Stella Gatziu Grivas

Cloud Broker: Bringing Intelligence into the Cloud

Handling changes of business processes, and making sure systems are up and running after a change in the business process with minimum downtime is something which has been of interest to researchers for long and there have been several approaches proposed for it. With Cloud computing becoming increasingly popular businesses require a strong system for cloud based implementations which can handle change management of processes. In this paper we propose a change management approach for cloud backed business process models.

Enterprise Architecture Frameworks for Enabling Cloud Computing

Cloud computing has emerged as a strong factor driving companies to remarkable business success. Far from just being an IT level support solution cloud computing is triggering changes in their core business models by making them more efficient and cost-effective. This has generated an interest for a lot of companies to try and adopt cloud computing for their existing and new business process. In this research we present an approach which a company can use to analyze if its operations can be positively impacted by moving to the cloud. Further we describe our approach using which the company can make that transition to the cloud.

Asynchronous messaging for OSGi

OSGi is a popular Java-based platform, which has its roots in the area of embedded systems. However, nowadays it is used more and more in enterprise systems. To fit this new application area, OSGi has recently been extended with the Remote Services specification. This specification enables distribution, which OSGi was previously lacking. However, the specification provides means for synchronous communication only and leaves out asynchronous communication. As an attempt to fill a gap in this field, we propose, implement and evaluate an approach for the integration of asynchronous messaging into OSGi.

Cloud-Based Event-Processing Architecture for Opinion Mining

The viability of cloud computing for information-intensive tasks arising in real-time opinion mining and sentiment analysis of large online text streams is described. We show how a smart distributed architecture enables an efficient and scalable design for opinion mining on internet-based content that answers key challenges, such as integrating heterogeneous data sources and adapting to events through dynamic system configuration. In particular, we present a novel approach of semantic complex event processing in a cloud environment capturing different levels of information, such as event data (e.g. content from various heterogeneous, distributed sources) as well as associations identified during the opinion mining and sentiment analysis process (e.g. dynamic co-reference resolution).

Context-aware website personalization

Today there is a need in on-line shops to support the visitors of a web page appropriately by analyzing their current situation. In this paper we introduce a model which supports the identification of the content the user is interested in and the shopping strategy of the current session. We use context information extracted from enterprise data, content data, the current and the historical behaviour of the user. This allows us to learn more about the interests and needs of the user. We monitor and analyze this content information at runtime and use it for the adaption of the web site during the users navigation.

Security of a Public Cloud

This paper is about the current state of security in cloud computing. It shows some of the key benefits and the major drawbacks that come around with swapping out services and infrastructure to a public cloud. Based on these benefits and drawbacks, K.O. (knock-out) criteria will be identified, which can be seen as the minimum basis for secure cloud environment. Then a final conclusion about security in cloud computing will be given.

Cloud Computing Business Case Framework: Introducing a Mixed-Model Business Case Framework for Small and Medium Enterprises to Determine the Value of Cloud Computing

Cloud Computing is still at the top of the agenda of almost every company. The market for cloud services grew consistently over the last year and is expected to continue to rise over the next few years. To justify the investment, companies need to carefully evaluate the costs, benefits and risks of cloud services and create a compelling business case. The formation of a strong case for an investment decision about cloud services presents two primary challenges for small and medium enterprises. Companies often cannot compare the true costs of different services since they do not know the current costs of their IT-systems and do not include all the cost factors of cloud services within their calculations. Secondly, it is difficult to include all the intangible benefits and risks of cloud services within the business case, as they are not possible to quantify or hardly quantifiable. A framework for the cloud business case based on the current state of the art literature can help to overcome those challenges by creating awareness for all relevant factors and defining a suitable business case method.

Towards a Timely Root Cause Analysis for Complex Situations in Large Scale Telecommunications Networks

Abstract Large scale telecommunications networks need to be continuously monitored to detect problems and react accordingly to ensure the networks stability. Current monitoring systems are well capable to monitor such large scale installations for simple situations like failing routers, links or abnormal link utilization. However, current systems fail to provide near real-time in-depth root cause analysis for nation scale networks. This is particularly important in cases where the monitoring dashboard is flooded with notifications caused by side-effects of one bigger failure. In our project we develop a processing system capable of providing this root cause analysis in a timely fashion even for large telecommunications networks. To cope with these challenges we defined a specialized processing model for the detection and analysis of complex error situations which is largely based on event stream processing mechanisms. In this paper we discuss the first stage of this process and its initial implementation.

FHNW Maturity Models for Cloud and Enterprise IT

Existing cloud maturity models define the level of maturity according to the number of cloud solutions implemented or the duration of deployment. However, this does not include the motivation regarding why cloud solutions are used in an enterprise. Likewise, there has been no investigated into what changes the deployment of cloud services entails, how enterprise IT positions itself and whether the enterprise is able to bring about the necessary changes to support them. The combination of the FHNW Cloud and Enterprise IT Maturity Models provides information regarding why and how the cloud is used and how the enterprise IT is set up. As a result, the two maturity models support enterprises that already use the cloud on the way to making them even more efficient, to having their business IT aligned, and to contributing significantly to the successful digital transformation.

How Cloud Will Transform the Retail Banking Industry

This paper focusses on current trends in the banking industry and on illustrating how these trends can be supported by cloud computing. The main characteristics of cloud computing that could support transformation are facilitated data accessibility, enabled processing of data from various sources and the opportunity of an easier integration of functions or data. Trends in the banking industry are increasing customer centricity, redesigning of branches and deployment of new communication and distribution channels. For each trend we report quotes general information to provide an overview of the transformation caused by this trend. We identify which business processes are influenced, how they are affected and we explain how cloud computing could support the identified changes.