Compiler-driven data layout transformations for network applications

This work approaches the little studied topic of compiler optimisations directed to network applications. It starts by investigating if there exist any fundamental differences between application domains that justify the development and tuning of domain-specific compiler optimisations. It shows an automated approach that is capable of identifying domain-specific workload characterisations and presenting them in a readily interpretable format based on decision trees. The generated workload profiles summarise key resource utilisation issues and enable compiler engineers to address the highlighted bottlenecks. By applying this methodology to data intensive network infrastructure application it shows that data organisation is the key obstacle to overcome in order to achieve high performance. It therefore proposes and evaluates three specialised data transformations (structure splitting, array regrouping, and software caching) against the industrial EEMBC networking benchmarks and real-world data sets. It also demonstrates on one hand that speedups of up to 2.62 can be achieved, but on the other that no single solution performs equally well across different network traffic scenarios. Hence, to address this issue, an adaptive software caching scheme for high frequency route lookup operations is introduced and its effectiveness evaluated one more time against EEMBC networking benchmarks and real-world data sets achieving speedups of up to 3.30 and 2.27. The results clearly demonstrate that adaptive data organisation schemes are necessary to ensure optimal performance under varying network loads. Finally this research addresses another issue introduced by data transformations such as array regrouping and software caching, i.e. the need for static analysis to allow efficient resource allocation. This thesis proposes a static code analyser that allows the automatic resource analysis of source code containing lists and tree structures. The tool applies a combination of amortised analysis and separation logic methodology to real code and is able to evaluate type and resource usage of existing data structures, which can be used to compute global resource consumption values for full data intensive network applications

Stix: a goal-oriented distributed management system for large-scale broadband wireless access networks

Stix is a platform managing emerging large-scale broadband wireless access (BWA) networks. It has been developed to make it easy to manage such networks for community deployments and wireless Internet service providers while keeping the network management infrastructure scalable and flexible. Stix is based on the notions of goal-oriented and in-network management. With Stix, administrators graphically specify network management activities as workflows, which are deployed at a distributed set of agents within the network that cooperate in executing those workflows and storing management information. We implement the Stix system on embedded boards and show that the implementation has a low memory footprint. Using real topology and logging data from a large-scale BWA network operator, we show that Stix is significantly more scalable (via reduction in management traffic) compared to the commonly employed centralized management approach. Finally we use two case studies to demonstrate the ease with which Stix platform can be used for carrying out network reconfiguration and performance management tasks, thereby also showing its potential as a flexible platform to realize self-management mechanisms

Safety-critical Java for embedded systems

This paper presents the motivation for and outcomes of an engineering research project on certifiable Java for embedded systems. The project supports the upcoming standard for safety-critical Java, which defines a subset of Java and libraries aiming for development of high criticality systems. The outcome of this project include prototype safety-critical Java implementations, a time-predictable Java processor, analysis tools for memory safety, and example applications to explore the usability of safety-critical Java for this application area. The text summarizes developments and key contributions and concludes with the lessons learned

Compiler-driven data layout transformations for network applications

This work approaches the little studied topic of compiler optimisations directed to network applications. It starts by investigating if there exist any fundamental differences between application domains that justify the development and tuning of domain-specific compiler optimisations. It shows an automated approach that is capable of identifying domain-specific workload characterisations and presenting them in a readily interpretable format based on decision trees. The generated workload profiles summarise key resource utilisation issues and enable compiler engineers to address the highlighted bottlenecks. By applying this methodology to data intensive network infrastructure application it shows that data organisation is the key obstacle to overcome in order to achieve high performance. It therefore proposes and evaluates three specialised data transformations (structure splitting, array regrouping, and software caching) against the industrial EEMBC networking benchmarks and real-world data sets. It also demonstrates on one hand that speedups of up to 2.62 can be achieved, but on the other that no single solution performs equally well across different network traffic scenarios. Hence, to address this issue, an adaptive software caching scheme for high frequency route lookup operations is introduced and its effectiveness evaluated one more time against EEMBC networking benchmarks and real-world data sets achieving speedups of up to 3.30 and 2.27. The results clearly demonstrate that adaptive data organisation schemes are necessary to ensure optimal performance under varying network loads. Finally this research addresses another issue introduced by data transformations such as array regrouping and software caching, i.e. the need for static analysis to allow efficient resource allocation. This thesis proposes a static code analyser that allows the automatic resource analysis of source code containing lists and tree structures. The tool applies a combination of amortised analysis and separation logic methodology to real code and is able to evaluate type and resource usage of existing data structures, which can be used to compute global resource consumption values for full data intensive network applications.EThOS - Electronic Theses Online ServiceGBUnited Kingdo