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- PublicationABI: A mechanism for increasing video delivery quality in multi-radio Wireless Mesh Networks with Energy SavingWireless Mesh Networks (WMNs) are becoming increasingly popular mostly due to their ease of deployment. One of the main drawbacks of these networks is that they suffer with respect to Quality of Service (QoS) provisioning to its clients. Equipping wireless mesh nodes with multiple radios for increasing the available bandwidth has become a common practice nowadays due to the low cost of the wireless chipsets. Even though the available bandwidth increases with each radio deployed on the mesh node, the energy consumed for transmission increases accordingly. Thus, efficient usage of the radio interfaces is a key aspect for keeping the energy consumption at low levels while keeping a high QoS level for the mesh network’s clients. In the light of the above presented aspects concerning WMNs, the contribution of this paper is two-fold: (i) ABI, a mechanism for efficient usage of the available bandwidth for the mesh nodes, and (ii) decreasing the energy consumption by activating the radios only when needed. The solution proposed is throughly evaluated and shows that the two contributions can provide good QoS and decrease the overall energy consumption.
184Scopus© Citations 3 - PublicationAdaptive GC-aware load balancing strategy for high-assurance Java distributed systemsHigh-Assurance applications usually require achieving fast response time and high throughput on a constant basis. To fulfil these stringent quality of service requirements, these applications are commonly deployed in clustered instances. However, how to effectively manage these clusters has become a new challenge. A common approach is to deploy a front-end load balancer to optimise the workload distribution among the clustered applications. Thus, researchers have been studying how to improve the effectiveness of a load balancer. Our previous work presented a novel load balancing strategy which improves the performance of a distributed Java system by avoiding the performance impacts of Major Garbage Collection, which is a common cause of performance degradation in Java applications. However, as that strategy used a static configuration, it could only improve the performance of a system if the strategy was configured with domain expert knowledge. This paper extends our previous work by presenting an adaptive GC-aware load balancing strategy which self-configures according to the GC characteristics of the application. Our results have shown that this adaptive strategy can achieve higher throughput and lower response time, compared to the round-robin load balancing, while also avoiding the burden of manual tuning.
346Scopus© Citations 9 - PublicationAn Adaptive VM Provisioning Method for Large-Scale Agent-Based Traffic Simulations on the Cloud(Institute of Electrical and Electronic Engineers (IEEE), 2014-12-18)
; ; ; Using the Cloud for large-scale distributed simulations, such as agent-based traffic simulations, sounds like a good idea, as it is possible to provision and release easily processing nodes (e.g., Virtual machines) in the Cloud. However, the question is complex as it involves users' objectives, such as, time to process the simulation and cost of the simulation, and because the workload evolves in distributed simulations, in each node and the whole system, and this impact the resource provisioning plans. This paper proposes two main contributions: (i) a method for efficient utilization of computational resources for distributed agent-based simulations, providing a mechanism that adapts the resource provisioning to users' objectives and workload evolution, and (ii) a staged asynchronous migration technique to limit the migration overhead when the number of workers change. Our preliminary experimental results on a 24 hour scenario of traffic in the city of Tokyo show that our system outperforms a static provisioning by 12% in average and 23% during periods when workload changes a lot.430Scopus© Citations 15 - PublicationAutomated WAIT for Cloud-Based Application TestingCloud computing is causing a paradigm shift in the provision and use of software. This has changed the way of obtaining, managing and delivering computing services and solutions. Similarly, it has brought new challenges to software testing. A particular area of concern is the performance of cloud-based applications. This is because the increased complexity of the applications has exposed new areas of potential failure points, complicating all performance-related activities. This situation makes the performance testing of cloud environments very challenging. Similarly, the identification of performance issues and the diagnosis of their root causes are time-consuming and complex, usually require multiple tools and heavily rely on expertise. To simplify these tasks, hence increasing the productivity and reducing the dependency on human experts, this paper presents a lightweight approach to automate the usage of expert tools in the performance testing of cloud-based applications. In this paper, we use a tool named Whole-system Analysis of Idle Time to demonstrate how our research work solves this problem. The validation involved two experiments, which assessed the overhead of the approach and the time savings that it can bring to the analysis of performance issues. The results proved the benefits of the approach by achieving a significant decrease in the time invested in performance analysis while introducing a low overhead in the tested system.
391Scopus© Citations 11 - PublicationBDTest, a System to Test Big Data FrameworksTesting Big Data Processing systems is a challenging task as these systems are usually distributed on various virtual machines (potentially hosted by remote servers). In this poster we present a platform for testing non-functional properties of Big Data framework and a first implementation with Hadoop, a well known big data management and processing platform.
369Scopus© Citations 2 - PublicationBoTest: a Framework to Test the Quality of Conversational Agents Using Divergent Input Examples(ACM, 2018-03-11)
; ; ; ; ; Quality of conversational agents is important as users have high expectations. Consequently, poor interactions may lead to the user abandoning the system. In this paper, we propose a framework to test the quality of conversational agents. Our solution transforms working input that the conversational agent accurately recognises to generate divergent input examples that introduce complexity and stress the agent. As the divergent inputs are based on known utterances for which we have the 'normal' outputs, we can assess how robust the conversational agent is to variations in the input. To demonstrate our framework we built ChitChatBot, a simple conversational agent capable of making casual conversation.580Scopus© Citations 18 - PublicationCOCOA: A Synthetic Data Generator for Testing Anonymization Techniques(Springer, 2016-09-16)
; ; ; Conducting extensive testing of anonymization techniques is critical to assess their robustness and identify the scenarios where they are most suitable. However, the access to real microdata is highly restricted and the one that is publicly-available is usually anonymized or aggregated; hence, reducing its value for testing purposes. In this paper, we present a framework (COCOA) for the generation of realistic synthetic microdata that allows to define multi-attribute relationships in order to preserve the functional dependencies of the data. We prove how COCOA is useful to strengthen the testing of anonymization techniques by broadening the number and diversity of the test scenarios. Results also show how COCOA is practical to generate large datasets.839Scopus© Citations 8 - PublicationA comparative study of multi-objective machine reassignment algorithms for data centres(Springer, 2019-09-20)
; ; ; ; At a high level, data centres are large IT facilities hosting physical machines (servers) that often run a large number of virtual machines (VMs)— but at a lower level, data centres are an intricate collection of interconnected and virtualised computers, connected services, complex service-level agreements. While data centre managers know that reassigning VMs to the servers that would best serve them and also minimise some cost for the company can potentially save a lot of money—the search space is large and constrained, and the decision complicated as they involve different dimensions. This paper consists of a comparative study of heuristics and exact algorithms for the Multi-objective Machine Reassignment problem. Given the common intuition that the problem is too complicated for exact resolutions, all previous works have focused on various (meta)heuristics such as First-Fit, GRASP, NSGA-II or PLS. In this paper, we show that the state-of-art solution to the single objective formulation of the problem (CBLNS) and the classical multi-objective solutions fail to bridge the gap between the number, quality and variety of solutions. Hybrid metaheuristics, on the other hand, have proven to be more effective and efficient to address the problem – but as there has never been any study of an exact resolution, it was difficult to qualify their results. In this paper, we present the most relevant techniques used to address the problem, and we compare them to an exact resolution ( -Constraints). We show that the problem is indeed large and constrained (we ran our algorithm for 30 days on a powerful node of a supercomputer and did not get the final solution for most instances of our problem) but that a metaheuristic (GeNePi) obtains acceptable results: more (+188%) solutions than the exact resolution and a little more than half (52%) the hypervolume (measure of quality of the solution set).325Scopus© Citations 6 - PublicationDemo: PIT a Practical Mutation Testing Tool for Java(ACM, 2016-07-20)
; ; ; ; Mutation testing introduces artificial defects to measure the adequacy of testing. In case candidate tests can distinguish the behaviour of mutants from that of the original program, they are considered of good quality otherwise developers need to design new tests. While, this method has been shown to be effective, industry-scale code challenges its applicability due to the sheer number of mutants and test executions it requires. In this paper we present PIT, a practical mutation testing tool for Java, applicable on real-world codebases. PIT is fast since it operates on bytecode and optimises mutant executions. It is also robust and well integrated with development tools, as it can be invoked through a command line interface, Ant or Maven. PIT is also open source and hence, publicly available at http://pitest.org/.1034Scopus© Citations 128 - PublicationdSUMO: Towards a Distributed SUMO(2013-05-17)
; ; Microscopic urban mobility simulations consist of modelling a city's road network and infrastructure, and to run autonomous individual vehicles to understand accurately what is going on in the city. However, when the scale of the problem space is large or when the processing time is critical, performing such simulations might be problematic as they are very computationally expensive applications. In this paper, we propose to leverage the power of many computing resources to perform quicker or larger microscopic simulations, keeping the same accuracy as the classical simulation running on a single computing unit. We have implemented a distributed version of SUMO, called dSUMO. We show in this paper that the accuracy of the simulation in SUMO is not impacted by the distribution and we give some preliminary results regarding the performance of dSUMO compared to SUMO.647 - PublicationDynamic Adaptation of the Traffic Management System CarDemo(IEEE, 2014-09-12)
; ; ; ; ; ; ; ; 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.348 - PublicationAn Energy-efficient Mechanism for Increasing Video Quality of Service in Wireless Mesh NetworksThe continuous growth in user demand for high-quality rich media services puts pressure on Wireless Mesh Network (WMN) resources. Solutions such as those which increase the capacity of the mesh network by equipping mesh routers with additional wireless interfaces provide better Quality of Service (QoS) for video deliveries, but result in higher overall energy consumption for the network. This paper presents LBIS, a distributed solution which combines the benefits of both load-balancing and interface-shifting in order to enhance QoS levels for video services delivered over multi-hop WMNs, while maintaining low energy consumption levels within the network. Simulation-based results show very good performance of our proposed mechanism in terms of QoS metrics (delay, packet loss), Peak Signal-to Noise Ratio (PSNR) and energy consumption in mesh network topologies, and with varying video traffic loads and distributions. The results demonstrate how LBIS can increase the QoS for video deliveries by more than 30% at the cost of an insignificant increase of the overall network energy consumption compared to the WMN with multiple radio interfaces without the LBIS adaptation.
398 - PublicationEnhancing the Utility of Anonymized Data by Improving the Quality of Generalization Hierarchies(Transactions on Data Privacy, 2017-04)
; ; ; ; The dissemination of textual personal information has become an important driver of innovation. However, due to the possible content of sensitive information, this data must be anonymized. A commonly-used technique to anonymize data is generalization. Nevertheless, its effectiveness can be hampered by the Value Generalization Hierarchies (VGHs) used as poorly-specified VGHs can decrease the usefulness of the resulting data. To tackle this problem, in our previous work we presented the Generalization Semantic Loss (GSL), a metric that captures the quality of categorical VGHs in terms of semantic consistency and taxonomic organization. We validated the accuracy of GSL using an intrinsic evaluation with respect to a gold standard ontology. In this paper, we extend our previous work by conducting an extrinsic evaluation of GSL with respect to the performance that VGHs have in anonymization (using data utility metrics). We show how GSL can be used to perform an a priori assessment of the VGHs¿ effectiveness for anonymization. In this manner, data publishers can quantitatively compare the quality of various VGHs and identify (before anonymization) those that better retain the semantics of the original data. Consequently, the utility of the anonymized datasets can be improved without sacrificing the privacy goal. Our results demonstrate the accuracy of GSL, as the quality of VGHs measured with GSL strongly correlates with the utility of the anonymized data. Results also show the benefits that an a priori VGH assessment strategy brings to the anonymization process in terms of time-savings and a reduction in the dependency on expert knowledge. Finally, GSL also proved to be lightweight in terms of computational resources.276 - PublicationExact and Hybrid Solutions for the Multi-objective VM Reassignment Problem(World Scientific Publishing, 2017-02-23)
; ; ; Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer linear programming (MILP) approaches, especially given the size of data centres. Hybrid solutions mixing CP and heuristic algorithms, such as, large neighbourhood search (CBLNS), also struggle to address the problem given its size and number of constraints. The multi-objective version of the Machine Reassignment Problem is even more challenging and it seems unlikely for CP, MILP or hybrid solutions to obtain good results in this context. As a result, the first approaches to address this problem have been based on other optimisation methods, including metaheuristics. In this paper we study three things: (i) under which conditions a mixed integer optimisation solver, such as IBM ILOG CPLEX, can be used for the Multi-objective Machine Reassignment Problem; (ii) how much of the search space can a well-known hybrid method such as CBLNS explore; and (iii) can we find a better hybrid approach combining MILP or CBLNS and another recent metaheuristic proposed for the problem (GeNePi). We show that MILP can handle only small or medium scale data centres, and with some relaxations, such as, an optimality tolerance gap and a limited number of directions explored in the search space. CBLNS on the other hand struggles with the problem in general but achieves reasonable performance for large instances of the problem. However, we show that our hybridisation improves both the quality of the set of solutions (CPLEX+GeNePi and CBLNS+GeNePi improve the solutions by +17.8% against CPLEX alone and +615% against CBLNS alone) and number of solutions (8.9 times more solutions than CPLEX alone and 56.76 times more solutions than CBLNS alone), while the processing time of CPLEX+GeNePi and CBLNS+GeNePi increases only by 6% and 16.4% respectively. Overall, the study shows that CPLEX+GeNePi is the best algorithm for small instances (CBLNS+GeNePi only gets 45.2% of CPLEX+GeNePi’s hypervolume) while CBLNS+GeNePi is better than the others on large instances (that CPLEX+GeNePi cannot address).424Scopus© Citations 12 - PublicationExperience of developing an openflow SDN prototype for managing IPTV networksIPTV is a method of delivering TV content to endusers that is growing in popularity. The implications of poor video quality may ultimately be a loss of revenue for the provider. Hence, it is vital to provide service assurance in these networks. This paper describes our experience of building an IPTV Software Defined Network testbed that can be used to develop and validate new approaches for service assurance in IPTV networks. The testbed is modular and many of the concepts detailed in this tutorial may be applied to the management of other end-to-end services.
1230Scopus© Citations 9 - PublicationA Fair Comparison of VM Placement Heuristics and a More Effective Solution(Institute of Electrical and Electronic Engineers (IEEE), 2014-06-27)
; ; ; Data center optimization, mainly through virtual machine (VM) placement, has received considerable attention in the past years. A lot of heuristics have been proposed to give quick and reasonably good solutions to this problem. However it is difficult to compare them as they use different datasets, while the distribution of resources in the datasets has a big impact on the results. In this paper we propose the first benchmark for VM placement heuristics and we define a novel heuristic. Our benchmark is inspired from a real data center and explores different possible demographics of data centers, which makes it suitable when comparing the behaviour of heuristics. Our new algorithm, RBP, outperforms the state-of-the-art heuristics and provides close to optimal results quickly.395Scopus© Citations 9 - PublicationGlobal dynamic load-balancing for decentralised distributed simulation(Institute of Electrical and Electronic Engineers (IEEE), 2014-12-10)
; ; Distributed simulations require partitioning mechanisms to operate, and the best partitioning algorithms try to load-balance the partitions. Dynamic load-balancing, i.e. re-partitioning simulation environments at run-time, becomes essential when the load in the partitions change. In decentralised distributed simulation the information needed to dynamically load-balance seems difficult to collect and to our knowledge, all solutions apply a local dynamic load balancing: partitions exchange load only with their neighbours (more loaded partitions to less loaded ones). This limits the effect of the load-balancing. In this paper, we present a global dynamic load-balancing of decentralised distributed simulations. Our algorithm collects information in a decentralised fashion and makes re-balancing decisions based on the load processed by every logical processes. While our algorithm has similar results to others in most cases, we show an improvement of the load-balancing up to 30% in some challenging scenarios against only 12.5% for a local dynamic load-balancing.305Scopus© Citations 2 - PublicationIn-Test Adaptation of Workload in Enterprise Application Performance Testing(ACM, 2017-04-26)
; ; ; 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.426Scopus© Citations 5 - PublicationIs seeding a good strategy in multi-objective feature selection when feature models evolve?Context: When software architects or engineers are given a list of all the features and their interactions (i.e., a Feature Model or FM) together with stakeholders 'preferences' their task is to find a set of potential products to suggest the decision makers. Software Product Lines Engineering (SPLE) consists in optimising those large and highly constrained search spaces according to multiple objectives reflecting the preference of the different stakeholders. SPLE is known to be extremely skill- and labour-intensive and it has been a popular topic of research in the past years.Objective: This paper presents the first thorough description and evaluation of the related problem of evolving software product lines. While change and evolution of software systems is the common case in the industry, to the best of our knowledge this element has been overlooked in the literature. In particular, we evaluate whether seeding previous solutions to genetic algorithms (that work well on the general problem) would help them to find better/faster solutions.Method: We describe in this paper a benchmark of large scale evolving FMs, consisting of 5 popular FMs and their evolutions – synthetically generated following an experimental study of FM evolution. We then study the performance of a state-of-the-art algorithm for multi-objective FM selection (SATIBEA) when seeded with former solutions.Results: Our experiments show that we can improve both the execution time and the quality of SATIBEA by feeding it with previous configurations. In particular, SATIBEA with seeds proves to converge an order of magnitude faster than SATIBEA alone.Conclusion: We show in this paper that evolution of FMs is not a trivial task and that seeding previous solutions can be used as a first step in the optimisation - unless the difference between former and current FMs is high, where seeding has a limited impact.
351Scopus© Citations 11 - PublicationiVMp: an Interactive VM Placement Algorithm for Agile Capital Allocation(Institute of Electrical and Electronic Engineers (IEEE), 2013-06-03)
; ; ; ; Server consolidation is an important problem in any enterprise, where capital allocators (CAs) must approve any cost saving plans involving the acquisition or allocation of new assets and the decommissioning of inefficient assets. Our paper describes iVMp an interactive VM placement algorithm, that allows CAs to become 'agile' capital allocators that can interactively propose and update constraints and preferences as placements are recommended by the system. To the best of our knowledge this is the first time that this interactive VM placement recommendation problem has been addressed in the academic literature. Our results show that the proposed algorithm finds near optimal solutions in a highly efficient manner.303