Olga Wenge

Towards Heuristic Optimization of Complex Service-Based Workflows for Stochastic QoS Attributes

The problem of selecting services from a set of functionally appropriate ones under Quality of Service constraints - the Service Selection Problem - is well-recognized in the literature based on deterministic parameters. However, Quality of Service may rather follow a stochastic distribution and, thus, may change at runtime. In order to cope with differing Quality of Service, we present a heuristic approach for efficiently addressing the Service Selection Problem in conjunction with stochastic Quality of Service attributes. Accounting for penalty cost which accrue due to Quality of Service violations, our approach reduces the impact of stochastic Quality of Service behavior on total cost significantly.

Security Information and Event Monitoring as a Service: a Survey on Current Concerns and Solutions

Today’s cloud environments are very heterogeneous. Current security approaches of intrusion detection, prevention, and response in physical environments are sophisticated. However, the growth of virtualization and multi-tenant technologies is creating new targets for intrusion and raises many questions about the implementation of the same protection in cloud environments. As an answer to the clouds’ heterogeneity, the heterogeneity of cloud security solutions is presented, which causes market confusion and bringsmore complexity in the selection process of sound security solutions. As not every enterprise has in-house tools, competences and expertise to secure cloud environments on its own, Security as a Service (SecaaS) solutions are becoming more popular, promising cost-savings and proper real-time threats detection and prevention. In our paper, we outline the current research areas in SecaaS, especially Security Information and Event Management (SIEM). Furthermore, we discuss requirements and concerns related to implementation of SIEM as a service and identify challenges for further research.

Heuristic Approaches for Robust Cloud Monitor Placement

When utilizing cloud-based services, consumers obtain high configurable resources with minimal management effort and eliminate large up-front IT investments. However, this shift in responsibility to the cloud provider is accompanied by a loss of control for the cloud consumer. By offering SLAs and corresponding monitoring solutions, cloud providers already try to address this issue, but these solutions are not considered as sufficient from a consumer’s perspective. Therefore, we developed an approach that allows to verify compliance with SLAs from a consumer’s perspective in our former work. Since the monitoring infrastructure itself may fail, this approach was enhanced in one of our subsequent works in order to account for reliability. We introduced the Robust Cloud Monitor Placement Problem and a formal optimization model. In this paper, we propose corresponding solution approaches and evaluate their practical applicability, since the problem is NP-complete.

Composition of Cloud Collaborations under Consideration of Non-functional Attributes

Cloud markets promise virtually unlimited resource supplies. Some providers set up distributed data centers at different geographical locations and jurisdictions and may not always be able to offer effectual physical capacity to serve large customers in one location. A solution is cloud collaborations, where multiple providers unite to conjointly offer capacities. Both Quality of Service and security properties of such collaborations will be determined by the “weakest link in the chain”, therefore resulting in a trade-off between monetary aggregates, cumulative capacity and non-functional attributes of a collaboration. Based on our previous research, we examine in our paper efficient composition of cloud collaborations from the broker’s perspective, considering Quality of Service and security requirements of cloud providers and users. We propose a Mixed Integer Programming-based heuristic approach CCCP-HEU.COM with deterministic and stochastic variants and provide its quantitative evaluation in comparison with our prior optimal approach.

Towards Establishing Security-Aware Cloud Markets

Todays cloud environments are very heterogeneous. This cloud heterogeneity, as the consequence of lacking cloud standards, builds technical and security barriers between cloud providers and blocks them from intended cloud collaborations within cloud marketplaces. A cloud broker, who acts on behalf of cloud providers, matches compatible collaborative partners according to their requirements and attempts to support the optimal exchange of cloud resources between them. The fulfillment of security requirements in cloud collaborations usually involves providing risk assessments, which are still very time-consuming and not applicable for ad hoc cloud collaborations within cloud marketplaces. Aiming to design and develop a security model for trading with cloud services, we identify in this paper concepts, mechanism and available tools that can support establishing of security-aware cloud markets. Furthermore, we introduce our information security governance driven cloud brokerage model with security labeling of tradable cloud products that can be the next step in the standardization process of tradable cloud products and optimize the selection of collaborative cloud partners.