COSCO: container orchestration using co-simulation and gradient based optimization for fog computing environments

Intelligent task placement and management of tasks in large-scale fog platforms is challenging due to the highly volatile nature of modern workload applications and sensitive user requirements of low energy consumption and response time. Container orchestration platforms have emerged to alleviate this problem with prior art either using heuristics to quickly reach scheduling decisions or AI driven methods like reinforcement learning and evolutionary approaches to adapt to dynamic scenarios. The former often fail to quickly adapt in highly dynamic environments, whereas the latter have run-times that are slow enough to negatively impact response time. Therefore, there is a need for scheduling policies that are both reactive to work efficiently in volatile environments and have low scheduling overheads. To achieve this, we propose a Gradient Based Optimization Strategy using Back-propagation of gradients with respect to Input (GOBI). Further, we leverage the accuracy of predictive digital-twin models and simulation capabilities by developing a Coupled Simulation and Container Orchestration Framework (COSCO). Using this, we create a hybrid simulation driven decision approach, GOBI*, to optimize Quality of Service (QoS) parameters. Co-simulation and the back-propagation approaches allow these methods to adapt quickly in volatile environments. Experiments conducted using real-world data on fog applications using the GOBI and GOBI* methods, show a significant improvement in terms of energy consumption, response time, Service Level Objective and scheduling time by up to 15, 40, 4, and 82 percent respectively when compared to the state-of-the-art algorithms

A Strategy for Advancing Research and Impact in New Computing Paradigms

In the world of Information Technology, new computing paradigms, driven by requirements of different classes of problems and applications, emerge rapidly. These new computing paradigms pose many new research challenges. Researchers from different disciplines are working together to develop innovative solutions addressing them. In newer research areas with many unknowns, creating roadmaps, enabling tools, inspiring technological and application demonstrators offer confidence and prove feasibility and effectiveness of new paradigm. Drawing on our experience, we share strategy for advancing the field and community building in new and emerging computing research areas. We discuss how the development simulators can be cost-effective in accelerating design of real systems. We highlight strategic role played by different types of publications, conferences, and educational programs. We illustrate effectiveness of elements of our strategy with a case study on progression of cloud computing paradigm.Comment: 8 pages, 1 figur

Addressing the Faults Landscape in the Internet of Things: Toward Datacentric and System Resilience

\ua9 1997-2012 IEEE.In the Internet of Things (IoT) context, the landscape of weaknesses in the IoT spectrum sheds light on addressing faults by researchers due to the number of IoT components that unveil immense vulnerabilities to failures. Hence, there is a need to comprehend the faults dynamics to facilitate identifying potential hazards in a developer\u27s design, deliver methodologies to mitigate the risks, and ensure the data quality and resiliency of the IoT\u27s deployment. This article comprehensively aims to analyze faults occurrences in the IoT, their impacts on functionality, and their repercussions on data. It highlights the intricate patterns of data faults by addressing various aspects, such as duration, cause, pitfalls, component, type, and source

A manifesto for future generation cloud computing: Research directions for the next decade

© 2018 Association for Computing Machinery. The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high-performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to address issues such as scalability, elasticity, reliability, security, sustainability, and application models. The proposed manifesto addresses them by identifying the major open challenges in Cloud computing, emerging trends, and impact areas. It then offers research directions for the next decade, thus helping in the realisation of Future Generation Cloud Computing