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

Evaluator services for optimised service placement in distributed heterogeneous cloud infrastructures

Optimal placement of demanding real-time interactive applications in a distributed heterogeneous cloud very quickly results in a complex tradeoff between the application constraints and resource capabilities. This requires very detailed information of the various requirements and capabilities of the applications and available resources. In this paper, we present a mathematical model for the service optimization problem and study the concept of evaluator services as a flexible and efficient solution for this complex problem. An evaluator service is a service probe that is deployed in particular runtime environments to assess the feasibility and cost-effectiveness of deploying a specific application in such environment. We discuss how this concept can be incorporated in a general framework such as the FUSION architecture and discuss the key benefits and tradeoffs for doing evaluator-based optimal service placement in widely distributed heterogeneous cloud environments

Performance Evaluation Metrics for Cloud, Fog and Edge Computing: A Review, Taxonomy, Benchmarks and Standards for Future Research

Optimization is an inseparable part of Cloud computing, particularly with the emergence of Fog and Edge paradigms. Not only these emerging paradigms demand reevaluating cloud-native optimizations and exploring Fog and Edge-based solutions, but also the objectives require significant shift from considering only latency to energy, security, reliability and cost. Hence, it is apparent that optimization objectives have become diverse and lately Internet of Things (IoT)-specific born objectives must come into play. This is critical as incorrect selection of metrics can mislead the developer about the real performance. For instance, a latency-aware auto-scaler must be evaluated through latency-related metrics as response time or tail latency; otherwise the resource manager is not carefully evaluated even if it can reduce the cost. Given such challenges, researchers and developers are struggling to explore and utilize the right metrics to evaluate the performance of optimization techniques such as task scheduling, resource provisioning, resource allocation, resource scheduling and resource execution. This is challenging due to (1) novel and multi-layered computing paradigm, e.g., Cloud, Fog and Edge, (2) IoT applications with different requirements, e.g., latency or privacy, and (3) not having a benchmark and standard for the evaluation metrics. In this paper, by exploring the literature, (1) we present a taxonomy of the various real-world metrics to evaluate the performance of cloud, fog, and edge computing; (2) we survey the literature to recognize common metrics and their applications; and (3) outline open issues for future research. This comprehensive benchmark study can significantly assist developers and researchers to evaluate performance under realistic metrics and standards to ensure their objectives will be achieved in the production environments

Current and Future Issues in BPM Research: A European Perspective from the ERCIS Meeting 2010

Business process management (BPM) is a still-emerging field in the academic discipline of Information Systems (IS). This article reflects on a workshop on current and future issues in BPM research that was conducted by seventeen IS researchers from eight European countries as part of the 2010 annual meeting of the European Research Center for Information Systems (ERCIS). The results of this workshop suggest that BPM research can meaningfully contribute to investigating a broad variety of phenomena that are of interest to IS scholars, ranging from rather technical (e.g., the implementation of software architectures) to managerial (e.g., the impact of organizational culture on process performance). It further becomes noticeable that BPM researchers can make use of several research strategies, including qualitative, quantitative, and design-oriented approaches. The article offers the participants’ outlook on the future of BPM research and combines their opinions with research results from the academic literature on BPM, with the goal of contributing to establishing BPM as a distinct field of research in the IS discipline

Towards Measuring and Understanding Performance in Infrastructure- and Function-as-a-Service Clouds

Context. Cloud computing has become the de facto standard for deploying modern software systems, which makes its performance crucial to the efficient functioning of many applications. However, the unabated growth of established cloud services, such as Infrastructure-as-a-Service (IaaS), and the emergence of new services, such as Function-as-a-Service (FaaS), has led to an unprecedented diversity of cloud services with different performance characteristics.Objective. The goal of this licentiate thesis is to measure and understand performance in IaaS and FaaS clouds. My PhD thesis will extend and leverage this understanding to propose solutions for building performance-optimized FaaS cloud applications.Method.\ua0To achieve this goal, quantitative and qualitative research methods are used, including experimental research, artifact analysis, and literature review.Findings.\ua0The thesis proposes a cloud benchmarking methodology to estimate application performance in IaaS clouds, characterizes typical FaaS applications, identifies gaps in literature on FaaS performance evaluations, and examines the reproducibility of reported FaaS performance experiments. The evaluation of the benchmarking methodology yielded promising results for benchmark-based application performance estimation under selected conditions. Characterizing 89 FaaS applications revealed that they are most commonly used for short-running tasks with low data volume and bursty workloads. The review of 112 FaaS performance studies from academic and industrial sources found a strong focus on a single cloud platform using artificial micro-benchmarks and discovered that the majority of studies do not follow reproducibility principles on cloud experimentation.Future Work. Future work will propose a suite of application performance benchmarks for FaaS, which is instrumental for evaluating candidate solutions towards building performance-optimized FaaS applications

QoS Analysis in Heterogeneous Choreography Interactions

International audienceWith an increasing number of services and devices interacting in a decentralized manner, choreographies are an active area of investigation. The heterogeneous nature of interacting systems leads to choreographies that may not only include conventional services, but also sensor-actuator networks, databases and service feeds. Their middleware behavior within choreographies is captured through abstract interaction paradigms such as client-service, publish-subscribe and tuple space. In this paper, we study these heterogeneous interaction paradigms, connected through an eXtensible Service Bus proposed in the CHOReOS project. As the functioning of such choreographies is dependent on the Quality of Service (QoS) performance of participating entities, an intricate analysis of interaction paradigms and their effect on QoS metrics is needed. We study the composition of QoS metrics in heterogeneous choreographies, and the subsequent tradeoffs. This produces interesting insights such as selection of a particular system and its middleware during design time or end-to-end QoS expectation/guarantees during runtime. Non-parametric hypothesis tests are applied to systems, where QoS dependent services may be replaced at runtime to prevent deterioration in performance

Privacy-preserved security-conscious framework to enhance web service composition

The emergence of loosely coupled and platform-independent Service-Oriented Computing (SOC) has encouraged the development of large computing infrastructures like the Internet, thus enabling organizations to share information and offer valueadded services tailored to a wide range of user needs. Web Service Composition (WSC) has a pivotal role in realizing the vision of implementing just about any complex business processes. Although service composition assures cost-effective means of integrating applications over the Internet, it remains a significant challenge from various perspectives. Security and privacy are among the barriers preventing a more extensive application of WSC. First, users possess limited prior knowledge of security concepts. Second, WSC is hindered by having to identify the security required to protect critical user information. Therefore, the security available to users is usually not in accordance with their requirements. Moreover, the correlation between user input and orchestration architecture model is neglected in WSC with respect to selecting a high performance composition execution process. The proposed framework provides not only the opportunity to securely select services for use in the composition process but also handles service users’ privacy requirements. All possible user input states are modelled with respect to the extracted user privacy preferences and security requirements. The proposed approach supports the mathematical modelling of centralized and decentralized orchestration regarding service provider privacy and security policies. The output is then utilized to compare and screen the candidate composition routes and to select the most secure composition route based on user requests. The D-optimal design is employed to select the best subset of all possible experiments and optimize the security conscious of privacy-preserving service composition. A Choreography Index Table (CIT) is constructed for selecting a suitable orchestration model for each user input and to recommend the selected model to the choreographed level. Results are promising that indicate the proposed framework can enhance the choreographed level of the Web service composition process in making adequate decisions to respond to user requests in terms of higher security and privacy. Moreover, the results reflect a significant value compared to conventional WSC, and WSC optimality was increased by an average of 50% using the proposed CIT

Novel Resource and Energy Management for 5G Integrated Backhaul/Fronthaul (5G-Crosshaul)

The integration of both fronthaul and backhaul into a single transport network (namely, 5G-Crosshaul) is envisioned for the future 5G transport networks. This requires a fully integrated and unified management of the fronthaul and backhaul resources in a cost-efficient, scalable and flexible way through the deployment of an SDN/NFV control framework. This paper presents the designed 5G-Crosshaul architecture, two selected SDN/NFV applications targeting for cost-efficient resource and energy usage: the Resource Management Application (RMA) and the Energy Management and Monitoring Application (EMMA). The former manages 5G-Crosshaul resources (network, computing and storage resources). The latter is a special version of RMA with the focus on the objectives of optimizing the energy consumption and minimizing the energy footprint of the 5G-Crosshaul infrastructure. Besides, EMMA is applied to the mmWave mesh network and the high speed train scenarios. In particular, we present the key application design with their main components and the interactions with each other and with the control plane, and then we present the proposed application optimization algorithms along with initial results. The first results demonstrate that the proposed RMA is able to cost-efficiently utilize the Crosshaul resources of heterogeneous technologies, while EMMA can achieve significant energy savings through energy-efficient routing of traffic flows. For experiments in real system, we also set up Proof of Concepts (PoCs) for both applications in order to perform real trials in the field.© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works