Data centre optimisation enhanced by software defined networking

Contemporary Cloud Computing infrastructures are being challenged by an increasing demand for evolved cloud services characterised by heterogeneous performance requirements including real-time, data-intensive and highly dynamic workloads. The classical way to deal with dynamicity is to scale computing and network resources horizontally. However, these techniques must be coupled effectively with advanced routing and switching in a multi-path environment, mixed with a high degree of flexibility to support dynamic adaptation and live-migration of virtual machines (VMs). We propose a management strategy to jointly optimise computing and networking resources in cloud infrastructures, where Software Defined Networking (SDN) plays a key enabling role

Data-driven agriculture for rural smallholdings

Spatial information science has a critical role to play in meeting the major challenges facing society in the coming decades, including feeding a population of 10 billion by 2050, addressing environmental degradation, and acting on climate change. Agriculture and agri-food value-chains, dependent on spatial information, are also central. Due to agriculture\u27s dual role as not only a producer of food, fibre and fuel, but also as a major land, water and energy consumer, agriculture is at the centre of both the food-water-energy-environment nexus and resource security debates. The recent confluence of a number of advances in data analytics, cloud computing, remote sensing, computer vision, robotic and drone platforms, and IoT sensors and networks have lead to a significant reduction in the cost of acquiring and processing data for decision support in the agricultural sector. When combined with cost-effective automation through development of swarm farming technologies, the technology has the potential to decouple productivity and cost efficiency from economies of size, reducing the need to increase farm size to remain economically viable. We argue that these pressures and opportunities are driving agricultural value-chains towards high-resolution data-driven decision-making, where even decisions made by small rural landowners can be data-driven. We survey recent innovations in data, especially focusing on sensor, spatial and data mining technologies with a view to their agricultural application; discuss economic feasibility for small farmers; and identify some technical challenges that need to be solved to reap the benefits. Flexibly composable information resources, coupled with sophisticated data sharing technologies, and machine learning with transparently embedded spatial and aspatial methods are all required

End-to-end service quality for cloud applications

This paper aims to highlight the importance of End-to-End (E2E) service quality for cloud scenarios, with focus on telecom carrier-grade services. In multi-tenant distributed and virtualized cloud infrastructures, enhanced resource sharing raises issues in terms of performance stability and reliability. Moreover, the heterogeneity of business entities responsible for the cloud service delivery, threatens the possibility of offering precise E2E service levels. Setting up proper Service-Level Agreements (SLAs) among the involved players, may become overly challenging. However, problems may be mitigated by a thoughtful intervention of standardization. The paper reviews some of the most important efforts in research and industry to tackle E2E service quality and concludes with some recommendations for additional research and/or standardization effort required to be able to deploy mission critical or interactive real-time services with high demands on service quality, reliability and predictability on cloud platforms. © 2013 Springer International Publishing

A survey on the cyber security of Small-to-Medium businesses: Challenges, research focus and recommendations

Small-to-medium sized businesses (SMBs) constitute a large fraction of many countries’ economies but according to the literature SMBs are not adequately implementing cyber security which leaves them susceptible to cyber-attacks. Furthermore, research in cyber security is rarely focused on SMBs, despite them representing a large proportion of businesses. In this paper we review recent research on the cyber security of SMBs, with a focus on the alignment of this research to the popular NIST Cyber Security Framework (CSF). From the literature we also summarise the key challenges SMBs face in implementing good cyber security and conclude with key recommendations on how to implement good cyber security. We find that research in SMB cyber security is mainly qualitative analysis and narrowly focused on the Identify and Protect functions of the NIST CSF with very little work on the other existing functions. SMBs should have the ability to detect, respond and recover from cyber-attacks, and if research lacks in those areas, then SMBs may have little guidance on how to act. Future research in SMB cyber security should be more balanced and researchers should adopt well-established powerful quantitative research approaches to refine and test research whilst governments and academia are urged to invest in incentivising researchers to expand their research focus

An adoption model to assess e-service technology acceptance

As the world today is witnessing the remarkable growth of information and communication technology development and the Internet popularity, the widespread use of the electronic service (e-service) is becoming inevitable. Many e-service projects have been developed but since they are not used by users, they cannot help to improve organizational performance. As the user adoption of an e-service is an essential key for a successful and an effective implementation of any e-service project, there is a need to access the user acceptance of the system. This research developed the E-Service Technology Acceptance Model (ETAM) to assess the user acceptance of an e-service technology. According to the literature review in the field of e-service technology and the acceptance theories, this research identified the main factors influencing the acceptance of e-services, namely; satisfaction and quality where the dimensions of these factors were extracted from the previous studies. In order to categorise the dimensions, an exploratory survey was developed and conducted among the university students and then, the Exploratory Factor Analysis was applied using the SPSS Software. Then, a confirmatory survey was designed and tested to test the validity (content and construct) and the reliability of the instrument, before it was used to evaluate the ETAM. The survey was conducted among the e-service users in Malaysia and 426 questionnaires were collected. Finally, the Structural Equation Modelling using Lisrel was applied to validate the casual relations between the constructs and to assess the goodness-of-fit for the ETAM. The result of this study revealed that quality, security and satisfaction significantly influenced the intention to use an e-service and consequently the acceptance of the e-service technology. The ETAM model developed in this study can be used as a foundation for e-service providers to develop strategies to encourage people to use e-service and to increase the usage and the acceptance of e-services in Malaysia. Moreover, the ETAM which explains 71.8% of variance can help to evaluate and predict how users will respond to an e-service before starting to develop an e-service project. This model can also be applied it to improve the provided e-service to increase the usage rate

Real-Time Cross-Layer Routing Protocol for Ad Hoc Wireless Sensor Networks

Reliable and energy efficient routing is a critical issue in Wireless Sensor Networks (WSNs) deployments. Many approaches have been proposed for WSN routing, but sensor field implementations, compared to computer simulations and fully-controlled testbeds, tend to be lacking in the literature and not fully documented. Typically, WSNs provide the ability to gather information cheaply, accurately and reliably over both small and vast physical regions. Unlike other large data network forms, where the ultimate input/output interface is a human being, WSNs are about collecting data from unattended physical environments. Although WSNs are being studied on a global scale, the major current research is still focusing on simulations experiments. In particular for sensor networks, which have to deal with very stringent resource limitations and that are exposed to severe physical conditions, real experiments with real applications are essential. In addition, the effectiveness of simulation studies is severely limited in terms of the difficulty in modeling the complexities of the radio environment, power consumption on sensor devices, and the interactions between the physical, network and application layers. The routing problem in ad hoc WSNs is nontrivial issue because of sensor node failures due to restricted recourses. Thus, the routing protocols of WSNs encounter two conflicting issue: on the one hand, in order to optimise routes, frequent topology updates are required, while on the other hand, frequent topology updates result in imbalanced energy dissipation and higher message overhead. In the literature, such as in (Rahul et al., 2002), (Woo et al., 2003), (TinyOS, 2004), (Gnawali et al., 2009) and (Burri et al., 2007) several authors have presented routing algorithms for WSNs that consider purely one or two metrics at most in attempting to optimise routes while attempting to keep small message overhead and balanced energy dissipation. Recent studies on energy efficient routing in multihop WSNs have shown a great reliance on radio link quality in the path selection process. If sensor nodes along the routing path and closer to the base station advertise a high quality link to forwarding upstream packets, these sensor nodes will experience a faster depletion rate in their residual energy. This results in a topological routing hole or network partitioning as stated and resolved in and (Daabaj 2010). This chapter presents an empirical study on how to improve energy efficiency for reliable multihop communication by developing a real-time cross-layer lifetime-oriented routing protocol and integrating useful routing information from different layers to examine their joint benefit on the lifetime of individual sensor nodes and the entire sensor network. The proposed approach aims to balance the workload and energy usage among relay nodes to achieve balanced energy dissipation, thereby maximizing the functional network lifetime. The obtained experimental results are presented from prototype real-network experiments based on Crossbow’s sensor motes (Crossbow, 2010), i.e., Mica2 low-power wireless sensor platforms (Crossbow, 2010). The distributed real-time routing protocol which is proposed In this chapter aims to face the dynamics of the real world sensor networks and also to discover multiple paths between the base station and source sensor nodes. The proposed routing protocol is compared experimentally with a reliability-oriented collection-tree protocol, i.e., the TinyOS MintRoute protocol (Woo et al., 2003). The experimental results show that our proposed protocol has a higher node energy efficiency, lower control overhead, and fair average delay

Automated Framework to Improve User?s Awareness and to Categorize Friends on Online Social Networks

The popularity of online social networks has brought up new privacy threats. These threats often arise after users willingly, but unwittingly reveal their information to a wider group of people than they actually intended. Moreover, the well adapted ?friends-based? privacy control has proven to be ill-equipped to prevent dynamic information disclosure, such as in user text posts. Ironically, it fails to capture the dynamic nature of this data by reducing the problem to manual privacy management which is time-consuming, tiresome and error-prone task. This dissertation identifies an important problem with posting on social networks and proposes a unique two phase approach to the problem. First, we suggest an additional layer of security be added to social networking sites. This layer includes a framework for natural language to automatically check texts to be posted by the user and detect dangerous information disclosure so it warns the user. A set of detection rules have been developed for this purpose and tested with over 16,000 Facebook posts to confirm the detection quality. The results showed that our approach has an 85% detection rate which outperforms other existing approaches. Second, we propose utilizing trust between friends as currency to access dangerous posts. The unique feature of our approach is that the trust value is related to the absence of interaction on the given topic. To approach our goal, we defined trust metrics that can be used to determine trustworthy friends in terms of the given topic. In addition, we built a tool which calculates the metrics automatically, and then generates a list of trusted friends. Our experiments show that our approach has reasonably acceptable performance in terms of predicting friends? interactions for the given posts. Finally, we performed some data analysis on a small set of user interaction records on Facebook to show that friends? interaction could be triggered by certain topics

Towards Time-Aware Context-Aware Deep Trust Prediction in Online Social Networks

Trust can be defined as a measure to determine which source of information is reliable and with whom we should share or from whom we should accept information. There are several applications for trust in Online Social Networks (OSNs), including social spammer detection, fake news detection, retweet behaviour detection and recommender systems. Trust prediction is the process of predicting a new trust relation between two users who are not currently connected. In applications of trust, trust relations among users need to be predicted. This process faces many challenges, such as the sparsity of user-specified trust relations, the context-awareness of trust and changes in trust values over time. In this dissertation, we analyse the state-of-the-art in pair-wise trust prediction models in OSNs. We discuss three main challenges in this domain and present novel trust prediction approaches to address them. We first focus on proposing a low-rank representation of users that incorporates users' personality traits as additional information. Then, we propose a set of context-aware trust prediction models. Finally, by considering the time-dependency of trust relations, we propose a dynamic deep trust prediction approach. We design and implement five pair-wise trust prediction approaches and evaluate them with real-world datasets collected from OSNs. The experimental results demonstrate the effectiveness of our approaches compared to other state-of-the-art pair-wise trust prediction models.Comment: 158 pages, 20 figures, and 19 tables. This is my PhD thesis in Macquarie University, Sydney, Australi