Now showing 1 - 10 of 10
  • Publication
    PHOEBE: an automation framework for the effective usage of diagnosis tools in the performance testing of clustered systems
    The identification of performance issues and the diagnosis of their root causes are time-consuming and complex tasks, especially in clustered environments. To simplify these tasks, researchers have been developing tools with built-in expertise for practitioners. However, various limitations exist in these tools that prevent their efficient usage in the performance testing of clusters (e.g. the need of manually analysing huge volumes of distributed results). In a previous work, we introduced a policy-based adaptive framework (PHOEBE) that automates the usage of diagnosis tools in the performance testing of clustered systems, in order to improve a tester's productivity, by decreasing the effort and expertise needed to effectively use such tools. This paper extends that work by broadening the set of policies available in PHOEBE, as well as by performing a comprehensive assessment of PHOEBE in terms of its benefits, costs and generality (with respect to the used diagnosis tool). The performed evaluation involved a set of experiments in assessing the different trade-offs commonly experienced by a tester when using a performance diagnosis tool, as well as the time savings that PHOEBE can bring to the performance testing and analysis processes. Our results have shown that PHOEBE can drastically reduce the effort required by a tester to do performance testing and analysis in a cluster. PHOEBE also exhibited consistent behaviour (i.e. similar time-savings and resource utilisations), when applied to a set of commonly used diagnosis tools, demonstrating its generality. Finally, PHOEBE proved to be capable of simplifying the configuration of a diagnosis tool. This was achieved by addressing the identified trade-offs without the need for manual intervention from the tester.
      621
  • Publication
    Dynamic Adaptation of the Traffic Management System CarDemo
    This paper demonstrates how we applied a constraint-based dynamic adaptation approach on CarDemo, a traffic management system. The approach allows domain experts to describe the adaptation goals as declarative constraints, and automatically plan the adaptation decisions to satisfy these constraints. We demonstrate how to utilise this approach to realise the dynamic switch of routing services of the traffic management system, according to the change of global system states and user requests.
      345
  • Publication
    A QoS based call admission control and resource allocation mechanism for LTE femtocell deployment
    Current trends show a growing number of femtocell deployments, this in turn will lead to increased volumes of voice traffic being transmitted through fixed broadband access networks such as Digital Subscriber Line. In this paper the issue of maintaining call quality through the resource constraint expedited forwarding queue of DSLAMs is investigated. A quality based Call Admission Control and resource allocation mechanism is provided to avoid resource overloading and call quality degradation. The ITU-T's E-Model is used for call quality monitoring and a message exchange interface between the mobile and fixed networks which allows dynamic adjustment to network resources is described and simulated. The results show that high voice call quality can be maintained.
      339Scopus© Citations 21
  • Publication
    VoIP Quality Monitoring in LTE Femtocells
    The increasing number of users demanding voice and data communication through cellular networks has driven the need for higher network throughput rates and lower latency. LTE femtocells address this pressing problem by offloading cellular service providers networks and increase both coverage and capacity for their users. Assuming a wired DSL backhaul for these femtocells, this paper shows simulations exploring a case where the DSLAM represents the main bottleneck when the cellular network operator and the DSL provider do not collaborate. This paper introduces the concept of Intermediary Mean Opinion Score which may be employed at femtocell gateways to isolate network problems and feed into customer experience management. We also propose and investigate a technique of mapping the human audio recency into the MOS calculation. Results are presented to illustrate the information that can be extracted from a lightweight monitor in the network.
      354Scopus© Citations 12
  • Publication
    In-Test Adaptation of Workload in Enterprise Application Performance Testing
    Performance testing is used to assess if an enterprise application can fulfil its expected Service Level Agreements. However, since some performance issues depend on the input workloads, it is common to use time-consuming and complex iterative test methods, which heavily rely on human expertise. This paper presents an automated approach to dynamically adapt the workload so that issues (e.g. bottlenecks) can be identified more quickly as well as with less effort and expertise. We present promising results from an initial validation prototype indicating an 18-fold decrease in the test time without compromising the accuracy of the test results, while only introducing a marginal overhead in the system.
      360Scopus© Citations 5
  • Publication
    Multi-Layer-Mesh: A Novel Topology and SDN-based Path Switching for Big Data Cluster Networks
    Big Data technologies and tools have being used for the past decade to solve several scientific and industry problems, with Hadoop/YARN becoming the ”de facto” standard for these applications, although other technologies run on top of it. As any other distributed application, those big data technologies rely heavily on the network infrastructure to read and move data from hundreds or thousands of cluster nodes. Although these technologies are based on reliable and efficient distributed algorithms, there are scenarios and conditions that can generate bottlenecks and inefficiencies, i.e., when a high number of concurrent users creates data access contention. In this paper, we propose a novel network topology called MultiLayer-Mesh and a path switching algorithm based on SDN, that can increase the performance of a big data cluster while reducing the amount of utilized resources (network equipment), in turn reducing the energy and cooling consumption. A thorough simulation-based evaluation of our algorithms shows an average improvement in performance of 31.77% and an average decrease in resource utilization of 36.03% compared to a traditional SpineLeaf topology, in the selected test scenarios.
      349Scopus© Citations 2
  • Publication
    Impact of non-deterministic software execution times in SmartGrid applications
    Electricity companies will only allow customers to inject power into the grid network if the customer’s system is in synch with both frequency and phase as the grid itself. This is normally achieved using a specialised machine sold by the energy provider. It may be possible to achieve this via low cost, low power nodes such as a Raspberry Pi, to synchronize frequency and phase as well as voltage and current. In order to synchronize to microsecond or nanosecond precision, the hardware being deployed must in itself be able to achieve said precision when coupled with software. In this paper we evaluate the level of nondeterministic execution times in two versions of a widespread embedded compute platform, namely Raspberry Pi.
      266Scopus© Citations 1
  • Publication
    TRINI: an adaptive load balancing strategy based on garbage collection for clustered Java systems
    Nowadays, clustered environments are commonly used in high-performance computing and enterprise-level applications to achieve faster response time and higher throughput than single machine environments. Nevertheless, how to effectively manage the workloads in these clusters has become a new challenge. As a load balancer is typically used to distribute the workload among the cluster's nodes, multiple research efforts have concentrated on enhancing the capabilities of load balancers. Our previous work presented a novel adaptive load balancing strategy (TRINI) that improves the performance of a clustered Java system by avoiding the performance impacts of major garbage collection, which is an important cause of performance degradation in Java. The aim of this paper is to strengthen the validation of TRINI by extending its experimental evaluation in terms of generality, scalability and reliability. Our results have shown that TRINI can achieve significant performance improvements, as well as a consistent behaviour, when it is applied to a set of commonly used load balancing algorithms, demonstrating its generality. TRINI also proved to be scalable across different cluster sizes, as its performance improvements did not noticeably degrade when increasing the cluster size. Finally, TRINI exhibited reliable behaviour over extended time periods, introducing only a small overhead to the cluster in such conditions. These results offer practitioners a valuable reference regarding the benefits that a load balancing strategy, based on garbage collection, can bring to a clustered Java system.
      367Scopus© Citations 11
  • Publication
    Towards an emulated IoT test environment for anomaly detection using NEMU
    The advent of the Internet of Things (IoT) has led to a major change in the way we interact with increasingly ubiquitous connected devices such as smart objects and cyber-physical systems. It has also led to an exponential increase in the number of such Internet-connected devices over the last few years. Conducting extensive functional and performance testing is critical to assess the robustness and efficiency of IoT systems in order to validate them before their deployment in real life. However, creating an IoT test environment is a difficult and expensive task, usually requiring a significant amount of physical hardware and human effort to build it. This paper proposes a method to emulate an IoT environment using the Network Emulator for Mobile Universes (NEMU), itself built on the popular QEMU system emulator, in order to construct a testbed of inter-connected, emulated Raspberry Pi devices. Additionally, we experimentally demonstrate how our method can be successfully applied to IoT by showing how such an emulated environment can be used to detect anomalies in an IoT system.
      474
  • Publication
    Load balancing of Java applications by forecasting garbage collections
    Modern computer applications, especially at enterprise-level, are commonly deployed with a big number of clustered instances to achieve a higher system performance, in which case single machine based solutions are less cost-effective. However, how to effectively manage these clustered applications has become a new challenge. A common approach is to deploy a front-end load balancer to optimise the workload distribution between each clustered application. Since then, many research efforts have been carried out to study effective load balancing algorithms which can control the workload based on various resource usages such as CPU and memory. The aim of this paper is to propose a new load balancing approach to improve the overall distributed system performance by avoiding potential performance impacts caused by Major Java Garbage Collection. The experimental results have shown that the proposed load balancing algorithm can achieve a significant higher throughput and lower response time compared to the round-robin approach. In addition, the proposed solution only has a small overhead introduced to the distributed system, where unused resources are available to enable other load balancing algorithms together to achieve a better system performance.
      308Scopus© Citations 6