41,235 research outputs found
Coordination Implications of Software Coupling in Open Source Projects
The effect of software coupling on the quality of software has been studied quite widely since the seminal paper on software modularity by Parnas [1]. However, the effect of the increase in software coupling on the coordination of the developers has not been researched as much. In commercial software development environments there normally are coordination mechanisms in place to manage the coordination requirements due to software dependencies. But, in the case of Open Source software such coordination mechanisms are harder to implement, as the developers tend to rely solely on electronic means of communication. Hence, an understanding of the changing coordination requirements is essential to the management of an Open Source project. In this paper we study the effect of changes in software coupling on the coordination requirements in a case study of a popular Open Source project called JBoss
Predicting Intermediate Storage Performance for Workflow Applications
Configuring a storage system to better serve an application is a challenging
task complicated by a multidimensional, discrete configuration space and the
high cost of space exploration (e.g., by running the application with different
storage configurations). To enable selecting the best configuration in a
reasonable time, we design an end-to-end performance prediction mechanism that
estimates the turn-around time of an application using storage system under a
given configuration. This approach focuses on a generic object-based storage
system design, supports exploring the impact of optimizations targeting
workflow applications (e.g., various data placement schemes) in addition to
other, more traditional, configuration knobs (e.g., stripe size or replication
level), and models the system operation at data-chunk and control message
level.
This paper presents our experience to date with designing and using this
prediction mechanism. We evaluate this mechanism using micro- as well as
synthetic benchmarks mimicking real workflow applications, and a real
application.. A preliminary evaluation shows that we are on a good track to
meet our objectives: it can scale to model a workflow application run on an
entire cluster while offering an over 200x speedup factor (normalized by
resource) compared to running the actual application, and can achieve, in the
limited number of scenarios we study, a prediction accuracy that enables
identifying the best storage system configuration
TESNA: A Tool for Detecting Coordination Problems
Detecting problems in coordination can prove to be very difficult. This is especially true in large globally distributed environments where the Software Development can quickly go out of the Project Managerâs control. In this paper we outline a methodology to analyse the socio-technical coordination structures. We also show how this can be made easier with the help of a tool called TESNA that we have developed
DCDIDP: A distributed, collaborative, and data-driven intrusion detection and prevention framework for cloud computing environments
With the growing popularity of cloud computing, the exploitation of possible vulnerabilities grows at the same pace; the distributed nature of the cloud makes it an attractive target for potential intruders. Despite security issues delaying its adoption, cloud computing has already become an unstoppable force; thus, security mechanisms to ensure its secure adoption are an immediate need. Here, we focus on intrusion detection and prevention systems (IDPSs) to defend against the intruders. In this paper, we propose a Distributed, Collaborative, and Data-driven Intrusion Detection and Prevention system (DCDIDP). Its goal is to make use of the resources in the cloud and provide a holistic IDPS for all cloud service providers which collaborate with other peers in a distributed manner at different architectural levels to respond to attacks. We present the DCDIDP framework, whose infrastructure level is composed of three logical layers: network, host, and global as well as platform and software levels. Then, we review its components and discuss some existing approaches to be used for the modules in our proposed framework. Furthermore, we discuss developing a comprehensive trust management framework to support the establishment and evolution of trust among different cloud service providers. © 2011 ICST
Material and immaterial dimensions of clusters. Cooperation and learning as infrastructure for innovation
The paper concentrates on forms of cooperation in a learning context and presents theory-based empirical results of interactive learning processes in different clusters. A general outline of institutional aspects of clusters and networks is given and more specific theories of interactive learning are focussed. An extensive comparison of forms of such learning processes is undertaken, and finally policy conclusions are be drawn.
Role and Discipline Relationships in a Transdisciplinary Biomedical Team: Structuration, Values Override and Context Scaffolding
Though accepted that "team science" is needed to tackle and conquer the
health problems that are plaguing our society significant empirical evidence of
team mechanisms and functional dynamics is still lacking in abundance. Through
grounded methods the relationship between scientific disciplines and team roles
was observed in a United States National Institutes of Health-funded (NIH)
research consortium. Interviews and the Organizational Culture Assessment
Instrument (OCAI) were employed.. Findings show strong role and discipline
idiosyncrasies that when viewed separately provide different insights into team
functioning and change receptivity. When considered simultaneously,
value-latent characteristics emerged showing self-perceived contributions to
the team. This micro/meso analysis suggests that individual participation in
team level interactions can inform the structuration of roles and disciplines
in an attempt to tackle macro level problems.Comment: Presented at COINs13 Conference, Chile, 2013 (arxiv:1308.1028
Outlier detection techniques for wireless sensor networks: A survey
In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree
- âŠ