Network resilience

Mobile Broadband (MBB) traffic is increasing rapidly, and is estimated to keep
growing in future due to the availability of high speed 3G/4G networks and
the popularity of mobile devices. People are accessing Internet irrespective
of their locations and time thus introducing mobility in the access paradigm
and making MBB as a future of the Internet. The expansion of MBB traffic
necessitates the detail study of the characteristics of MBB networks with regards
to network performance and reliability. It is observed that the literature towards
the study of MBB performance mostly concern static scenarios. Therefore,
in this thesis, effects of mobility on MBB performance are studied, and the
QoS performance of Norwegian MBB networks under mobility are compared
to provide a realistic view of the QoS characteristics experienced by the end-
users. For this, performance metrics such as delay, packet loss, connectivity are
measured for four operational MBB networks under mobility simultaneously
using NorNet Edge (NNE), the dedicated testbed for experimentation and
measurements in MBB networks. Measurements in different speed are
examined to see how speed affects MBB performance. Radio conditions such
as Local Area Code (LAC), Cell Identification (CellID) are also investigated to
establish relation between the measured performance and physical locations as
well as cell attachment and handover behaviors. Mode and Submode are also
observed to see 2G/3G networks coverage and packet distribution in HSPA+,
HSDPA, HSUPA, WCDMA and EDGE networks. The results of this thesis show
that MBB performance is affected (degraded) by mobility, but degree varies
with respect to performance metrics. It was found that MBB operators under
mobility perform differently even though the underlying technology is same.

Mycelial fungi grow as indeterminate adaptive networks that have to forage for scarce resources in a patchy and unpredictable environment under constant onslaught from
mycophagous animals. Development of contrast-independent network extraction algorithms has dramatically improved our ability to characterise these dynamic macroscopic networks and promises to bridge the gap between experiments in realistic experimental microcosms and graph-theoretic network analysis, greatly facilitating quantitative description of their complex behaviour. Furthermore, using digitised networks as inputs,
empirically-based minimal biophysical mass-flow models already provide a high degree of explanation for patterns of long-distance radiolabel movement, and hint at global control mechanisms emerging naturally as a consequence of the intrinsic hydraulic connectivity. Network resilience is also critical to survival and can be explored both in silico by removing links in the digitised networks according to particular rules, or in vivo by allowing different mycophagous invertebrates to graze on the networks. Survival depends on both the intrinsic architecture adopted by each species and the ability to reconnect following damage. It is hoped that a comparative approach may yield useful insights into not just fungal ecology, but also biologically inspired rules governing the combinatorial trade-off between cost, transport efficiency, resilience and control complexity for self-organised adaptive networks in other domains.

Software-defined networking provides abstractions and a flexible architecture for the easy configuration of network devices, based on the decoupling of the data and control planes. This separation has the potential to considerably simplify the implementation of resilience functionality (e.g., traffic classification, anomaly detection, traffic shaping) in future networks. Although software-defined networking in general, and OpenFlow as its primary realisation, provide such abstractions, support is still needed for orchestrating a collection of OpenFlow-enabled services that must cooperate to implement network-wide resilience. In this paper, we describe a resilience management framework that can be readily applied to this problem. An important part of the framework are policy-controlled management patterns that describe how to orchestrate individual resilience services, implemented as OpenFlow applications.

Railway network is an integral part of the economy of many countries. Identifying critical network elements can help network executives to take appropriate preventive actions before catastrophic disruptions or to add necessary redundancy to enhance the resilience of the rail network.  The criticality of an element or a link is measured by calculating increased cost or delay when that element is disrupted. In this paper, we propose a framework for assessing the vulnerability of the rail networks by introducing two bi-level models. The first model determines those critical links which have the greatest impact on the routing cost when interdicted, and the next one takes the cost of scheduling into account, in addition to that of routing, over all origins and destinations. The trains are scheduled by a time-space framework considering customer demand, track and station capacities, and time planning horizon. To overcome the difficulty of solving bi-level models, they are converted to single level models using a heuristic approach. The paper includes two computational instances. The first is a test network which its results are compared with a full enumeration approach, namely the network scan method. Also a case study focused on three disruption scenarios in the railway network of Iran illustrates application of the developed models. The accuracy of obtained results indicates the effectiveness of the proposed methodology. In addition, our method has a very short computational time compared to the network scan method.

The hydraulic reliability of a water distribution system (WDS) can be improved by increasing the resilience to failure conditions. In previous research, numerous measures have been developed to quantify network resilience, which has been consequently linked to the hydraulic reliability of WDSs. Often, the difference between the output pressure head and the minimum required pressure head is required in the calculation of these network resilience measures. Difficulties arise when these measures are applied to water transmission systems (WTSs). The reason for this is that in a WTS, water is often pumped into a storage tank or reservoir, in which case the difference between the output pressure head and the minimum required pressure head is always zero. To overcome this shortcoming, it is suggested that the surplus power factor can be used as a network resilience measure because calculation of this measure does not require the pressure value at the outlet of a WDS. In the research presented here, three case studies are used to assess the suitability of the surplus power factor as a network resilience measure for WDSs. A fourth case study is used to demonstrate the application of surplus power factor as a network resilience measure for WTSs, to which the other measures cannot be applied. The results show that the surplus power factor can be used as a network resilience measure to incorporate hydraulic reliability considerations into the optimization of WDSs and particularly WTSs.

This paper deals with the comparative study of agile processes. The paper will serve as guide to other software development process models. Agile processes have important applications in the areas of software project management, software schedule management, etc. In particular the aim of agile processes is to satisfy the customer, faster development times with lower defects rate. This paper compares the agile processes with other software development life cycle models. Agile processes are not always advantageous, they have some drawbacks as well; the advantages and disadvantages of agile processes are also discussed in this paper.

Transportation network vulnerability analysis has developed increasingly in the last decade with the goal to identify the most critical locations against incidences. In this domain, many of the previous researches have focused on congested urban networks; however, there is still a need to consider regional and interurban sparse rail networks, specifically those networks in developing countries. In such sparse rail networks, there are limited possibilities to redirect trains if a link is disrupted, there might be less possibility of finding redundant alternative routes, and network failures are usually accompanied by a phenomenon called 'unsatisfied demand.' The study reported in this paper stemmed from research aimed to design precautionary actions for a developing country's sparse railway system. Our study framework deemed to find the most vulnerable part of an inter-urban sparse rail network using a network scan approach, which found the consequences of network disruptions. A number of criteria were defined to determine the total cost including unsatisfied demand and additional transportation costs due to disruptions. The results showed that how well the process of the vulnerability analysis, considering the features of both supply and demand sides, can be a guide for railway authorities in applying system safety measures.