Controller area network (CAN) modelling for automotive body control applications

This research details methods to improve upon current worst-case message response time analysis of CAN networks. Also, through the development of a CAN network model, and using modern simulation software, methods were shown to provide more realistic analyses of both sporadic and periodic messages on CAN networks prior to implementation.

Automotive can network response time analysis with variable jitter

Many methods to calculate message latencies for Controller Area Network (CAN) have previously been presented based upon the static worst-case behaviour of the system. With the use of modern simulation tools however, the behaviour of CAN networks can be simulated dynamically in order to find the likely worst-case response times for CAN messages. This paper shows the development of an automotive body control network model to be used as the basis for further simulations. A method to simulate the Worst-Case Response Time of this model is then presented, taking into account random queuing jitter.

Stakeholder involvement and interplay in coastal zone management and marine protected area planning

Most of Australia’s coastline and marine waters are crown ‘land’ and can be accessed by the public. As a result, many different users and stakeholder groups have an interest in coastal and marine planning and management decisions. As a way of analysing stakeholder involvement and interplay in coastal zone management and marine protected area (MPA) development in Australia, three case studies are presented to dissect the issues and explore common themes. The three themes are 1) Stakeholder involvement in implementing the oceans policy, 2) Stakeholder involvement in marine protected area network identification and 3) Stakeholder involvement in coastal land issues.

Emerging wireless personal area networks(WPANs) : - An analysis of techniques, tools and threats

Wireless Personal Area Networks provide a pivotal role in local area network technology complementing traditional Wireless Local Area Network technologies. Bluetooth, ZigBee and NFC (Near Field Communications) have emerged as key WPAN technologies with UWB (Ultra Wide Band) standards currently evolving. They are however subject to the usual range of security vulnerabilities found in wireless LANs such as spoofing, snooping, man-in-the-middle, denial of service and other attacks. However security in WPANs is not as mature as it is in Wireless LANs and further work is needed in order to provide comparable protection. This paper examines a range of WPAN technologies and security issues and proposes protection mechanisms that can mitigate risk in each case. © 2012 IEEE.

DDoS attack detection at local area networks using information theoretical metrics

DDoS attacks are one of the major threats to Internet services. Sophisticated hackers are mimicking the features of legitimate network events, such as flash crowds, to fly under the radar. This poses great challenges to detect DDoS attacks. In this paper, we propose an attack feature independent DDoS flooding attack detection method at local area networks. We employ flow entropy on local area network routers to supervise the network traffic and raise potential DDoS flooding attack alarms when the flow entropy drops significantly in a short period of time. Furthermore, information distance is employed to differentiate DDoS attacks from flash crowds. In general, the attack traffic of one DDoS flooding attack session is generated by many bots from one botnet, and all of these bots are executing the same attack program. As a result, the similarity among attack traffic should higher than that among flash crowds, which are generated by many random users. Mathematical models have been established for the proposed detection strategies. Analysis based on the models indicates that the proposed methods can raise the alarm for potential DDoS flooding attacks and can differentiate DDoS flooding attacks from flash crowds with conditions. The extensive experiments and simulations confirmed the effectiveness of our proposed detection strategies.

Hybrid controller with the combination of FLC and neural network-based IMC for nonlinear processes

This work presents a hybrid controller based on the combination of fuzzy logic control (FLC) mechanism and internal model-based control (IMC). Neural network-based inverse and forward models are developed for IMC. After designing the FLC and IMC independently, they are combined in parallel to produce a single control signal. Mean averaging mechanism is used to combine the prediction of both controllers. Finally, performance of the proposed hybrid controller is studied for a nonlinear numerical plant model (NNPM). Simulation result shows the proposed hybrid controller outperforms both FLC and IMC.

A congestion control scheme based on fuzzy logic in wireless body area networks

One of the major challenges in healthcare wireless body area network (WBAN) applications is to control congestion. Unpredictable traffic load, many-to-one communication nature and limited bandwidth occupancy are among major reasons that can cause congestion in such applications. Congestion has negative impacts on the overall network performance such as packet losses, increasing end-to-end delay and wasting energy consumption due to a large number of retransmissions. In life-critical applications, any delay in transmitting vital signals may lead to death of a patient. Therefore, in order to enhance the network quality of service (QoS), developing a solution for congestion estimation and control is imperative. In this paper, we propose a new congestion detection and control protocol for remote monitoring of patients health status using WBANs. The proposed system is able to detect congestion by considering local information such as buffer capacity and node rate. In case of congestion, the proposed system differentiates between vital signals and assigns priorities to them based on their level of importance. As a result, the proposed approach provides a better quality of service for transmitting highly important vital signs.

A self-learning system for identifying harmful network information

Network information identification is a “hot” topic currently. This paper designs a self-learning system using neural network algorithm for identifying the harmful network messages of both Chinese and English languages. The system segments the message into words and creates key word vector which characterizes the harmful network information. The BP algorithm is taken advantage of to train the neural network. The result of training and studying of the neural network can be applied onto many network applications based on message identification. The result of experiments demonstrates that our system has a high degree of accuracy.

LAN cafes: cafes, places of gathering or sites of informal teaching and learning?

Despite the interest of sociologists and educational researchers in Internet café as sites for new cultural and social formations and informal learning, thus far little attention has been paid to the function of café owners, managers and other staff in the mediation and co-construction of those spaces. Drawing from interviews with managers of commercial Internet café in Australia specialising in LAN (Local Area Network) gaming, this article seeks to examine their role and their attitudes more closely; in particular with regard to school-aged users of their facilities. We contend that LAN café are liminal spaces situated at the margins of Australian culture and located at the junctions between home, school and the street, online and offline spaces, work and play. The roles of LAN café managers are similarly ambiguous: in many ways they can be regarded as informal teachers facilitating the process of informal learning.

Study of the Geelong Local Learning and Employment Network

In common with many Western nations, Australian governments, both state and federal, have increasingly embraced network-based approaches in responding to the effects of globalisation. Since 2001, thirty one Local Learning and Employment Networks (LLEN) have been established across all areas of Victoria, Australia in line with recommendations of a Ministerial Review into Post Compulsory Education and Training Pathways. That review reported that, in the globalised context, youth in transition from schooling to independence faced persistent and severe difficulties unknown to previous generations; it also found problems were frequently concentrated in particular groups and regions. LLEN bring together the expertise and experience of local education providers, industry, community organisations, individuals and government organisations. As a result of their local decisions, collaboration and community building efforts it is intended that opportunities for young people will be enhanced. My research was conducted within an Australian Research Council Linkage Project awarded to Deakin University Faculty of Education in partnership with the Smart Geelong Region LLEN (SGR LLEN). The Linkage Project included two separate research components one of which forms my thesis: a case study of SGR LLEN. My data was generated through participant observation in SGR LLEN throughout 2004 and 2005 and through interviews, reflective writing and archival review. In undertaking my analysis and presenting my thesis I have chosen to weave a series of panels whose orientation is poststructural. This approach was based in my acceptance that all knowledge is partial and fragmentary and, accordingly, researchers need to find ways that highlight the intersections in and indeterminacy of their empirical data. The LLEN is -by its nature as a network -more than the contractual entity that gains funding from government, acts as the administrative core and occupies the LLEN office. As such I have woven firstly the formation and operational structure of the bounded entity that is SGR LLEN before weaving a series of six images that portray the unbounded LLEN as an instance-in-action. The thesis draws its theoretical inspiration from the work of Deleuze and Guattari (1987). Despite increased use of notions of networks, local decision-making and community building by governments there had been little empirical research that explored stakeholder understandings of networks and their role in community building as well as a lack of theorisation of how networks actually ‘work.’ My research addresses this lack and suggests an instituted network can function as a learning community capable of fostering systemic change in the post compulsory education training and employment sector and thereby contributing to better opportunities for young people. However the full potential of the policy is undermined by the reluctance of governments to follow through on the implications of their policies and, in particular, to confront the limiting effects of performativity at all levels.

Can we beat DDoS attacks in clouds?

Cloud is becoming a dominant computing platform. Naturally, a question that arises is whether we can beat notorious DDoS attacks in a cloud environment. Researchers have demonstrated that the essential issue of DDoS attack and defense is resource competition between defenders and attackers. A cloud usually possesses profound resources and has full control and dynamic allocation capability of its resources. Therefore, cloud offers us the potential to overcome DDoS attacks. However, individual cloud hosted servers are still vulnerable to DDoS attacks if they still run in the traditional way. In this paper, we propose a dynamic resource allocation strategy to counter DDoS attacks against individual cloud customers. When a DDoS attack occurs, we employ the idle resources of the cloud to clone sufficient intrusion prevention servers for the victim in order to quickly filter out attack packets and guarantee the quality of the service for benign users simultaneously. We establish a mathematical model to approximate the needs of our resource investment based on queueing theory. Through careful system analysis and real-world data set experiments, we conclude that we can defeat DDoS attacks in a cloud environment. © 2013 IEEE.

The microstructure and physicochemical properties of probiotic buffalo yoghurt during fermentation and storage: a comparison with bovine yoghurt

The physicochemical and rheological properties of yoghurt made from unstandardised unhomogenised buffalo milk were investigated during fermentation and 28 days of storage and compared to the properties of yoghurt made from homogenised fortified bovine milk. A number of differences observed in the gel network can be linked to differences in milk composition. The microstructure of buffalo yoghurt, as assessed by confocal laser scanning microscopy (CLSM) and cryo scanning electron microscopy (cryo-SEM), was interrupted by large fat globules and featured more serum pores. These fat globules have a lower surface area and bind less protein than the homogenised fat globules in bovine milk. These microstructural differences likely lead to the higher syneresis observed for buffalo yoghurt with an increase from 17.4 % (w/w) to 19.7 % (w/w) in the weight of whey generated at days 1 and 28 of the storage. The higher concentration of total calcium in buffalo milk resulted in the release of more ionic calcium during fermentation. Gelation was also slower but the strength of the two gels was similar due to similar protein and total solids concentrations. Buffalo yoghurt was more viscous, less able to recover from deformation and less Newtonian than bovine yoghurt with a thixotropy of 3,035 Pa.s-1 measured for buffalo yoghurt at the end of the storage, at least four times higher than the thixotropy of bovine yoghurt. While the titratable acidity, lactose consumption and changes in organic acid concentrations were similar, differences were recorded in the viability of probiotic bacteria with a lower viability of Lactobacillus acidophilus of 5.17 log (CFU/g) recorded for buffalo yoghurt at day 28 of the storage. Our results show that factors other than the total solids content and protein concentration of milk affect the structural properties of yoghurt. They also illustrate the physicochemical reasons why buffalo and bovine yoghurt are reported to have different sensory properties and provide insight into how compositional changes can be used to alter the microstructure and properties of dairy products. © 2013 Springer Science+Business Media New York.

Time-in-area represents foraging activity in a wide-ranging pelagic forager

Successful Marine Spatial Planning depends upon the identification of areas with high importance for particular species, ecosystems or processes. For seabirds, advancements in biologging devices have enabled us to identify these areas through the detailed study of at-sea behaviour. However, in many cases, only positional data are available and the presence of local biological productivity and hence seabird foraging behaviour is inferred from these data alone, under the untested assumption that foraging activity is more likely to occur in areas where seabirds spend more time. We fitted GPS devices and accelerometers to northern gannets Morus bassanus and categorised the behaviour of individuals outside the breeding colony as plunge diving, surface foraging, floating and flying. We then used the locations of foraging events to test the efficiency of 2 approaches: time-in-area and kernel density (KD) analyses, which are widely employed to detect highly-used areas and interpret foraging behaviour from positional data. For KD analyses, the smoothing parameter (h) was calculated using the ad hoc method (KDad hoc), and KDh=9.1, where h = 9.1 km, to designate core foraging areas from location data. A high proportion of foraging events occurred in core foraging areas designated using KDad hoc, KDh=9.1, and time-in-area. Our findings demonstrate that foraging activity occurs in areas where seabirds spend more time, and that both KD analysis and the time-in-area approach are equally efficient methods for this type of analysis. However, the time-in-area approach is advantageous in its simplicity, and in its ability to provide the shapes commonly used in planning. Therefore, the time-in-area approach can be used as a simple way of using seabirds to identify ecologically important locations from both tracking and survey data.

K-Center: an approach on the multi-source identification of information diffusion

The global diffusion of epidemics, computer viruses, and rumors causes great damage to our society. It is critical to identify the diffusion sources and timely quarantine them. However, most methods proposed so far are unsuitable for diffusion with multiple sources because of the high computational cost and the complex spatiotemporal diffusion processes. In this paper, based on the knowledge of infected nodes and their connections, we propose a novel method to identify multiple diffusion sources, which can address three main issues in this area: 1) how many sources are there? 2) where did the diffusion emerge? and 3) when did the diffusion break out? We first derive an optimization formulation for multi-source identification problem. This is based on altering the original network into a new network concerning two key elements: 1) propagation probability and 2) the number of hops between nodes. Experiments demonstrate that the altered network can accurately reflect the complex diffusion processes with multiple sources. Second, we derive a fast method to optimize the formulation. It has been proved that the proposed method is convergent and the computational complexity is O(mn log α) , where α = α (m,n) is the slowly growing inverse-Ackermann function, n is the number of infected nodes, and m is the number of edges connecting them. Finally, we introduce an efficient algorithm to estimate the spreading time and the number of diffusion sources. To evaluate the proposed method, we compare the proposed method with many competing methods in various real-world network topologies. Our method shows significant advantages in the estimation of multiple sources and the prediction of spreading time.

A distributed gateway selection algorithm for UAV networks

In recent years, unmanned aerial vehicle (UAV) has been widely adopted in military and civilian applications. For small UAVs, cooperation based on communication networks can effectively expand their working area. Although the UAV networks are quite similar to the traditional mobile ad hoc networks, the special characteristics of the UAV application scenario have not been considered in the literature. In this paper, we propose a distributed gateway selection algorithm with dynamic network partition by taking into account the application characteristics of UAV networks. In the proposed algorithm, the influence of the asymmetry information phenomenon on UAVs' topology control is weakened by dividing the network into several subareas. During the operation of the network, the partition of the network can be adaptively adjusted to keep the whole network topology stable even though UAVs are moving rapidly. Meanwhile, the number of gateways can be completely controlled according to the system requirements. In particular, we define the stability of UAV networks, build a network partition model, and design a distributed gateway selection algorithm. Simulation results show using our proposed scheme that the faster the nodes move in the network, the more stable topology can be found, which is quite suitable for UAV applications.