There is significant interest in the technical and policy communities regarding the extent, scope, and consumer harm of persistent interdomain congestion. We provide empirical grounding for discussions of interdomain congestion by developing a system and method to measure congestion on thousands of interdomain links without direct access to them. We implement a system based on the Time Series Latency Probes (TSLP) technique that identifies links with evidence of recurring congestion suggestive of an under-provisioned link. We deploy our system at 86 vantage points worldwide and show that congestion inferred using our lightweight TSLP method correlates with other metrics of interconnection performance impairment. We use our method to study interdomain links of eight large U.S. broadband access providers from March 2016 to December 2017, and validate our inferences against ground-truth traffic statistics from two of the providers. For the period of time over which we gathered measurements, we did not find evidence of widespread endemic congestion on interdomain links between access ISPs and directly connected transit and content providers, although some such links exhibited recurring congestion patterns. We describe limitations, open challenges, and a path toward the use of this method for large-scale third-party monitoring of the Internet interconnection ecosystem.

No abstract

IntroductionA software organization typically operates in three dimensions for increasing productivity -process, technology and people. There is considerable literature on the process and technology dimensions 1, 2 but very little on the people dimension 3 . Glass, et al 3 have studied 369 papers in 6 leading journals and discovered that Software Engineering research is fundamentally about technical and computing issues and that it is seldom about behavioral issues. In industry, discussion about the people dimension is generally limited to training for new processes and technologies 4 . Since this approach has not accrued any perceptible gains in productivity 5 , we believe that there is a case for exploring the people dimension deeply and earnestly.The major contribution of this paper is to put forth a multi-stage approach to develop egoless programmers as advocated by Weinberg. We are using contemporary terms like egoless engineering and development or general terms like egoless behavior to mean the same thing i.e. egoless programming. Our multi-stage approach consists of developing an instrument to assess "egoless behavior" of individuals, validating the self-assessment with peers' assessments and formulating group and individual action plans. The paper reports self-assessment and team-assessment using the instrument. The sample size consists of 86 software engineering students of a junior class of a computer engineering undergraduate program. The analysis includes "egoless" behavior of the class based on self-assessment and team-assessment, as well as their correlation with determinants like gender, semester and cumulative grade point averages (SGPA and CGPA).The next section discusses the background behind the problem of productivity in software organizations followed by the research design of our experiment leading to analysis of the results and ending with concluding remarks.

No abstract

No abstract