1,720,988 research outputs found
Analysis of MySpace User Profiles
No full textOnline social networks have attracted millions of users, who have integrated social network web sites into their daily life. Users participate to the changes and to the evolution of these sites because they are producers and reviewers of contents that help them to maintain the existing social relationships, make new friends, collaborate and enrich experiences. This paper presents a study of the characteristics of the users
of MySpace web site, with the objective of studying relationships and interactions among users and deriving hints about their behavior. The analysis relies on data collected by monitoring the web site for 12 weeks.
Typical user behaviors have been derived and classes of users characterized by different levels of participation to the social network have been identified. In particular, the analysis reveals that most of the users actively participate to the social network and specify many
personal details. Social networks web sites allow access to such details; the sharing of information about users and their relationships can lead to non-ethic online activities, which threat the privacy and the security of
users themselves
What's inside MySpace comments?
No full textThe paper presents a characterization of the comments
included in the user profiles of a popular social networking
site. Some parameters are defined, which express comments
composition in terms of length, language used, and external
resources accessed. From the analysis of comments a model is
derived, which reflects three different types of users. The behavior
of users in terms of the language used is also derived
A Methodology Towards Automatic Performance Analysis of Parallel Applications
No full textTuning and debugging the performance of parallel applications is an iterative process consisting of several steps dealing with identification and localization of inefficiencies, repair, and verification of the achieved performance. In this paper, we address the analysis of the performance of parallel applications from a methodological viewpoint with the aim of identifying and localizing inefficiencies. Our methodology is based on performance metrics and criteria that highlight the properties of the applications and the load imbalance and dissimilarities in the behavior of the processors. A few case studies illustrate the application of the methodology
Workload Characterization: A Survey Revisited
Full text linkWorkload characterization is a well-established discipline that plays a key role in many performance en-
gineering studies. The large-scale social behavior inherent in the applications and services being deployed
nowadays leads to rapid changes in workload intensity and characteristics and opens new challenging
management and performance issues. A deep understanding of user behavior and workload properties and
patterns is therefore compelling. This article presents a comprehensive survey of the state of the art of
workload characterization by addressing its exploitation in some popular application domains. In particular,
we focus on conventional web workloads as well as on the workloads associated with online social networks,
video services, mobile apps, and cloud computing infrastructures. We discuss the peculiarities of these work-
loads and present the methodological approaches and modeling techniques applied for their characterization.
The role of workload models in various scenarios (e.g., performance evaluation, capacity planning, content
distribution, resource provisioning) is also analyzed
Workflow Scheduling in the Cloud-Edge Continuum
No full textScheduling in the cloud-edge continuum is a challenging problem. In
fact, scheduling has to cope with the peculiarities of these complex ecosystems
and satisfy at the same time the desired service levels. In this paper, we investigate
the benefits of the cloud-edge continuum for deploying workflows with different
characteristics, e.g., computation or communication-intensive. In detail, we formulate a multi-objective optimization problem solved using a Genetic Algorithm.
This problem is aimed at identifying the scheduling plans that minimize two conflicting objectives, namely, the expected workflow execution time and monetary
cost associated with the cloud and edge resources to be provisioned. Our experiments have shown that the plans that exploit both cloud and edge resources represent a good tradeoff between the two objectives. In addition, the workflow characteristics strongly influence these plans. Similarly, the uncertainties that might
affect the infrastructure performance are responsible of significant changes in the
corresponding Pareto fronts
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