Distributed aop middleware for large-scale scenarios

En aquesta tesi doctoral presentem una proposta de middleware distribuït pel desenvolupament d'aplicacions de gran escala. La nostra motivació principal és permetre que les responsabilitats distribuïdes d'aquestes aplicacions, com per exemple la replicació, puguin integrar-se de forma transparent i independent. El nostre enfoc es basa en la implementació d'aquestes responsabilitats mitjançant el paradigma d'aspectes distribuïts i es beneficia dels substrats de les xarxes peer-to-peer (P2P) i de la programació orientada a aspectes (AOP) per realitzar-ho de forma descentralitzada, desacoblada, eficient i transparent. La nostra arquitectura middleware es divideix en dues capes: un model de composició i una plataforma escalable de desplegament d'aspectes distribuïts. Per últim, es demostra la viabilitat i aplicabilitat del nostre model mitjançant la implementació i experimentació de prototipus en xarxes de gran escala reals.In this PhD dissertation we present a distributed middleware proposal for large-scale application development. Our main aim is to separate the distributed concerns of these applications, like replication, which can be integrated independently and transparently. Our approach is based on the implementation of these concerns using the paradigm of distributed aspects. In addition, our proposal benefits from the peer-to-peer (P2P) networks and aspect-oriented programming (AOP) substrates to provide these concerns in a decentralized, decoupled, efficient, and transparent way. Our middleware architecture is divided into two layers: a composition model and a scalable deployment platform for distributed aspects. Finally, we demonstrate the viability and applicability of our model via implementation and experimentation of prototypes in real large-scale networks

Proactive Interference-aware Resource Management in Deep Learning Training Cluster

Deep Learning (DL) applications are growing at an unprecedented rate across many domains, ranging from weather prediction, map navigation to medical imaging. However, training these deep learning models in large-scale compute clusters face substantial challenges in terms of low cluster resource utilisation and high job waiting time. State-of-the-art DL cluster resource managers are needed to increase GPU utilisation and maximise throughput. While co-locating DL jobs within the same GPU has been shown to be an effective means towards achieving this, co-location subsequently incurs performance interference resulting in job slowdown. We argue that effective workload placement can minimise DL cluster interference at scheduling runtime by understanding the DL workload characteristics and their respective hardware resource consumption. However, existing DL cluster resource managers reserve isolated GPUs to perform online profiling to directly measure GPU utilisation and kernel patterns for each unique submitted job. Such a feedback-based reactive approach results in additional waiting times as well as reduced cluster resource efficiency and availability. In this thesis, we propose Horus: an interference-aware and prediction-based DL cluster resource manager. Through empirically studying a series of microbenchmarks and DL workload co-location combinations across heterogeneous GPU hardware, we demonstrate the negative effects of performance interference when colocating DL workload, and identify GPU utilisation as a general proxy metric to determine good placement decisions. From these findings, we design Horus, which in contrast to existing approaches, proactively predicts GPU utilisation of heterogeneous DL workload extrapolated from the DL model computation graph features when performing placement decisions, removing the need for online profiling and isolated reserved GPUs. By conducting empirical experimentation within a medium-scale DL cluster as well as a large-scale trace-driven simulation of a production system, we demonstrate Horus improves cluster GPU utilisation, reduces cluster makespan and waiting time, and can scale to operate within hundreds of machines

RICIS Software Engineering 90 Symposium: Aerospace Applications and Research Directions Proceedings Appendices

Papers presented at RICIS Software Engineering Symposium are compiled. The following subject areas are covered: flight critical software; management of real-time Ada; software reuse; megaprogramming software; Ada net; POSIX and Ada integration in the Space Station Freedom Program; and assessment of formal methods for trustworthy computer systems

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

A decentralised semantic architecture for social networking platforms

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonSocial networking platforms (SNPs) are complex distributed software applications exhibiting many challenges related to data portability. Since existing platforms are propriety in design, users cannot easily share their data with other SNPs, however decentralisation of social networking platforms can provide a solution to this problem. There is a difference of opinion, the way the research and developer communities have pursued this issue. Existing approaches used in decentralisation provide limited structural detail and lack in providing a systematic framework of design activities. There is a need for an architectural framework based on standardised software architectural principles and technologies to guide the design and development of decentralised social networking platforms in order to improve the level of both data portability and interoperability. The main aim of this research is to develop an architectural solution to achieve data portability among SNPs via decentralisation. Existing proposed decentralised platforms are based on a distributed structure and are mainly for a specific aspect such as access control or security and privacy. In addition to this, existing approaches lack in practicality due to underdeveloped and non-standardised design. To solve these issues a new architectural framework is needed, which can provide design and development guidelines for the decentralised social networking platform. The goal of this thesis is to study, design and develop an architectural framework for social networking platforms that can incorporate the requirements of the decentralisation, to make portability possible. The synergies between the software engineering principles and social web technologies are investigated to create a standard approach. The proposed architecture is based on component-based software development (CBSD) and aspect-oriented software development (AOSD), a unified approach known as CAM (Component Aspect Model). The foundations of the proposed architecture are based on decentralised social networking architecture (DSNA), architectural style which is derived from CAM. Components and aspects are the building blocks of the proposed decentralised social networking platform architecture. From a development perspective, each component represents a social network functionality and aspects represent the properties and preferences that are used to decentralise the functionality. The model for the component composition is a major challenge because the use of CAM for social networks has not been attempted before. The proposed architecture comprehensively integrates the DSNA architectural style into each architectural component. Portability among SNPs by means of decentralisation can be summarised into three steps. (1) Definition of the architectural style, (2) implementation of the architectural style into components and (3) integration of the component composition. To date component composition approaches have not been used for social networks as a way to develop social network functionality. The concept of middleware has been adapted to achieve the composition feature of the architecture. In the architecture Social Network Support Layer (SNSL) functions as middleware to facilitate component composition. Existing middleware solutions still lack integration of CBSD and AOSD concepts. This limitation is characterised by, a lack of explicit guidelines for composition, a lack of declarative specification and definition model to express component composition and a lack of support for role allocation. This research overcome these limitations. The application of the architecture is based on the W3C SWAT (Social Web Acid Test) scenario. A Messaging application is developed to evaluate the scenario based on the Design Science Research Methodology. The architectural style is defined in the first stage of design followed by the component-based architecture. The architectural style is defined to guide the architecture and the component composition model. In the second stage, the design and implementation of composition technology (that is SNSL) are developed with architectural style and the rules defined in the first stage. The refined version of the architecture is evaluated in the third stage, according to WC3 SWAT test. The definitive version of the proposed architecture with the benchmarked result can be used to design and build social networking platforms, allowing users to share and collaborate information across the different social networking platforms

Doctor of Philosophy

dissertationWe propose a collective approach for harnessing the idle resources (cpu, storage, and bandwidth) of nodes (e.g., home desktops) distributed across the Internet. Instead of a purely peer-to-peer (P2P) approach, we organize participating nodes to act collectively using collective managers (CMs). Participating nodes provide idle resources to CMs, which unify these resources to run meaningful distributed services for external clients. We do not assume altruistic users or employ a barter-based incentive model; instead, participating nodes provide resources to CMs for long durations and are compensated in proportion to their contribution. In this dissertation we discuss the challenges faced by collective systems, present a design that addresses these challenges, and study the effect of selfish nodes. We believe that the collective service model is a useful alternative to the dominant pure P2P and centralized work queue models. It provides more effective utilization of idle resources, has a more meaningful economic model, and is better suited for building legal and commercial distributed services. We demonstrate the value of our work by building two distributed services using the collective approach. These services are a collective content distribution service and a collective data backup service

Software test and evaluation study phase I and II : survey and analysis

Issued as Final report, Project no. G-36-661 (continues G-36-636; includes A-2568