Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges

Architecting integrated internet of things systems

IoT (Internet of Things) enables anytime and anyplace connectivity for anything by linking the objects of the real world with the virtual world. In the near future, it is predicted that more than 50 billion of things will be connected to the internet. This will lead to many different IoT- based systems that will have a huge impact on the society. Often, these IoT systems will not be standalone but will be composed with other different systems to create additional value. Hence, with the heterogeneity and the integration of IoT-based systems with other IoT-based or non-IoT-based systems has become an important challenge. In this thesis, the main objective is to analyze, design and integrate IoT-based systems and to answer the following research questions: RQ1. What are the characteristic features of IoT systems? RQ2. How to design the architecture for an IoT-based system? RQ3. What are the identified obstacles of the data distribution (DDS) middleware? RQ4. What are the solution directions for the identified obstacles of DDS? RQ5. What are the approaches for integrating multiple IoT-based systems? RQ6. How to design a DDS-based IoT system? RQ7. How to derive feasible deployment alternatives for DDS-based systems? In order to answer these research questions, three different research methodologies were used: Systematic Literature Review, Design Science Research, and Case Study Research. In chapter 2, we have applied a feature driven domain analysis of IoT systems. We have presented the reference architecture for IoT and discussed the corresponding layers. Among these layers, we have focused on the session layer of the IoT. The protocols in this layer are related with the communication sessions of the IoT systems and hence determine the communication characteristics of the IoT systems. We have presented the common and variant features of the most commonly used session layer protocols, namely AMQP, CoAP, DDS, MQTT, and XMPP which are used for communication between M2M (machine-to- machine), M2S (machine-to-server), and S2S (server-to-server). Further, we have provided an evaluation framework to compare session layer communication protocols. Among these protocols, we focused on the DDS that is mainly used for M2M communication in Industrial Internet of Things (IIoT). In chapter 3, we have described an architecture design method for architecting IoT systems for the Farm Management Information Systems (FMIS) domain. Hereby, we have also developed a family feature diagram to represent the common and variant features of IoT- based FMIS. In order to illustrate our approach, we have performed a systematic case study approach including the IoT-based wheat and tomato production with IoT-based FMIS. The case study research showed that the approach was both effective and practical. In chapter 4, we have presented the method for designing integrated IoT systems. We showed that integration of IoT-based systems can be at different layers including session layer, cloud layer and application layer. Further we have shown that the integration is typically carried out based on well-defined patterns, that is, generic solutions structures for recurring problems. We have systematically compiled and structured the 15 different integration patterns which can be used in different combinations and likewise supporting the composition of different IoT systems. We have illustrated the use of example patterns in a smart city case study and have shown that the systematic structuring of the integration patterns is useful for integrating IoT systems. A systematic research methodology has been applied in chapter 5 to identify the current obstacles to adopt DDS and their solution directions. We have selected 34 primary studies among the 468 identified papers since the introduction of DDS in 2003. We identified 11 basic categories of problems including complexity of DDS configuration, performance prediction, measurement and optimization, implementing DDS, DDS integration over WAN, DDS using wireless networks and mobile computing, interoperability among DDS vendor implementations, data consistency in DDS, reliability in DDS, scalability in DDS, security, and integration with event-based systems. We have adopted feature diagrams to summarize and provide an overview of the identified problem and their solutions defined in the primary studies. DDS based architecture design for IoT systems is presented in chapter 6. DDS is considered to be a potential middleware for IoT because of its focus on event-driven communication in which quality of service is also explicitly defined. We provide a systematic approach to model the architecture for DDS-based IoT in which we adopted architecture viewpoints for modeling DDS, IoT and DDS-based IoT systems. We have integrated and represented the architecture models that can be used to model DDS-based IoT systems for various application domains. When designing DDS-based systems typically multiple different alternatives can be derived. Chapter 7 presents an approach for deriving feasible DDS configuration alternatives. For this we have provided a systematic approach for extending the DDS UML profile and developed an extensible tool framework Deploy-DDS to derive feasible deployment alternatives given the application model, the physical resources, and the execution configurations. The tool framework Deploy-DDS implements a set of predefined algorithms and can be easily extended with new algorithms to support the system architect. We have evaluated the approach and the tool framework for a relevant IoT case study on smart city engineering. Chapter 8 concludes the thesis by summarizing the contributions.</p

A Scalable Blocking Framework for Multidatabase Privacy-preserving Record Linkage

Today many application domains, such as national statistics, healthcare, business analytic, fraud detection, and national security, require data to be integrated from multiple databases. Record linkage (RL) is a process used in data integration which links multiple databases to identify matching records that belong to the same entity. RL enriches the usefulness of data by removing duplicates, errors, and inconsistencies which improves the effectiveness of decision making in data analytic applications. Often, organisations are not willing or authorised to share the sensitive information in their databases with any other party due to privacy and confidentiality regulations. The linkage of databases of different organisations is an emerging research area known as privacy-preserving record linkage (PPRL). PPRL facilitates the linkage of databases by ensuring the privacy of the entities in these databases. In multidatabase (MD) context, PPRL is significantly challenged by the intrinsic exponential growth in the number of potential record pair comparisons. Such linkage often requires significant time and computational resources to produce the resulting matching sets of records. Due to increased risk of collusion, preserving the privacy of the data is more problematic with an increase of number of parties involved in the linkage process. Blocking is commonly used to scale the linkage of large databases. The aim of blocking is to remove those record pairs that correspond to non-matches (refer to different entities). Many techniques have been proposed for RL and PPRL for blocking two databases. However, many of these techniques are not suitable for blocking multiple databases. This creates a need to develop blocking technique for the multidatabase linkage context as real-world applications increasingly require more than two databases. This thesis is the first to conduct extensive research on blocking for multidatabase privacy-preserved record linkage (MD-PPRL). We consider several research problems in blocking of MD-PPRL. First, we start with a broad background literature on PPRL. This allow us to identify the main research gaps that need to be investigated in MD-PPRL. Second, we introduce a blocking framework for MD-PPRL which provides more flexibility and control to database owners in the block generation process. Third, we propose different techniques that are used in our framework for (1) blocking of multiple databases, (2) identifying blocks that need to be compared across subgroups of these databases, and (3) filtering redundant record pair comparisons by the efficient scheduling of block comparisons to improve the scalability of MD-PPRL. Each of these techniques covers an important aspect of blocking in real-world MD-PPRL applications. Finally, this thesis reports on an extensive evaluation of the combined application of these methods with real datasets, which illustrates that they outperform existing approaches in term of scalability, accuracy, and privacy

Observing the clouds : a survey and taxonomy of cloud monitoring

This research was supported by a Royal Society Industry Fellowship and an Amazon Web Services (AWS) grant. Date of Acceptance: 10/12/2014Monitoring is an important aspect of designing and maintaining large-scale systems. Cloud computing presents a unique set of challenges to monitoring including: on-demand infrastructure, unprecedented scalability, rapid elasticity and performance uncertainty. There are a wide range of monitoring tools originating from cluster and high-performance computing, grid computing and enterprise computing, as well as a series of newer bespoke tools, which have been designed exclusively for cloud monitoring. These tools express a number of common elements and designs, which address the demands of cloud monitoring to various degrees. This paper performs an exhaustive survey of contemporary monitoring tools from which we derive a taxonomy, which examines how effectively existing tools and designs meet the challenges of cloud monitoring. We conclude by examining the socio-technical aspects of monitoring, and investigate the engineering challenges and practices behind implementing monitoring strategies for cloud computing.Publisher PDFPeer reviewe

A Paradigm for Scalable, Transactional, and Efficient Spatial Indexes

With large volumes of geo-tagged data collected in various applications, spatial query pro- cessing becomes essential. Query engines depend on efficient indexes to expedite processing. There are three main challenges: scaling out to accommodate large volumes of spatial data, support- ing transactional primitives for strong consistency guarantees, and adapting to highly dynamic workloads. This thesis proposes a paradigm for scalable, transactional, and efficient spatial indexes to significantly reduce development efforts in designing and comparing multiple spatial indexes.This thesis first introduces a distributed and transactional key value store called DTranx to persist the spatial indexes. DTranx follows the SEDA architecture to exploit high concurrency in multi-core environments and it adopts a hybrid of optimistic concurrency control and two-phase commit protocols to narrow down the critical sections of distributed locking during transaction com- mits. Moreover, DTranx integrates a persistent memory based write-ahead log to reduce durability overhead and combines a garbage collection mechanism without affecting normal transactions. To maintain high throughput for search workloads when databases are constantly updated, snapshot transactions are introduced.Then, a paradigm is presented with a set of intuitive APIs and a Mempool runtime to re- duce development efforts. Mempool transparently synchronizes local states of data structures with DTranx and it handles two critical tasks: address translation and transparent server synchroniza- tion, of which the latter includes transaction construction and data synchronization. Furthermore, a dynamic partitioning strategy is integrated into DTranx to generate partitioning and replication plans that reduce inter-server communications and balance resource usage.Lastly, single-threaded data structures BTree and RTree are converted into distributed versions within two weeks. The BTree and RTree achieve 253.07 kops/sec and 77.83 kops/sec through- put respectively for pure search operations in a 25-server cluster

Mitigating Botnet-based DDoS Attacks against Web Servers

Distributed denial-of-service (DDoS) attacks have become wide-spread on the Internet. They continuously target retail merchants, financial companies and government institutions, disrupting the availability of their online resources and causing millions of dollars of financial losses. Software vulnerabilities and proliferation of malware have helped create a class of application-level DDoS attacks using networks of compromised hosts (botnets). In a botnet-based DDoS attack, an attacker orders large numbers of bots to send seemingly regular HTTP and HTTPS requests to a web server, so as to deplete the server's CPU, disk, or memory capacity. Researchers have proposed client authentication mechanisms, such as CAPTCHA puzzles, to distinguish bot traffic from legitimate client activity and discard bot-originated packets. However, CAPTCHA authentication is vulnerable to denial-of-service and artificial intelligence attacks. This dissertation proposes that clients instead use hardware tokens to authenticate in a federated authentication environment. The federated authentication solution must resist both man-in-the-middle and denial-of-service attacks. The proposed system architecture uses the Kerberos protocol to satisfy both requirements. This work proposes novel extensions to Kerberos to make it more suitable for generic web authentication. A server could verify client credentials and blacklist repeated offenders. Traffic from blacklisted clients, however, still traverses the server's network stack and consumes server resources. This work proposes Sentinel, a dedicated front-end network device that intercepts server-bound traffic, verifies authentication credentials and filters blacklisted traffic before it reaches the server. Using a front-end device also allows transparently deploying hardware acceleration using network co-processors. Network co-processors can discard blacklisted traffic at the hardware level before it wastes front-end host resources. We implement the proposed system architecture by integrating existing software applications and libraries. We validate the system implementation by evaluating its performance under DDoS attacks consisting of floods of HTTP and HTTPS requests

Record Linkage Techniques: Exploring and developing data matching methods to create national record linkage infrastructure to support population level research

In a world where the growth in digital information and systems continues to expand, researchers have access to unprecedented amounts of data. These large and complex data reservoirs require creative, innovative and scalable tools to unlock the potential of this ‘big data’. Record linkage is a powerful tool in the ‘big data’ arsenal. This thesis demonstrates the value of national record linkage infrastructure and how this has been achieved for the Australian research community

Efficient query processing for scalable web search

Search engines are exceptionally important tools for accessing information in today’s world. In satisfying the information needs of millions of users, the effectiveness (the quality of the search results) and the efficiency (the speed at which the results are returned to the users) of a search engine are two goals that form a natural trade-off, as techniques that improve the effectiveness of the search engine can also make it less efficient. Meanwhile, search engines continue to rapidly evolve, with larger indexes, more complex retrieval strategies and growing query volumes. Hence, there is a need for the development of efficient query processing infrastructures that make appropriate sacrifices in effectiveness in order to make gains in efficiency. This survey comprehensively reviews the foundations of search engines, from index layouts to basic term-at-a-time (TAAT) and document-at-a-time (DAAT) query processing strategies, while also providing the latest trends in the literature in efficient query processing, including the coherent and systematic reviews of techniques such as dynamic pruning and impact-sorted posting lists as well as their variants and optimisations. Our explanations of query processing strategies, for instance the WAND and BMW dynamic pruning algorithms, are presented with illustrative figures showing how the processing state changes as the algorithms progress. Moreover, acknowledging the recent trends in applying a cascading infrastructure within search systems, this survey describes techniques for efficiently integrating effective learned models, such as those obtained from learning-to-rank techniques. The survey also covers the selective application of query processing techniques, often achieved by predicting the response times of the search engine (known as query efficiency prediction), and making per-query tradeoffs between efficiency and effectiveness to ensure that the required retrieval speed targets can be met. Finally, the survey concludes with a summary of open directions in efficient search infrastructures, namely the use of signatures, real-time, energy-efficient and modern hardware and software architectures