4,997 research outputs found
On the influence of topological characteristics on robustness of complex networks
In this paper, we explore the relationship between the topological
characteristics of a complex network and its robustness to sustained targeted
attacks. Using synthesised scale-free, small-world and random networks, we look
at a number of network measures, including assortativity, modularity, average
path length, clustering coefficient, rich club profiles and scale-free exponent
(where applicable) of a network, and how each of these influence the robustness
of a network under targeted attacks. We use an established robustness
coefficient to measure topological robustness, and consider sustained targeted
attacks by order of node degree. With respect to scale-free networks, we show
that assortativity, modularity and average path length have a positive
correlation with network robustness, whereas clustering coefficient has a
negative correlation. We did not find any correlation between scale-free
exponent and robustness, or rich-club profiles and robustness. The robustness
of small-world networks on the other hand, show substantial positive
correlations with assortativity, modularity, clustering coefficient and average
path length. In comparison, the robustness of Erdos-Renyi random networks did
not have any significant correlation with any of the network properties
considered. A significant observation is that high clustering decreases
topological robustness in scale-free networks, yet it increases topological
robustness in small-world networks. Our results highlight the importance of
topological characteristics in influencing network robustness, and illustrate
design strategies network designers can use to increase the robustness of
scale-free and small-world networks under sustained targeted attacks
On a Catalogue of Metrics for Evaluating Commercial Cloud Services
Given the continually increasing amount of commercial Cloud services in the
market, evaluation of different services plays a significant role in
cost-benefit analysis or decision making for choosing Cloud Computing. In
particular, employing suitable metrics is essential in evaluation
implementations. However, to the best of our knowledge, there is not any
systematic discussion about metrics for evaluating Cloud services. By using the
method of Systematic Literature Review (SLR), we have collected the de facto
metrics adopted in the existing Cloud services evaluation work. The collected
metrics were arranged following different Cloud service features to be
evaluated, which essentially constructed an evaluation metrics catalogue, as
shown in this paper. This metrics catalogue can be used to facilitate the
future practice and research in the area of Cloud services evaluation.
Moreover, considering metrics selection is a prerequisite of benchmark
selection in evaluation implementations, this work also supplements the
existing research in benchmarking the commercial Cloud services.Comment: 10 pages, Proceedings of the 13th ACM/IEEE International Conference
on Grid Computing (Grid 2012), pp. 164-173, Beijing, China, September 20-23,
201
Towards a Taxonomy of Performance Evaluation of Commercial Cloud Services
Cloud Computing, as one of the most promising computing paradigms, has become
increasingly accepted in industry. Numerous commercial providers have started
to supply public Cloud services, and corresponding performance evaluation is
then inevitably required for Cloud provider selection or cost-benefit analysis.
Unfortunately, inaccurate and confusing evaluation implementations can be often
seen in the context of commercial Cloud Computing, which could severely
interfere and spoil evaluation-related comprehension and communication. This
paper introduces a taxonomy to help profile and standardize the details of
performance evaluation of commercial Cloud services. Through a systematic
literature review, we constructed the taxonomy along two dimensions by
arranging the atomic elements of Cloud-related performance evaluation. As such,
this proposed taxonomy can be employed both to analyze existing evaluation
practices through decomposition into elements and to design new experiments
through composing elements for evaluating performance of commercial Cloud
services. Moreover, through smooth expansion, we can continually adapt this
taxonomy to the more general area of evaluation of Cloud Computing.Comment: 8 pages, Proceedings of the 5th International Conference on Cloud
Computing (IEEE CLOUD 2012), pp. 344-351, Honolulu, Hawaii, USA, June 24-29,
201
Automatic Segmentation of Spontaneous Data using Dimensional Labels from Multiple Coders
This paper focuses on automatic segmentation of spontaneous data using continuous dimensional labels from multiple coders. It introduces efficient algorithms to the aim of (i) producing ground-truth by maximizing inter-coder agreement, (ii) eliciting the frames or samples that capture the transition to and from an emotional state, and (iii) automatic segmentation of spontaneous audio-visual data to be used by machine learning techniques that cannot handle unsegmented sequences. As a proof of concept, the algorithms introduced are tested using data annotated in arousal and valence space. However, they can be straightforwardly applied to data annotated in other continuous emotional spaces, such as power and expectation
A systemic review of the cybersecurity challenges in Australian water infrastructure management
Cybersecurity risks have become obstinate problems for critical water infrastructure management in Australia and worldwide. Water management in Australia involves a vast complex of smart technical control systems interconnected with several networks, making the infrastructure susceptible to cyber-attacks. Therefore, ensuring the use of security mechanisms in the control system modules and communication networks for sensors and actuators is vital. The statistics show that Australia is facing frequent cyber-attacks, most of which are either undetected or overlooked or require immediate response. To address these cyber risks, Australia has changed from a country with negligible recognition of attacks on critical infrastructure to a country with improved capability to manage cyber warfare. However, little attention is paid to reducing the risk of attacks to the critical water infrastructure. This study aims to evaluate Australia’s current cybersecurity attack landscape and the implemented controls for water infrastructure using a systematic literature review (SLR). This study also compares Australia in the context of global developments and proposes future research directions. The synthesis of the evidence from 271 studies in this review indicates the importance of managing security vulnerabilities and threats in SCADA water control systems, including the need to upgrade the contemporary water security architecture to mitigate emerging risks. Moreover, human resource development with a specific focus on security awareness and training for SCADA employees is found to be lacking, which will be essential for alleviating cyber threats to the water infrastructure in Australia
- …