Self-aware software architecture style and patterns for cloud-based applications

Modern cloud-reliant software systems are faced with the problem of cloud service providers violating their Service Level Agreement (SLA) claims. Given the large pool of cloud providers and their instability, cloud applications are expected to cope with these dynamics autonomously. This thesis investigates an approach for designing self-adaptive cloud architectures using a systematic methodology that guides the architect while designing cloud applications. The approach termed $Self-aware$ $Architecture$ $Pattern$ promotes fine-grained representation of architectural concerns to aid design-time analysis of risks and trade-offs. To support the coordination and control of architectural components in decentralised self-aware cloud applications, we propose a $Reputation-aware$ $posted$ $offer$ $market$ $coordination$ $mechanism$. The mechanism builds on the classic posted offer market mechanism and extends it to track behaviour of unreliable cloud services. The self-aware cloud architecture and its reputation-aware coordination mechanism are quantitatively evaluated within the context of an Online Shopping application using synthetic and realistic workload datasets under various configurations (failure, scale, resilience levels etc.). Additionally, we qualitatively evaluated our self-aware approach against two classic self-adaptive architecture styles using independent experts' judgment, to unveil its strengths and weaknesses relative to these styles

Architecting self-aware software systems

Contemporary software systems are becoming increasingly large, heterogeneous, and decentralised. They operate in dynamic environments and their architectures exhibit complex trade-offs across dimensions of goals, time, and interaction, which emerges internally from the systems and externally from their environment. This gives rise to the vision of self-aware architecture, where design decisions and execution strategies for these concerns are dynamically analysed and seamlessly managed at run-time. Drawing on the concept of self-awareness from psychology, this paper extends the foundation of software architecture styles for self-adaptive systems to arrive at a new principled approach for architecting self-aware systems. We demonstrate the added value and applicability of the approach in the context of service provisioning to cloud-reliant service-based applications

A Dynamic Data-Driven Simulation Approach for Preventing Service Level Agreement Violations in Cloud Federation

The new possibility of accessing an infinite pool of computational resources at a drastically reduced price has made cloud computing popular. With the increase in its adoption and unpredictability of workload, cloud providers are faced with the problem of meeting their service level agreement (SLA) claims as demonstrated by large vendors such as Amazon and Google. Therefore, users of cloud resources are embracing the more promising cloud federation model to ensure service guarantees. Here, users have the option of selecting between multiple cloud providers and subsequently switching to a more reliable one in the event of a provider’s inability to meet its SLA. In this paper, we propose a novel dynamic data-driven architecture capable of realising resource provision in a cloud federation with minimal SLA violations. We exemplify the approach with the aid of case studies to demonstrate its feasibility. Keywords

The handbook of engineering self-aware and self-expressive systems

When faced with the task of designing and implementing a new self-aware and self-expressive computing system, researchers and practitioners need a set of guidelines on how to use the concepts and foundations developed in the Engineering Proprioception in Computing Systems (EPiCS) project. This report provides such guidelines on how to design self-aware and self-expressive computing systems in a principled way. We have documented different categories of self-awareness and self-expression level using architectural patterns. We have also documented common architectural primitives, their possible candidate techniques and attributes for architecting self-aware and self-expressive systems. Drawing on the knowledge obtained from the previous investigations, we proposed a pattern driven methodology for engineering self-aware and self-expressive systems to assist in utilising the patterns and primitives during design. The methodology contains detailed guidance to make decisions with respect to the possible design alternatives, providing a systematic way to build self-aware and self-expressive systems. Then, we qualitatively and quantitatively evaluated the methodology using two case studies. The results reveal that our pattern driven methodology covers the main aspects of engineering self-aware and self-expressive systems, and that the resulted systems perform significantly better than the non-self-aware systems