Dynamic virtual network traffic engineering with energy efficiency in multi-location data center networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)For cloud enterprise customers that require services on demand, data centers must allocate and partition data center resources in a dynamic fashion. We consider the problem in which a request from an enterprise customer is mapped to a virtual network (VN) that is allocated requiring both bandwidth and compute resources by connecting it from an entry point of a data center to one or more servers, should this data center be selected from multiple geographically distributed data centers. We present a dynamic traffic engineering framework, for which we develop an optimization model based on a mixed-integer linear programming (MILP) formulation that a data center operator can use at each review point to optimally assign VN customers. Through a series of studies, we then present results on how different VN customers are treated in terms of request acceptance when each VN class has a different resource requirement. We found that a VN class with a low resource requirement has a low blocking even in heavy traffic, while the VN class with a high resource requirement faces a high service denial. On the other hand, cost for the VN with the highest resource requirement is not always the highest in the heavy traffic because of the significantly high service denial faced by this VN class.1017School of Graduate Studies Research Grant at the University of Missouri-Kansas CityNational Science Foundation [1526299]CNPq (National Counsel of Technological and Scientific Development), BrazilConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)28th International Teletraffic Congress (ITC)SEP 12-16, 2016Univ Wurzburg, Wurzburg, GERMAN

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

Software-Defined Cloud Computing: Architectural Elements and Open Challenges

The variety of existing cloud services creates a challenge for service providers to enforce reasonable Software Level Agreements (SLA) stating the Quality of Service (QoS) and penalties in case QoS is not achieved. To avoid such penalties at the same time that the infrastructure operates with minimum energy and resource wastage, constant monitoring and adaptation of the infrastructure is needed. We refer to Software-Defined Cloud Computing, or simply Software-Defined Clouds (SDC), as an approach for automating the process of optimal cloud configuration by extending virtualization concept to all resources in a data center. An SDC enables easy reconfiguration and adaptation of physical resources in a cloud infrastructure, to better accommodate the demand on QoS through a software that can describe and manage various aspects comprising the cloud environment. In this paper, we present an architecture for SDCs on data centers with emphasis on mobile cloud applications. We present an evaluation, showcasing the potential of SDC in two use cases-QoS-aware bandwidth allocation and bandwidth-aware, energy-efficient VM placement-and discuss the research challenges and opportunities in this emerging area.Comment: Keynote Paper, 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2014), September 24-27, 2014, Delhi, Indi