Algorithms for advance bandwidth reservation in media production networks

Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results

Can open-source projects (re-) shape the SDN/NFV-driven telecommunication market?

Telecom network operators face rapidly changing business needs. Due to their dependence on long product cycles they lack the ability to quickly respond to changing user demands. To spur innovation and stay competitive, network operators are investigating technological solutions with a proven track record in other application domains such as open source software projects. Open source software enables parties to learn, use, or contribute to technology from which they were previously excluded. OSS has reshaped many application areas including the landscape of operating systems and consumer software. The paradigmshift in telecommunication systems towards Software-Defined Networking introduces possibilities to benefit from open source projects. Implementing the control part of networks in software enables speedier adaption and innovation, and less dependencies on legacy protocols or algorithms hard-coded in the control part of network devices. The recently proposed concept of Network Function Virtualization pushes the softwarization of telecommunication functionalities even further down to the data plane. Within the NFV paradigm, functionality which was previously reserved for dedicated hardware implementations can now be implemented in software and deployed on generic Commercial Off-The Shelf (COTS) hardware. This paper provides an overview of existing open source initiatives for SDN/NFV-based network architectures, involving infrastructure to orchestration-related functionality. It situates them in a business process context and identifies the pros and cons for the market in general, as well as for individual actors

Orchestrator conversation : distributed management of cloud applications

Managing cloud applications is complex, and the current state of the art is not addressing this issue. The ever-growing software ecosystem continues to increase the knowledge required to manage cloud applications at a time when there is already an IT skills shortage. Solving this issue requires capturing IT operation knowledge in software so that this knowledge can be reused by system administrators who do not have it. The presented research tackles this issue by introducing a new and fundamentally different way to approach cloud application management: a hierarchical collection of independent software agents, collectively managing the cloud application. Each agent encapsulates knowledge of how to manage specific parts of the cloud application, is driven by sending and receiving cloud models, and collaborates with other agents by communicating using conversations. The entirety of communication and collaboration in this collection is called the orchestrator conversation. A thorough evaluation shows the orchestrator conversation makes it possible to encapsulate IT operations knowledge that current solutions cannot, reduces the complexity of managing a cloud application, and happens inherently concurrent. The evaluation also shows that the conversation figures out how to deploy a single big data cluster in less than 100 milliseconds, which scales linearly to less than 10 seconds for 100 clusters, resulting in a minimal overhead compared with the deployment time of at least 20 minutes with the state of the art

Network Service Orchestration: A Survey

Business models of network service providers are undergoing an evolving transformation fueled by vertical customer demands and technological advances such as 5G, Software Defined Networking~(SDN), and Network Function Virtualization~(NFV). Emerging scenarios call for agile network services consuming network, storage, and compute resources across heterogeneous infrastructures and administrative domains. Coordinating resource control and service creation across interconnected domains and diverse technologies becomes a grand challenge. Research and development efforts are being devoted to enabling orchestration processes to automate, coordinate, and manage the deployment and operation of network services. In this survey, we delve into the topic of Network Service Orchestration~(NSO) by reviewing the historical background, relevant research projects, enabling technologies, and standardization activities. We define key concepts and propose a taxonomy of NSO approaches and solutions to pave the way towards a common understanding of the various ongoing efforts around the realization of diverse NSO application scenarios. Based on the analysis of the state of affairs, we present a series of open challenges and research opportunities, altogether contributing to a timely and comprehensive survey on the vibrant and strategic topic of network service orchestration.Comment: Accepted for publication at Computer Communications Journa

An elastic software architecture for extreme-scale big data analytics

This chapter describes a software architecture for processing big-data analytics considering the complete compute continuum, from the edge to the cloud. The new generation of smart systems requires processing a vast amount of diverse information from distributed data sources. The software architecture presented in this chapter addresses two main challenges. On the one hand, a new elasticity concept enables smart systems to satisfy the performance requirements of extreme-scale analytics workloads. By extending the elasticity concept (known at cloud side) across the compute continuum in a fog computing environment, combined with the usage of advanced heterogeneous hardware architectures at the edge side, the capabilities of the extreme-scale analytics can significantly increase, integrating both responsive data-in-motion and latent data-at-rest analytics into a single solution. On the other hand, the software architecture also focuses on the fulfilment of the non-functional properties inherited from smart systems, such as real-time, energy-efficiency, communication quality and security, that are of paramount importance for many application domains such as smart cities, smart mobility and smart manufacturing.The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the ELASTIC Project (www.elastic-project.eu), grant agreement No 825473.Peer ReviewedPostprint (published version

Industry Simulation Gateway on a Scalable Cloud

Large scale simulation experimentation typically requires significant computational resources due to an excessive number of simulation runs and replications to be performed. The traditional approach to provide such computational power, both in academic research and industry/business applications, was to use computing clusters or desktop grid resources. However, such resources not only require upfront capital investment but also lack the flexibility and scalability that is required to serve a variable number of clients/users efficiently. This paper presents how SakerGrid, a commercial desktop grid based simulation platform and its associated science gateway have been extended towards a scalable cloud computing solution. The integration of SakerGrid with the MiCADO automated deployment and autoscaling framework supports the execution of multiple simulation experiments by dynamically allocating virtual machines in the cloud in order to complete the experiment by a user-defined deadline

A New Paradigm to Address Threats for Virtualized Services

With the uptaking of virtualization technologies and the growing usage of public cloud infrastructures, an ever larger number of applications run outside of the traditional enterprise’s perimeter, and require new security paradigms that fit the typical agility and elasticity of cloud models in service creation and management. Though some recent proposals have integrated security appliances in the logical application topology, we argue that this approach is sub-optimal. Indeed, we believe that embedding security agents in virtualization containers and delegating the control logic to the software orchestrator provides a much more effective, flexible, and scalable solution to the problem. In this paper, we motivate our mindset and outline a novel framework for assessing cyber-threats of virtualized applications and services. We also review existing technologies that build the foundation of our proposal, which we are going to develop in the context of a joint research project