A Lightweight, Non-intrusive Approach for Orchestrating Autonomously-managed Network Elements

Software-Defined Networking enables the centralized orchestration of data traffic within a network. However, proposed solutions require a high degree of architectural penetration. The present study targets the orchestration of network elements that do not wish to yield much of their internal operations to an external controller. Backpressure routing principles are used for deriving flow routing rules that optimally stabilize a network, while maximizing its throughput. The elements can then accept in full, partially or reject the proposed routing rule-set. The proposed scheme requires minimal, relatively infrequent interaction with a controller, limiting its imposed workload, promoting scalability. The proposed scheme exhibits attracting network performance gains, as demonstrated by extensive simulations and proven via mathematical analysis.Comment: 6 pages 7, figures, IEEE ISCC'1

Traffic Profiling for Mobile Video Streaming

This paper describes a novel system that provides key parameters of HTTP Adaptive Streaming (HAS) sessions to the lower layers of the protocol stack. A non-intrusive traffic profiling solution is proposed that observes packet flows at the transmit queue of base stations, edge-routers, or gateways. By analyzing IP flows in real time, the presented scheme identifies different phases of an HAS session and estimates important application-layer parameters, such as play-back buffer state and video encoding rate. The introduced estimators only use IP-layer information, do not require standardization and work even with traffic that is encrypted via Transport Layer Security (TLS). Experimental results for a popular video streaming service clearly verify the high accuracy of the proposed solution. Traffic profiling, thus, provides a valuable alternative to cross-layer signaling and Deep Packet Inspection (DPI) in order to perform efficient network optimization for video streaming.Comment: 7 pages, 11 figures. Accepted for publication in the proceedings of IEEE ICC'1

Managing services quality through admission control and active monitoring

We propose a lightweight traffic admission control scheme based on on-line monitoring which ensures multimedia services quality both intra-domain and end-to-end. The AC strategy is distributed, service-oriented and allows to control QoS and SLS without adding complexity to the network core. For each service class, AC decisions are driven by rate-based SLS control rules and QoS parameters control rules, defined and parameterized according to each service characteristics. These rules are essentially based on systematic on-line measurements of relevant QoS and performance parameters. Thus, from a practical perspective, we discuss and evaluate methodologies and mechanisms for parameter estimation. The AC criteria is evaluated as regards its ability to ensure service commitments while achieving high network utilization. The results show that the proposed model provides a good compromise between simplicity, service level guarantee and network usage, even for services with strict QoS requirements

Distributed admission control for QoS and SLS management

This article proposes a distributed admission control (AC) model based on on-line monitoring to manage the quality of Internet services and Service Level Specifications (SLSs) in class-based networks. The AC strategy covers intra- and interdomain operation, without adding significant complexity to the network control plane and involving only edge nodes. While ingress nodes perform implicit or explicit AC resorting to service-oriented rules for SLS and QoS parameters control, egress nodes collect service metrics providing them as inputs for AC. The end-to-end operation is viewed as a cumulative and repetitive process of AC and available service computation.We discuss crucial key points of the model implementation and evaluate its two main components: themonitoring process and the AC criteria. The results show that, using proper AC rules and safety margins, service commitments can be efficiently satisfied, and the simplicity and flexibility of the model can be explored to manage successfully QoS requirements of multiple Internet services.(undefined

NFV Platforms: Taxonomy, Design Choices and Future Challenges

Due to the intrinsically inefficient service provisioning in traditional networks, Network Function Virtualization (NFV) keeps gaining attention from both industry and academia. By replacing the purpose-built, expensive, proprietary network equipment with software network functions consolidated on commodity hardware, NFV envisions a shift towards a more agile and open service provisioning paradigm. During the last few years, a large number of NFV platforms have been implemented in production environments that typically face critical challenges, including the development, deployment, and management of Virtual Network Functions (VNFs). Nonetheless, just like any complex system, such platforms commonly consist of abounding software and hardware components and usually incorporate disparate design choices based on distinct motivations or use cases. This broad collection of convoluted alternatives makes it extremely arduous for network operators to make proper choices. Although numerous efforts have been devoted to investigating different aspects of NFV, none of them specifically focused on NFV platforms or attempted to explore their design space. In this paper, we present a comprehensive survey on the NFV platform design. Our study solely targets existing NFV platform implementations. We begin with a top-down architectural view of the standard reference NFV platform and present our taxonomy of existing NFV platforms based on what features they provide in terms of a typical network function life cycle. Then we thoroughly explore the design space and elaborate on the implementation choices each platform opts for. We also envision future challenges for NFV platform design in the incoming 5G era. We believe that our study gives a detailed guideline for network operators or service providers to choose the most appropriate NFV platform based on their respective requirements. Our work also provides guidelines for implementing new NFV platforms

Predicting Traffic Flow Size and Duration

Current networks suffer from poor traffic management that leads to traffic congestion, even when some parts of the network are still unused. In traditional networks each node decides how to forward traffic based only on local reachability knowledge in a setting where optimizing the cost and efficiency of the network is a complex task. Modern networking technologies like Software-Defined Networking (SDN) provide automation and programmability to Networks. In such networks control functions can be applied in a different manner to each specific traffic flow and a variety of traffic information can be gathered from several different sources. This dissertation studies the feasibility of an intelligent network that can predict traffic characteristics, when the first packets arrive. The goal is to know the duration and size of flow to improve scheduling, load balancing and routing capabilities. An OpenFlow application is implemented in an SDN Data Collecting Controller (DCC), that shows how the first few packets of a traffic flow can be gathered with scalability concerns and in a non-intrusive way. The use of different classifiers such as Random Forest, Naive Bayes, Support Vector Machines, Multi-layer Perceptron and K-Neighbour for effective flow duration and size classification is studied. The results of using each of these classifiers to predict flow size and duration using the DCC gathered data are presented and compared

Passive network awareness as a means for improved grid scheduling

Grids enable sharing resources of heterogeneous nature and administration. In such distributed systems, the network is usually taken for granted which is potentially problematic due to the complexity and unpredictability of public networks that typically underlie grids. This article introduces GridMAP, a mechanism for considering the network state for enhancing grid scheduling. Network measurements are collected in a passive manner from a user-centric vantage point. This mechanism has been evaluated on a production e-science grid infrastructure, with results showing the ability of GridMAP to improve grid scheduling with minimal network, computational and deployment overheads