Performance Evaluation of Microservices Architectures using Containers

Microservices architecture has started a new trend for application development for a number of reasons: (1) to reduce complexity by using tiny services; (2) to scale, remove and deploy parts of the system easily; (3) to improve flexibility to use different frameworks and tools; (4) to increase the overall scalability; and (5) to improve the resilience of the system. Containers have empowered the usage of microservices architectures by being lightweight, providing fast start-up times, and having a low overhead. Containers can be used to develop applications based on monolithic architectures where the whole system runs inside a single container or inside a microservices architecture where one or few processes run inside the containers. Two models can be used to implement a microservices architecture using containers: master-slave, or nested-container. The goal of this work is to compare the performance of CPU and network running benchmarks in the two aforementioned models of microservices architecture hence provide a benchmark analysis guidance for system designers.Comment: Submitted to the 14th IEEE International Symposium on Network Computing and Applications (IEEE NCA15). Partially funded by European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 639595) - HiEST Projec

On the Fly Orchestration of Unikernels: Tuning and Performance Evaluation of Virtual Infrastructure Managers

Network operators are facing significant challenges meeting the demand for more bandwidth, agile infrastructures, innovative services, while keeping costs low. Network Functions Virtualization (NFV) and Cloud Computing are emerging as key trends of 5G network architectures, providing flexibility, fast instantiation times, support of Commercial Off The Shelf hardware and significant cost savings. NFV leverages Cloud Computing principles to move the data-plane network functions from expensive, closed and proprietary hardware to the so-called Virtual Network Functions (VNFs). In this paper we deal with the management of virtual computing resources (Unikernels) for the execution of VNFs. This functionality is performed by the Virtual Infrastructure Manager (VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We discuss the instantiation process of virtual resources and propose a generic reference model, starting from the analysis of three open source VIMs, namely OpenStack, Nomad and OpenVIM. We improve the aforementioned VIMs introducing the support for special-purpose Unikernels and aiming at reducing the duration of the instantiation process. We evaluate some performance aspects of the VIMs, considering both stock and tuned versions. The VIM extensions and performance evaluation tools are available under a liberal open source licence

Using Virtual Reality to increase technical performance during rowing workouts

Technology is advancing rapidly in virtual reality (VR) and sensors, gathering feedback from our body and the environment we are interacting in. Combining the two technologies gives us the opportunity to create personalized and reactive immersive environments. These environments can be used e.g. for training in dangerous situations (e.g. fire, crashes, etc), or to improve skills with less distraction than regular natural environments would have. The pilot study described in this thesis puts an athlete who is rowing on a stationary rowing machine into a virtual environment. The VR takes movement from several sensors of the ergo-meter and displays those in VR. In addition, metrics on technique are being derived from the sensor data and physiological data. All this is used to investigate if, and to which extent, VR may improve the technical skills of the athlete during the complex sport of rowing. Furthermore, athletes are giving subjective feedback about their experience comparing a standard rowing workout, with the workout using VR. First results indicate better performance and an enhanced experience by the athlete

Building distributed heterogeneous smart phone Java applications an evaluation from a development perspective

The advances in mobile phone technology have enabled such devices to be programmed to run general-purpose applications using a special edition of the Java programming language. Java is designed to be a heterogeneous programming language targeting different platforms. Such ability when coupled with the provision of high-speed mobile Internet access would open the door for a new breed of distributed mobile applications. This paper explores the capabilities and limitations of this technology and addresses the considerations that must be taken when designing and developing such distributed applications. Our findings are verified by building a test client-server system where the clients in this system are mobile phones behaving as active processing elements not just mere service requesters

Online Algorithms for Geographical Load Balancing

It has recently been proposed that Internet energy costs, both monetary and environmental, can be reduced by exploiting temporal variations and shifting processing to data centers located in regions where energy currently has low cost. Lightly loaded data centers can then turn off surplus servers. This paper studies online algorithms for determining the number of servers to leave on in each data center, and then uses these algorithms to study the environmental potential of geographical load balancing (GLB). A commonly suggested algorithm for this setting is “receding horizon control” (RHC), which computes the provisioning for the current time by optimizing over a window of predicted future loads. We show that RHC performs well in a homogeneous setting, in which all servers can serve all jobs equally well; however, we also prove that differences in propagation delays, servers, and electricity prices can cause RHC perform badly, So, we introduce variants of RHC that are guaranteed to perform as well in the face of such heterogeneity. These algorithms are then used to study the feasibility of powering a continent-wide set of data centers mostly by renewable sources, and to understand what portfolio of renewable energy is most effective