Symbiotic and sensitivity-aware architecture for globally-optimal benefit in self-adaptive cloud

Due to the uncertain and dynamic demand for Quality of Service (QoS) in cloud-based systems, engineering self-adaptivity in cloud architectures require novel approaches to support on-demand elasticity. The architecture should dynamically select an elastic strategy, which optimizes the global benefit for QoS and cost objectives for all cloud-based services. The architecture shall also provide mechanisms for reaching the strategy with minimal overhead. However, the challenge in the cloud is that the nature of objectives (e.g., throughput and the required cost) and QoS interference could cause overlapping sensitivity amongst intra-and inter-services objectives, which leads to objective-dependency (i.e., conflicted or harmonic) during optimization. In this paper, we propose a symbiotic and sensitivity-aware architecture for optimizing global-benefit with reduced overhead in the cloud. The architecture dynamically partitions QoS and cost objectives into sensitivity independent regions, where the local optimums are achieved. In addition, the architecture realizes the concept of symbiotic feedback loop, which is a bio-directional self-adaptive action that not only allows to dynamically monitor and adapt the managed services by scaling to their demand, but also to adaptively consolidate the managing system by re-partitioning the regions based on symptoms. We implement the architecture as a prototype extending on decentralized MAPE loop by introducing an Adaptor component. We then experimentally analyze and evaluate our architecture using hypothetical scenarios. The results reveal that our symbiotic and sensitivity-aware architecture is able to produce even better global benefit and smaller overhead in contrast to other non sensitivity-aware architectures

Taxonomy of Cloud Lock-in Challenges

This chapter reviews key concepts and terminologies needed for understanding the complexity of the vendor lock-in problem being investigated in this book. Firstly, we present aspects of cloud computing that contribute to vendor lock-in and briefly introduce existing results from cloud-related areas of computer science that contributes to understanding and tackling vendor lock-in. Secondly, we explore the literature on proprietary lock-in risks in cloud computing environments to identify its causes (i.e., restrictions), consequences, mitigations strategies, and related challenges faced by enterprise consumers migrating to cloud-based services. Then, we propose taxonomy of cloud lock-in perspectives based on reports of real experiences on migration to understand the overall cloud SaaS migration challenges. Finally, we narrow down to our perspective on cloud lock-in to three main perspectives which takes the use of sound techniques from IS research discipline and cloud-related literature into consideration, to improve the portability, security and interoperability of cloud (and on-premise) applications in hybrid environments. Collectively, the discussions presented herein, accordingly enables both academia and IT practitioners in the cloud computing community to get an overarching view of the process of combating application and data lock-in challenges, and security risks in the cloud

Investigational Analysis of Security Measures Effectiveness in Cloud Computing: A Study

In the modern era of business operation, the technical adoption of cloud services are high on rise by the large scale to small scale business establishment on various products and services. Needless to say that with the rise of adoption also gives birth to security concerns as cloud runs on common internet which are also used by trillions of internet-users. There are various means by which introducing a malicious program inside the cloud is not that complicated task for attacker. The various services providers as well as past researcher have introduced some of the potential security features which is claimed to be highly effective. However, accomplishing fail-proof security systems in cloud is never witnessed nor reported by any user or researcher, which clearly specifies that security problems do persist and are on exponential rise. Therefore, this paper discusses about the security issues in cloud supported by brief description of standard security models currently available in cloud. With extensive literatures on the existing security solutions, a significant research gap is explored in robust authentication system in cloud services. Keywords-component; Security, Cloud Computing,attacks, security model

Monitoring Cloud Services through Models at Runtime: A Case in an Ambient Assisted Living Environment

[EN] Ambient Assisted Living (AAL) has become an important domain that provides software systems and services to support and improve people¿s daily quality of life. Yet, it has not achieved large market penetration. Existing works suggest that this is primarily due to not sufficiently addressing the quality requirements posed by healthcare organizations. In particular, there is a lack of comprehensive frameworks that allow the assessment of the quality of AAL systems. In previous work, we introduced a method for monitoring cloud services using models at runtime (MoS@RT), which allows the monitoring requirements or the metric operationalizations of these requirements to be changed at runtime without the modification of the underlying infrastructure. The method and its supporting infrastructure have been successfully applied in the monitoring of cloud services, but further evaluation in other domains is needed. In this paper, we report a case study on the use of MoS@RT to monitor cloud services in an AAL environment aimed at supporting the elderly¿s well-being. The results suggest that relevant quality attributes of AAL systems can be adequately monitored using MoS@RT and that the report generated by the monitoring infrastructure is useful for service providers and customers to help them ensure that cloud services meet the required levels of quality.We thank to Fundación Carolina, Universidad de Cuenca, and Universitat Politècnica de València for their support. This research is supported by the project Fog Computing applied to monitoring devices used in AAL environments: platform for the elderly (Research Projects DIUC XVII).Cedillo, P.; Insfran, E.; Abrahao Gonzales, SM. (2022). Monitoring Cloud Services through Models at Runtime: A Case in an Ambient Assisted Living Environment. Journal of Object Technology. 21(4):1-19. https://doi.org/10.5381/jot.2022.21.4.a111921