Management Application Interactions in Software-Based Networks

IEEE To support the next wave of networking technologies and services, which will likely involve heterogeneous resources and requirements, rich management functionality will need to be deployed. This raises questions regarding the interoperability of such functionality in an environment where potentially interacting applications operate in parallel. Interactions can cause configuration instabilities and subsequently network performance degradation, especially in the presence of contradicting objectives. Detecting and handling these interactions is therefore essential. In this article we present an overview of the interaction management problem, a critical issue in software-based networks. We review and compare existing solutions proposed in the literature and discuss key challenges toward the development of a generic framework for the automated and real-time management of these interactions

Proactive multi-tenant cache management for virtualized ISP networks

The content delivery market has mainly been dominated by large Content Delivery Networks (CDNs) such as Akamai and Limelight. However, CDN traffic exerts a lot of pressure on Internet Service Provider (ISP) networks. Recently, ISPs have begun deploying so-called Telco CDNs, which have many advantages, such as reduced ISP network bandwidth utilization and improved Quality of Service (QoS) by bringing content closer to the end-user. Virtualization of storage and networking resources can enable the ISP to simultaneously lease its Telco CDN infrastructure to multiple third parties, opening up new business models and revenue streams. In this paper, we propose a proactive cache management system for ISP-operated multi-tenant Telco CDNs. The associated algorithm optimizes content placement and server selection across tenants and users, based on predicted content popularity and the geographical distribution of requests. Based on a Video-on-Demand (VoD) request trace of a leading European telecom operator, the presented algorithm is shown to reduce bandwidth usage by 17% compared to the traditional Least Recently Used (LRU) caching strategy, both inside the network and on the ingress links, while at the same time offering enhanced load balancing capabilities. Increasing the prediction accuracy is shown to have the potential to further improve bandwidth efficiency by up to 79%

On the Placement of Management and Control Functionality in Software Defined Networks

In order to support reactive and adaptive operations, Software-Defined Networking (SDN)-based management and control frameworks call for decentralized solutions. A key challenge to consider when deploying such solutions is to decide on the degree of distribution of the management and control functionality. In this paper, we develop an approach to determine the allocation of management and control entities by designing two algorithms to compute their placement. The algorithms rely on a set of input parameters which can be tuned to take into account the requirements of both the network infrastructure and the management applications to execute in the network. We evaluate the influence of these parameters on the configuration of the resulting management and control planes based on real network topologies and provide guidelines regarding the settings of the proposed algorithms

Toughening and stiffening of starch food extrudates through the addition of cellulose fibres and minerals

Pet food, one of the largest type of commercial packaged foods, continuously sets new challenges, amongst them the possibility to enhance palatability via adjusting product composition. This will optimise texture perception across consumer groups of diverse chewing capabilities, as well as improve food oral breakdown efficiency with further impact on metabolic health and nutrient bioavailability in the digestive process. Our aim is to pioneer new methods of controlling texture by answering longstanding questions such as the impact of nutrients on the mechanical properties of foods. The impact of cellulose fibres and minerals on the fracture toughness and stiffness properties of starch food extrudates is investigated for the first time through employing tensile tests and two fracture toughness tests namely Essential Work of Fracture (EWF) and cutting, on four different compositions. Fibres alone are found to increase stiffness (stiffening) and toughness (toughening) whereas minerals decrease stiffness (softening) with a minor influence on toughness. Interestingly, fibres and minerals combined maximise toughening at 28% compared to pure starch, due to the synergistic effect of fibre-matrix de-bonding and fibre breakage mechanisms at the crack tip. These new results indicate that texture can be significantly altered through the addition of minerals and short fibres. Such information is critical in the design of products that need to satisfy both nutritional and textural criteria

Decentralized Solutions for Monitoring Large-Scale Software-Defined Networks

Software-Defined Networking (SDN) technologies offer the possibility to automatically and frequently reconfigure the network resources by enabling simple and flexible network programmability. One of the key challenges to address when developing a new SDN-based solution is the design of a monitoring framework that can provide frequent and consistent updates to heterogeneous management applications. To cope with the requirements of large-scale networks (i.e. large number of geographically dispersed devices), a distributed monitoring approach is required. This PhD aims at investigating decentralized solutions for resource monitoring in SDN. The research will focus on the design of monitoring entities for the collection and processing of information at different network locations and will investigate how these can efficiently share their knowledge in a distributed management environment

CacheMAsT: Cache Management Analysis and Visualization Tool

Recent approaches have proposed to empower Internet Service Providers (ISPs) with caching capabilities that can allow them to implement their own cache management strategies and as such have better control over the utilization of their resources. In this demo paper, we present CacheMAsT (Cache Management Analysis and Visualization Tool), a decision support tool to visualize the configuration and performance of in-network cache management approaches. CacheMAsT is aimed at assisting researchers and engineers in analyzing and evaluating the different factors that can affect the performance of a cache management strategy and ultimately decide on the optimal approach to apply

Self-Tuning Service Provisioning for Decentralised Cloud Applications

Cloud computing has revolutionized service delivery by providing on-demand invocation and elasticity. To reap these benefits, computation has been displaced from client devices and into data centers. This partial centralization is undesirable for applications that have stringent locality requirements, e.g., low latency. This problem could be addressed with large numbers of smaller cloud resources closer to users. However, as cloud computing diffuses from within data centers and into the network, there will be a need for cloud resource allocation algorithms that operate on resource-constrained computational units that serve localized subsets of customers. In this paper, we present a mechanism for service provisioning in distributed clouds where applications compete for resources. The mechanism operates by enabling execution zones to assign resources based on Vickrey auctions and provides high-quality probabilistic models that applications can use to predict the outcomes of such auctions. This allows applications to use knowledge of the locality distribution of their clients to accurately select the number of bids to be sent to each execution zone and their value. The proposed mechanism is highly scalable, efficient, and validated by extensive simulations

Accuracy-Aware Adaptive Traffic Monitoring for Software Dataplanes

Network operators have recently been developing multi-Gbps traffic monitoring tools on commodity hardware, as part of the packet-processing pipelines realizing software dataplanes. These solutions allow the execution of sophisticated per-packet monitoring using the processing power available on servers. Although advances in packet capture have enabled the interception of packets at high rates, bottlenecks can still arise in the monitoring process as a result of concurrent access to shared processor resources, variations of the traffic skew, and unbalanced packet-rate spikes. In this paper we present an adaptive monitoring framework, →ol, which is resilient to bottlenecks while maintaining the accuracy of monitoring reports above a user-specified threshold. →ol dynamically reduces the measurement task sets under adverse conditions, and reconfigures them to recover potential accuracy degradations. To quantify the monitoring accuracy at run time, →ol adopts a novel task-independent technique that generates accuracy estimates according to recently observed traffic characteristics. With a prototype implementation based on a generic packet-processing pipeline, and using well-known measurements tasks, we show that →ol achieves lossless traffic monitoring for a wide range of conditions, significantly enhances the level of monitoring accuracy, and performs adaptations at the time scale of milliseconds with limited overhead

Managing the Future Internet through Intelligent In-Network Substrates

The current Internet has been founded on the architectural premise of a simple network service used to interconnect relatively intelligent end systems. While this simplicity allowed it to reach an impressive scale, the predictive manner in which ISP networks are currently planned and configured through external management systems and the uniform treatment of all traffic are hampering its use as a unifying multi-service network. The future Internet will need to be more intelligent and adaptive, optimizing continuously the use of its resources and recovering from transient problems, faults and attacks without any impact on the demanding services and applications running over it. This article describes an architecture that allows intelligence to be introduced within the network to support sophisticated self-management functionality in a coordinated and controllable manner. The presented approach, based on intelligent substrates, can potentially make the Internet more adaptable, agile, sustainable, and dependable given the requirements of emerging services with highly demanding traffic and rapidly changing locations. We discuss how the proposed framework can be applied to three representative emerging scenarios: dynamic traffic engineering (load balancing across multiple paths); energy efficiency in ISP network infrastructures; and cache management in content-centric networks

Extensible Signaling Framework for Decentralized Network Management Applications

The management of network infrastructures has become increasingly complex over time, which is mainly attributed to the introduction of new functionality to support emerging services and applications. To address this important issue, research efforts in the last few years focused on developing Software-Defined Networking solutions. While initial work proposed centralized architectures, their scalability limitations have led researchers to investigate a distributed control plane, with controller placement algorithms and mechanisms for building a logically centralized network view, being examples of challenges addressed. A critical issue that has not been adequately addressed concerns the communication between distributed decision-making entities to ensure configuration consistency. To this end, this paper proposes a signaling framework that can allow the exchange of information in distributed management and control scenarios. The benefits of the proposed framework are illustrated through a realistic network resource management use case. Based on simulation, we demonstrate the flexibility and extensibility of our solution in meeting the requirements of distributed decision-making processes