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Mobile applications (apps) often suffer from failure nowadays. Developers usually pay more attention to the failure that is perceived by users and compromises the user experience. Existing approaches focus on mining large volume logs to…
As more and more service providers choose Cloud platforms, which is provided by third party resource providers, resource providers needs to provision resources for heterogeneous workloads in different Cloud scenarios. Taking into account…
Identifying root causes for unexpected or undesirable behavior in complex systems is a prevalent challenge. This issue becomes especially crucial in modern cloud applications that employ numerous microservices. Although the machine learning…
While the advanced machine learning algorithms are effective in load forecasting, they often suffer from low data utilization, and hence their superior performance relies on massive datasets. This motivates us to design machine learning…
Web applications, accessible via web browsers over the Internet, facilitate complex functionalities without local software installation. In the context of web applications, a workload refers to the number of user requests sent by users or…
Fog computing, which distributes computing resources to multiple locations between the Internet of Things (IoT) devices and the cloud, is attracting considerable attention from academia and industry. Yet, despite the excitement about the…
Today, the number of data-intensive and compute-intensive applications like business and scientific workflows has dramatically increased, which made cloud computing more popular in the matter of delivering a large amount of computing…
Clustering is a fundamental data mining tool that aims to divide data into groups of similar items. Generally, intuition about clustering reflects the ideal case -- exact data sets endowed with flawless dissimilarity between individual…
Cloud application services are distributed in nature and have components across the stack working together to deliver the experience to end users. The wide adoption of microservice architecture exacerbates failure management due to…
In the past few years, we have envisioned an increasing number of businesses start driving by big data analytics, such as Amazon recommendations and Google Advertisements. At the back-end side, the businesses are powered by big data…
Benchmarking the performance of public cloud providers is a common research topic. Previous research has already extensively evaluated the performance of different cloud platforms for different use cases, and under different constraints and…
Cloud applications are increasingly shifting from large monolithic services to complex graphs of loosely-coupled microservices. Despite the advantages of modularity and elasticity microservices offer, they also complicate cluster management…
Detecting and resolving performance anomalies in Cloud services is crucial for maintaining desired performance objectives. Scaling actions triggered by an anomaly detector help achieve target latency at the cost of extra resource…
Context: The success of software crowdsourcing depends on steady tasks supply and active worker pool. Existing analysis reveals an average task failure ratio of 15.7% in software crowdsourcing market. Goal: The objective of this study is to…
Due to the new advancements in automation using Artificial Intelligence, Robotics and Internet of Things it has become crucial to pay attention to possible vulnerabilities in order to avoid cyber attack and hijacking that can occur which…
In this paper, the fundamental problem of distribution and proactive caching of computing tasks in fog networks is studied under latency and reliability constraints. In the proposed scenario, computing can be executed either locally at the…
Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous disciplines, from…
At present there are a number of barriers to creating an energy efficient workload scheduler for a Private Cloud based data center. Firstly, the relationship between different workloads and power consumption must be investigated. Secondly,…
As cloud services become central in an increasing number of applications, they process and store more personal and business-critical data. At the same time, privacy and compliance regulations such as GDPR, the EU ePrivacy regulation, PCI,…
This paper presents a methodology and a system, named LogMaster, for mining correlations of events that have multiple attributions, i.e., node ID, application ID, event type, and event severity, in logs of large-scale cluster systems.…