Aris Leivadeas

On the optimal allocation of virtual resources in cloud computing networks

Cloud computing builds upon advances on virtualization and distributed computing to support cost-efficient usage of computing resources, emphasizing on resource scalability and on demand services. Moving away from traditional data-center oriented models, distributed clouds extend over a loosely coupled federated substrate, offering enhanced communication and computational services to target end-users with quality of service (QoS) requirements, as dictated by the future Internet vision. Toward facilitating the efficient realization of such networked computing environments, computing and networking resources need to be jointly treated and optimized. This requires delivery of user-driven sets of virtual resources, dynamically allocated to actual substrate resources within networked clouds, creating the need to revisit resource mapping algorithms and tailor them to a composite virtual resource mapping problem. In this paper, toward providing a unified resource allocation framework for networked clouds, we first formulate the optimal networked cloud mapping problem as a mixed integer programming (MIP) problem, indicating objectives related to cost efficiency of the resource mapping procedure, while abiding by user requests for QoS-aware virtual resources. We subsequently propose a method for the efficient mapping of resource requests onto a shared substrate interconnecting various islands of computing resources, and adopt a heuristic methodology to address the problem. The efficiency of the proposed approach is illustrated in a simulation/emulation environment, that allows for a flexible, structured, and comparative performance evaluation. We conclude by outlining a proof-of-concept realization of our proposed schema, mounted over the European future Internet test-bed FEDERICA, a resource virtualization platform augmented with network and computing facilities.

A Cloud-Oriented Content Delivery Network Paradigm: Modeling and Assessment

Cloud-oriented content delivery networks (CCDNs) constitute a promising alternative to traditional content delivery networks. Exploiting the advantages and principles of the cloud, such as the pay as you go business model and geographical dispersion of resources, CCDN can provide a viable and cost-effective solution for realizing content delivery networks and services. In this paper, a hierarchical framework is proposed and evaluated toward an efficient and scalable solution of content distribution over a multiprovider networked cloud environment, where inter and intra cloud communication resources are simultaneously considered along with traditional cloud computing resources. To efficiently deal with the CCDN deployment problem in this emerging and challenging computing paradigm, the problem is decomposed to graph partitioning and replica placement problems while appropriate cost models are introduced/adapted. Novel approaches on the replica placement problem within the cloud are proposed while the limitations of the physical substrate are taken into consideration. The performance of the proposed hierarchical CCDN framework is assessed via modeling and simulation, while appropriate metrics are defined/adopted associated with and reflecting the interests of the different identified involved key players.

Efficient Resource Mapping Framework over Networked Clouds via Iterated Local Search-Based Request Partitioning

The cloud represents a computing paradigm where shared configurable resources are provided as a service over the Internet. Adding intra- or intercloud communication resources to the resource mix leads to a networked cloud computing environment. Following the cloud infrastructure as a Service paradigm and in order to create a flexible management framework, it is of paramount importance to address efficiently the resource mapping problem within this context. To deal with the inherent complexity and scalability issue of the resource mapping problem across different administrative domains, in this paper a hierarchical framework is described. First, a novel request partitioning approach based on Iterated Local Search is introduced that facilitates the cost-efficient and online splitting of user requests among eligible cloud service providers (CPs) within a networked cloud environment. Following and capitalizing on the outcome of the request partitioning phase, the embedding phase—where the actual mapping of requested virtual to physical resources is performed can be realized through the use of a distributed intracloud resource mapping approach that allows for efficient and balanced allocation of cloud resources. Finally, a thorough evaluation of the proposed overall framework on a simulated networked cloud environment is provided and critically compared against an exact request partitioning solution as well as another common intradomain virtual resource embedding solution.

Socio-aware virtual network embedding

Network virtualization provides a powerful way to run multiple networks over a shared substrate and has been recognized as a key enabler for overcoming the perceived ossification of the current Internet. This article addresses a specific aspect of network virtualization, virtual network embedding (VNE), which primarily refers to the efficient mapping of virtual resources onto physical ones. Specifically, influenced and inspired by the intersection of recent trends in network virtualization, social network analysis, and service-centric future Internet architectures, in this article the scope of the VNE paradigm is extended by including socio-aware features. Toward this direction, appropriate social-based metrics are introduced, and the conventional VNE objective of minimizing the cost of embedding a request into the substrate under certain physical constraints is extended by considering an additional objective related to the social features of the physical network. An evaluation of the proposed socio-aware VNE paradigm with respect to several aspects and metrics (i.e., accounting, social) is provided and critically compared against conventional VNE approaches. The corresponding results and observations support the vision of paving the way to adopting social-aware virtualized topologies for fostering specific applications within the future Internet paradigm. Finally, the adaptation and prototype of a socio-aware resource mapping approach on a wireless virtualized testbed is summarized, serving as a proof of concept.

Resource discovery and allocation for federated virtualized infrastructures

The European Union Project Networking innovations Over Virtualized Infrastructures (NOVI) set out to design and implement a modular data, control and management plane federation architecture, leading to an integrated experimental prototype mounted on interconnected European Future Internet testbeds. In this paper we present the components of this architecture, responsible for resource discovery and mapping of virtual topologies over a federated multi-domain network virtualization environment. We subsequently introduce a method for the efficient mapping of user requests for virtual networks onto a substrate infrastructure, adopting a semantic-based approach to address the problem. The efficiency of the proposed scheme is evaluated via simulation and critically compared against common non-semantic-based solutions. Networking innovations over virtualized infrastructures-NOVI federation architecture.Resource discovery and allocation over multi-domain virtualized infrastructures.Prototype of a distributed, semantic-based resource discovery and mapping framework.A semantic aware virtual network embedding algorithm.The approach is evaluated via simulation against non-semantic aware solutions.

Energy Aware Networked Cloud Mapping

Cloud computing has emerged as the computing paradigm that enables the delivery of utility-based IT services to users. The hyper-growth of Cloud computing has led to increased power consumption with significant consequences both in terms of environmental and operational costs. Hence, over the last years, attention has been drawn to optimizing energy consumption at the data center, aimed at the reduction of carbon footprints. However the world of Cloud Computing is constantly developing, with new concepts introduced while additional challenges arise. In this paper, a method for energy efficient resource allocation is proposed, in the context of a networked cloud environment. The method employs dynamic server consolidation by periodic VM migration. The approach is validated conducting performance evaluation via simulation, while it is compared against energy aware / non energy aware methods, using a set of both power indication and resource allocation metrics.

Optimal virtualized network function allocation for an SDN enabled cloud

Enterprise and Service Provider networks are increasingly making use of Virtualized Network Functions (VNFs) to reap the benefits of reduced Capital expenditures (CAPEX) and Operating expenses (OPEX). Total cost of ownership calculations however are typically a function of the attainable network performance, which in a virtualized system is highly dependent on the overall system architecture and the resource allocation policy. This paper examines how to improve the overall performance of deploying VNFs in a virtualized environment, proposing an appropriate architectural framework to leverage the capabilities of other technologies such as Software Defined Networking (SDN) and Cloud Computing which can be highly complemented with the Network Function Virtualization (NFV) paradigm. We focus on the standardization of the three technologies under a common architecture and we incorporate resource allocation as a main functional architectural block. The problem studied is referred as the VNF placement problem, and tries to efficiently, intelligently, and dynamically allocate a series of VNFs comprising a service chain in a cloud environment according to the current status of the cloud resources. We propose and evaluate a set of algorithms towards satisfying the requirement of enterprise and service providers to grant high performance VNFs for the end users, while allowing the cloud providers to profitably utilize the available resources. Graphical abstractDisplay Omitted HighlightsDynamic traffic steering and allocation of a service chain in an SDN enabled Cloud.Service Chain Deployment Models.Standardization of NFV, SDN, and Cloud Computing.Optimal VNF allocation based in Mixed Integer Programming.Heuristic Algorithms to approximate optimal solution.

Performance analysis of virtualized network functions on virtualized systems architectures

Network Function Virtualization (NFV) is an emerging network architecture that employs the concept of virtualization and allows the consolidation of many network services on top of an industry standard off-the-shelf server. This decoupling of network functions and services from dedicated and expensive hardware appliances has led the Enterprise and Service Providers to increasingly make use of Virtualized Network Functions (VNFs) to reap the benefits of reduced capital and operational expenses. Total cost of ownership calculations however are typically a function of the attainable network throughput and performance, which in a virtualized system is highly dependent on the overall system architecture. The number of VNFs running on the server, their I/O demands, the performance characterization of the underlying hypervisor scheduler, or the packet path from physical interfaces into the VNFs are examples of how the system architecture can influence overall performance and throughput. This article provides the challenges of deploying VNFs on a virtualized system architecture and analyzes the impact of the architecture on the overall VNF performance under both single-VNF and multi-VNF configurations.

Resource Management and Orchestration for a Dynamic Service Chain Steering Model

Network Function Virtualization along with Network Service Chaining envision a reduction in the respective cost that end users, service providers, and network operators are experiencing, while providing complete and high quality services. However, the vast range of available services and the service on-demand model, creates dynamic traffic conditions that necessitates a flexible and automatic network platform to redirect traffic according to network conditions. In this paper, we study the problem of deploying service chains, consisting of a number of virtualized network functions (VNFs), in a SDN enabled data center network, where a random number of users are associated with each service chain. To this end, appropriate resource management algorithms are introduced for the placement of VNFs satisfying server affinity and latency constraints. The interconnection of the VNFs is facilitated by an SDN controller, which periodically recalculates the routing paths to adjust to the dynamic traffic conditions.

Dynamic traffic steering of multi-tenant virtualized network functions in SDN enabled data centers

Network Functions Visualization (NFV) builds upon virtualization technology and allows the decoupling of network services from dedicated and complex hardware-based appliances. This decoupling allows network providers to install these functions in commercial off-the-shelf hardware reducing the overall capital and operational expenses. In order to provide complete and high quality services to the end users, a series of these functions may need to be traversed creating a service chain model. In this paper, we study the problem of allocating a dynamic service chain, where a random number of users are associated with each service chain, in a data center network. The allocation consists of the placement of VNFs in appropriate servers and the interconnection between these servers. This interconnection is facilitated by an SDN controller, which proves to be complementary with the NFV paradigm. Towards these aims, we propose two algorithms for the placement of the VNFs, while the SDN controller periodically recalculates the routing paths to adjust to the dynamic traffic conditions.