Impact of misbehaviour on QoS in wireless mesh networks

Proceedings of: 8th International IFIP-TC 6 Networking Conference (Networking 2009), Aachen, Germany, May 11-15, 2009This paper analyzes the impact of misbehaviour on QoS provisioning in wireless mesh networks. Misbehaviour occurs when a network participant decides not to cooperate. Since cooperation is fundamental for distributed environments such as mesh networks, misbehaviour can be a serious threat to them. In this work, the authors focus on the IEEE 802.11 EDCA medium access function which provides QoS in mesh networks. Simulation studies have been performed to determine what realistic forms of misbehaviour can occur and what their impact is. From these results the most beneficial forms of MAC layer misbehaviour in multihop mesh networks are derived.European Community's Seventh Framework ProgramThe research leading to these results has received funding from the European Community's Sixth Framework Programme under grant agreement n° 0384239 (NoE CONTENT). The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 214994.Publicad

A Survey of Green Networking Research

Reduction of unnecessary energy consumption is becoming a major concern in wired networking, because of the potential economical benefits and of its expected environmental impact. These issues, usually referred to as "green networking", relate to embedding energy-awareness in the design, in the devices and in the protocols of networks. In this work, we first formulate a more precise definition of the "green" attribute. We furthermore identify a few paradigms that are the key enablers of energy-aware networking research. We then overview the current state of the art and provide a taxonomy of the relevant work, with a special focus on wired networking. At a high level, we identify four branches of green networking research that stem from different observations on the root causes of energy waste, namely (i) Adaptive Link Rate, (ii) Interface proxying, (iii) Energy-aware infrastructures and (iv) Energy-aware applications. In this work, we do not only explore specific proposals pertaining to each of the above branches, but also offer a perspective for research.Comment: Index Terms: Green Networking; Wired Networks; Adaptive Link Rate; Interface Proxying; Energy-aware Infrastructures; Energy-aware Applications. 18 pages, 6 figures, 2 table

Understanding the implementation of evidence-based care: A structural network approach

<p>Abstract</p> <p>Background</p> <p>Recent study of complex networks has yielded many new insights into phenomenon such as social networks, the internet, and sexually transmitted infections. The purpose of this analysis is to examine the properties of a network created by the 'co-care' of patients within one region of the Veterans Health Affairs.</p> <p>Methods</p> <p>Data were obtained for all outpatient visits from 1 October 2006 to 30 September 2008 within one large Veterans Integrated Service Network. Types of physician within each clinic were nodes connected by shared patients, with a weighted link representing the number of shared patients between each connected pair. Network metrics calculated included edge weights, node degree, node strength, node coreness, and node betweenness. Log-log plots were used to examine the distribution of these metrics. Sizes of k-core networks were also computed under multiple conditions of node removal.</p> <p>Results</p> <p>There were 4,310,465 encounters by 266,710 shared patients between 722 provider types (nodes) across 41 stations or clinics resulting in 34,390 edges. The number of other nodes to which primary care provider nodes have a connection (172.7) is 42% greater than that of general surgeons and two and one-half times as high as cardiology. The log-log plot of the edge weight distribution appears to be linear in nature, revealing a 'scale-free' characteristic of the network, while the distributions of node degree and node strength are less so. The analysis of the k-core network sizes under increasing removal of primary care nodes shows that about 10 most connected primary care nodes play a critical role in keeping the <it>k</it>-core networks connected, because their removal disintegrates the highest <it>k</it>-core network.</p> <p>Conclusions</p> <p>Delivery of healthcare in a large healthcare system such as that of the US Department of Veterans Affairs (VA) can be represented as a complex network. This network consists of highly connected provider nodes that serve as 'hubs' within the network, and demonstrates some 'scale-free' properties. By using currently available tools to explore its topology, we can explore how the underlying connectivity of such a system affects the behavior of providers, and perhaps leverage that understanding to improve quality and outcomes of care.</p

Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

Simulation Analysis of Download and Recovery Processes in P2P Storage Systems

Peer-to-peer storage systems rely on data fragmentation and distributed storage. Unreachable fragments are continuously recovered, requiring multiple fragments of data (constituting a "block") to be downloaded in parallel. Recent modeling efforts have assumed the recovery process to follow an exponential distribution, an assumption made mainly in the absence of studies characterizing the "real" distribution of the recovery process. This report aims at filling this gap through an empirical study. To that end, we implement the distributed storage protocol in the NS-2 network simulator and run a total of six experiments covering a large variety of scenarios. We show that the fragment download time follows approximately an exponential distribution. We also show that the block download time and the recovery time essentially follow a hypo-exponential distribution with many distinct phases (maximum of as many exponentials). We use expectation maximization and least square estimation algorithms to fit the empirical distributions. We also provide a good approximation of the number of phases of the hypo-exponential distribution that applies in all scenarios considered. Last, we test the goodness of our fits using statistical (Kolmogorov-Smirnov test) and graphical methods

ENERGY AWARE TRAFFIC ENGINEERING IN WIRED COMMUNICATION NETWORKS

The reduction of power consumption in communication networks has become a key issue for both the Internet Service Providers (ISP) and the research community. Ac- cording to different studies, the power consumption of Information and Communication Technologies (ICT) varies from 2% to 10% of the worldwide power consumption [1,2]. Moreover, the expected trends for the future predict a notably increase of the ICT power consumption, doubling its value by 2020 [2] and growing to around 30% of the worldwide electricity demand by 2030 according to business-as-usual evaluation scenarios [15]. It is therefore not surprising that researchers, manufacturers and network providers are spending significant efforts to reduce the power consumption of ICT systems from dif- ferent angles. To this extent, networking devices waste a considerable amount of power. In partic- ular, their power consumption has always been increased in the last years, coupled with the increase of the offered performance [16]. Actually, power consumption of network- ing devices scales with the installed capacity, rather than the current load [17]. Thus, for an ISP the network power consumption is practically constant, unrespectively to traffic fluctuations. However, actual traffic is subject to strong day/night oscillations [3]. Thus, many devices are underutilized, especially during off-peak hours when traffic is low. This represents a clear opportunity for saving energy, since many resources (i.e., routers and links) are powered on without being fully utilized. In this context, resource consolidation is a known paradigm for the reduction of the power consumption. It consists in having a carefully selected subset of network devices entering a low power state, and use the rest to transport the required amount of traffic. This is possible without disrupting the Quality of Service (QoS) offered by the network infrastructure, since communication networks are designed over the peak foreseen traffic request, and with redundancy and over-provisioning in mind. In this thesis work, we present different techniques to perform resource consolida- tion in backbone IP-based networks, ranging from centralized solutions, where a central entity computes a global solution based on an omniscient vision of the network, to dis- tributed solutions, where single nodes take independent decisions on the local power- state, based solely on local knowledge. Moreover, different technological assumptions are made, to account for different possible directions of the network devices evolutions, ranging from the possibility to switch off linecard ports, to whole network nodes, and taking into account different power consumption profiles