one hand and identifying opportunities and challenges to be confronted in the preparation of the intended prototype and its operation on the other. In pursuit of those objectives, the workshop participants produced:1. a value statement addressing the question of why a Linked Data approach is worth prototyping;2. a manifesto for Linked Libraries (and Museums and Archives and …);3. an outline of the phases in a life cycle of Linked Data approaches;4. a prioritized list of known issues in generating, harvesting & using Linked Data;5. a workflow with notes for converting library bibliographic records and other academic metadata to URIs;6. examples of potential “killer apps” using Linked Data: and7. a list of next steps and potential projects.This report includes a summary of the workshop agenda, a chart showing the use of Linked Data in cultural heritage venues, and short biographies and statements from each of the participants

Practical requirements elicitation in modern product development: A multi-case study in discontinuous innovation

Practical modern product development, specifically rapid, lean efforts to create new disrupting or specialized products, face constraints that require modified requirements elicitation (RE) techniques. Requirements elicitation conventions have not been updated to address the challenges of these approaches, and industry practitioners lack the tools to select the most efficient techniques. This study examines the RE approaches performed by three resource-limited teams conducting discontinuous new product development through a multi-case study to identify gaps between the literature and practice, with suggestions to fill them. Our findings suggest modern RE practices and challenges closely reflect those found by studies on RE in agile development, highlighted by a limited variety of techniques and a focus on user feedback despite user unavailability, resulting in partially complete and validated requirements. We suggest further investigation into practical technique selection, development of technique metrics, and a technique selection literature review to practitioners prior to RE

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations

BDEv 3.0: energy efficiency and microarchitectural characterization of Big Data processing frameworks

This is a post-peer-review, pre-copyedit version of an article published in Future Generation Computer Systems. The final authenticated version is available online at: https://doi.org/10.1016/j.future.2018.04.030[Abstract] As the size of Big Data workloads keeps increasing, the evaluation of distributed frameworks becomes a crucial task in order to identify potential performance bottlenecks that may delay the processing of large datasets. While most of the existing works generally focus only on execution time and resource utilization, analyzing other important metrics is key to fully understanding the behavior of these frameworks. For example, microarchitecture-level events can bring meaningful insights to characterize the interaction between frameworks and hardware. Moreover, energy consumption is also gaining increasing attention as systems scale to thousands of cores. This work discusses the current state of the art in evaluating distributed processing frameworks, while extending our Big Data Evaluator tool (BDEv) to extract energy efficiency and microarchitecture-level metrics from the execution of representative Big Data workloads. An experimental evaluation using BDEv demonstrates its usefulness to bring meaningful information from popular frameworks such as Hadoop, Spark and Flink.Ministerio de Economía, Industria y Competitividad; TIN2016-75845-PMinisterio de Educación; FPU14/02805Ministerio de Educación; FPU15/0338

Hector: Detecting resource-release omission faults in error-handling code for systems software

International audienceOmitting resource-release operations in systems error handling code can lead to memory leaks, crashes, and deadlocks. Finding omission faults is challenging due to the difficulty of reproducing system errors, the diversity of system resources, and the lack of appropriate abstractions in the C language. To address these issues, numerous approaches have been proposed that globally scan a code base for common resource-release operations. Such macroscopic approaches are notorious for their many false positives, while also leaving many faults undetected. We propose a novel microscopic approach to finding resource-release omission faults in systems software. Rather than generalizing from the entire source code, our approach focuses on the error-handling code of each function. Using our tool, Hector, we have found over 370 faults in six systems software projects, including Linux, with a 23% false positive rate. Some of these faults allow an unprivileged malicious user to crash the entire system