25,510 research outputs found
Adaptive application deployment of priority services in virtual environments
This paper introduces an adaptive application deployment service for virtualized environments (named DECIDE). This service facilitates the definition of customized cluster/cloud environment and the adaptive integration of scheduling policies for testing and deploying containerized applications. The service-based design of DECIDE and the use of a virtualized environment makes it possible to easily change the cluster/cloud configuration and its scheduling policy. It provides a differentiated service for application deployment based on priorities, according to user requirements. A prototype of this service was implemented using Apache MESOS and Docker. As a proof of concept, a federated application for electronic identification (eIDAS) was deployed using the DECIDE approach, which allows users to evaluate different deployment scenarios and scheduling policies providing useful information for decision making. Experiments were carried out to validate service functionality and the feasibility for testing and deploying applications that require different scheduling policies.This work was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness under the grant TIN2016-79637-P “Towards Unification of HPC and Big Data Paradigms”
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World
This report documents the program and the outcomes of GI-Dagstuhl Seminar
16394 "Software Performance Engineering in the DevOps World".
The seminar addressed the problem of performance-aware DevOps. Both, DevOps
and performance engineering have been growing trends over the past one to two
years, in no small part due to the rise in importance of identifying
performance anomalies in the operations (Ops) of cloud and big data systems and
feeding these back to the development (Dev). However, so far, the research
community has treated software engineering, performance engineering, and cloud
computing mostly as individual research areas. We aimed to identify
cross-community collaboration, and to set the path for long-lasting
collaborations towards performance-aware DevOps.
The main goal of the seminar was to bring together young researchers (PhD
students in a later stage of their PhD, as well as PostDocs or Junior
Professors) in the areas of (i) software engineering, (ii) performance
engineering, and (iii) cloud computing and big data to present their current
research projects, to exchange experience and expertise, to discuss research
challenges, and to develop ideas for future collaborations
ENORM: A Framework For Edge NOde Resource Management
Current computing techniques using the cloud as a centralised server will
become untenable as billions of devices get connected to the Internet. This
raises the need for fog computing, which leverages computing at the edge of the
network on nodes, such as routers, base stations and switches, along with the
cloud. However, to realise fog computing the challenge of managing edge nodes
will need to be addressed. This paper is motivated to address the resource
management challenge. We develop the first framework to manage edge nodes,
namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for
provisioning and auto-scaling edge node resources are proposed. The feasibility
of the framework is demonstrated on a PokeMon Go-like online game use-case. The
benefits of using ENORM are observed by reduced application latency between 20%
- 80% and reduced data transfer and communication frequency between the edge
node and the cloud by up to 95\%. These results highlight the potential of fog
computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12
September 201
Performance-oriented Cloud Provisioning: Taxonomy and Survey
Cloud computing is being viewed as the technology of today and the future.
Through this paradigm, the customers gain access to shared computing resources
located in remote data centers that are hosted by cloud providers (CP). This
technology allows for provisioning of various resources such as virtual
machines (VM), physical machines, processors, memory, network, storage and
software as per the needs of customers. Application providers (AP), who are
customers of the CP, deploy applications on the cloud infrastructure and then
these applications are used by the end-users. To meet the fluctuating
application workload demands, dynamic provisioning is essential and this
article provides a detailed literature survey of dynamic provisioning within
cloud systems with focus on application performance. The well-known types of
provisioning and the associated problems are clearly and pictorially explained
and the provisioning terminology is clarified. A very detailed and general
cloud provisioning classification is presented, which views provisioning from
different perspectives, aiding in understanding the process inside-out. Cloud
dynamic provisioning is explained by considering resources, stakeholders,
techniques, technologies, algorithms, problems, goals and more.Comment: 14 pages, 3 figures, 3 table
CyberGuarder: a virtualization security assurance architecture for green cloud computing
Cloud Computing, Green Computing, Virtualization, Virtual Security Appliance, Security Isolation
DYVERSE: DYnamic VERtical Scaling in Multi-tenant Edge Environments
Multi-tenancy in resource-constrained environments is a key challenge in Edge
computing. In this paper, we develop 'DYVERSE: DYnamic VERtical Scaling in
Edge' environments, which is the first light-weight and dynamic vertical
scaling mechanism for managing resources allocated to applications for
facilitating multi-tenancy in Edge environments. To enable dynamic vertical
scaling, one static and three dynamic priority management approaches that are
workload-aware, community-aware and system-aware, respectively are proposed.
This research advocates that dynamic vertical scaling and priority management
approaches reduce Service Level Objective (SLO) violation rates. An online-game
and a face detection workload in a Cloud-Edge test-bed are used to validate the
research. The merits of DYVERSE is that there is only a sub-second overhead per
Edge server when 32 Edge servers are deployed on a single Edge node. When
compared to executing applications on the Edge servers without dynamic vertical
scaling, static priorities and dynamic priorities reduce SLO violation rates of
requests by up to 4% and 12% for the online game, respectively, and in both
cases 6% for the face detection workload. Moreover, for both workloads, the
system-aware dynamic vertical scaling method effectively reduces the latency of
non-violated requests, when compared to other methods
DISCO: Distributed Multi-domain SDN Controllers
Modern multi-domain networks now span over datacenter networks, enterprise
networks, customer sites and mobile entities. Such networks are critical and,
thus, must be resilient, scalable and easily extensible. The emergence of
Software-Defined Networking (SDN) protocols, which enables to decouple the data
plane from the control plane and dynamically program the network, opens up new
ways to architect such networks. In this paper, we propose DISCO, an open and
extensible DIstributed SDN COntrol plane able to cope with the distributed and
heterogeneous nature of modern overlay networks and wide area networks. DISCO
controllers manage their own network domain and communicate with each others to
provide end-to-end network services. This communication is based on a unique
lightweight and highly manageable control channel used by agents to
self-adaptively share aggregated network-wide information. We implemented DISCO
on top of the Floodlight OpenFlow controller and the AMQP protocol. We
demonstrated how DISCO's control plane dynamically adapts to heterogeneous
network topologies while being resilient enough to survive to disruptions and
attacks and providing classic functionalities such as end-point migration and
network-wide traffic engineering. The experimentation results we present are
organized around three use cases: inter-domain topology disruption, end-to-end
priority service request and virtual machine migration
- …