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%

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

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

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

Paradoxical and powerful: Volunteers’ experiences of befriending people with dementia

This qualitative UK study explored the lived experiences of volunteer befrienders to people with dementia, using interpretative phenomenological analysis. Individual semi-structured interviews were conducted with nine befrienders aged between 25 and 66 years. The relationship that developed between befriender and befriendee was at the heart of befrienders’ experiences. It comprised numerous paradoxical processes that generated issues of power, equality and boundaries, characterising befriending as a complex and unique phenomenon. Befriending was expressed as a deeply personal and human experience, often with emotional power and profound meaning. Befrienders’ personal learning included seeing past dementia stereotypes, challenging their own assumptions and boundaries, and reflecting on love, life and humanness. Dissemination of these findings could help to challenge the stigma around dementia, and enhance recruitment and support of dementia befrienders. Future research should consider befriendee experiences of the relationship, additional measures of befriending effectiveness, and exploration of befriender attrition and support. </jats:p

Dual tasking interferes with dynamic balance in young and old healthy adults

BACKGROUND: Functional mobility requires an ability to adapt to environmental factors together with an ability to execute a secondary task simultaneously while walking. A complex dual-tasking gait test may provide an indication of functional ability and falls risk among community-dwelling older adults. PURPOSE: The aim of this cross-sectional study is to investigate age-related differences in dual-tasking ability and to evaluate whether dual-tasking ability is related to executive function. METHODS: Forty-one community-dwelling healthy older and forty-one younger adults completed a dual-tasking assessment in which concurrent tasks were incorporated into the Functional Gait Assessment (FGA). The manual dual-task involved carrying a glass of water (FGA-M) while the cognitive dual-tasks involved numeracy (FGA-N) and literacy (FGA-L) related tasks. FGA scores under single (FGA-S) and dual-task conditions together with associated dual-task costs and response accuracy were determined. Executive function was assessed using The Behavioural Assessment of the Dysexecutive Syndrome (BADS). RESULTS: FGA-N and FGA-L scores were adversely affected in both groups compared to FGA-S (p≤0.001). However, score reductions and dual-task costs were significantly greater for older adults compared to younger adults on FGA-N (p≤0.05) and FGA-L (p≤0.001), with older adult performance on FGA-N associated with falls risk (p≤0.05). Executive function did not appear to be related to dual-tasking ability. CONCLUSION: Findings suggest that cognitively demanding tasks while walking, have a deleterious effect on dynamic balance and could place older adults at a greater risk of falls