SEUSS: rapid serverless deployment using environment snapshots

Modern FaaS systems perform well in the case of repeat executions when function working sets stay small. However, these platforms are less effective when applied to more complex, large-scale and dynamic workloads. In this paper, we introduce SEUSS (serverless execution via unikernel snapshot stacks), a new system-level approach for rapidly deploying serverless functions. Through our approach, we demonstrate orders of magnitude improvements in function start times and cacheability, which improves common re-execution paths while also unlocking previously-unsupported large-scale bursty workloads.Published versio

Cloud Computing Service Selection Algorithm

In modern world Cloud Computing is one of the most promising and evolving areas of computer science. As time passes by more and more cloud devices are being setup. Similarly more companies and industries are opting for cloud services, etc. Cloud has made up a virtual reality of the practical world. It oers online storage space, online infrastructure, online platforms, etc to make our everyday computing experience easier and cheaper. One of the aspects of cloud computing is provision of servers to execute our programs which comes under Infrastructure as a Service (IaaS). In this project we have focused on devising an algorithm to schedule jobs and allocate servers in cloud systems. The algorithm is ecient as it provides optimal allocation. It maximizes the number of job requests that can be processed in unit time while conserving energy and keeping the costs low. The said optimal allocation is achieved by reducing the idle time of nodes of active servers and reducing the total number of servers used. We implemented our algorithm using random data sets of job requests with dierent attributes and generated simulations in forms of graphs. The graphs prove the eciency of job scheduling algorithm and the server allocation for which we used Best Fit algorithm of the Bin Packing problem. Finally a detailed analysis is given and future works are stated

The benefits of virtualization across the software development pipeline

Abstract. The emergence of cloud computing and the evolution into service-based solutions across the software industry have influenced many changes in software development paradigms and methods. As a result, various forms of virtualization and container-based solutions have become more and more commonplace throughout the field, with technologies and frameworks such as Docker and Kubernetes becoming industry standard solutions to virtualization. This thesis is a literature review into existing research on virtualization and containers, and their use in various categories of the software industry. The aim of the thesis is to look at the reasons for the proliferation of virtual machines and containers, along with their benefits for the software development process, the continuous integration and delivery pipeline, and the different cloud platforms and providers. The benefits of virtualization are clearest in the cloud infrastructure, as cloud services are inherently built to utilize virtual machines. Containers and container orchestration systems allow container management and dynamic resource allocation, improving efficiency and reducing costs. In software development and testing, the modular and self-contained nature of containers allows for faster iteration and more problem-averse development. And finally, in the continuous integration and delivery pipelines, containers and container management tools allows automation, and lower overhead and complexity, enabling lower-threshold software deployment. Along with enabling cloud infrastructure as it exists today, the evolution of virtualization and containers in the software industry provide benefits across the board

Mobile, collaborative augmented reality using cloudlets

The evolution in mobile applications to support advanced interactivity and demanding multimedia features is still ongoing. Novel application concepts (e.g. mobile Augmented Reality (AR)) are however hindered by the inherently limited resources available on mobile platforms (not withstanding the dramatic performance increases of mobile hardware). Offloading resource intensive application components to the cloud, also known as "cyber foraging", has proven to be a valuable solution in a variety of scenarios. However, also for collaborative scenarios, in which data together with its processing are shared between multiple users, this offloading concept is highly promising. In this paper, we investigate the challenges posed by offloading collaborative mobile applications. We present a middleware platform capable of autonomously deploying software components to minimize average CPU load, while guaranteeing smooth collaboration. As a use case, we present and evaluate a collaborative AR application, offering interaction between users, the physical environment as well as with the virtual objects superimposed on this physical environment