Analysis of source code metrics from ns-2 and ns-3 network simulators

Ns-2 and its successor ns-3 are discrete-event simulators which are closely related to each other as they share common background, concepts and similar aims. Ns-3 is still under development, but it offers some interesting characteristics for developers while ns-2 still has a large user base. While other studies have compared different network simulators, focusing on performance measurements, in this paper we adopted a different approach by focusing on technical characteristics and using software metrics to obtain useful conclusions. We chose ns-2 and ns-3 for our case study because of the popularity of the former in research and the increasing use of the latter. This reflects the current situation where ns-3 has emerged as a viable alternative to ns-2 due to its features and design. The paper assesses the current state of both projects and their respective evolution supported by the measurements obtained from a broad set of software metrics. By considering other qualitative characteristics we obtained a summary of technical features of both simulators including, architectural design, software dependencies or documentation policies.Ministerio de Ciencia e Innovación TEC2009-10639-C04-0

From missions to systems : generating transparently distributable programs for sensor-oriented systems

Early Wireless Sensor Networks aimed simply to collect as much data as possible for as long as possible. While this remains true in selected cases, the majority of future sensor network applications will demand much more intelligent use of their resources as networks increase in scale and support multiple applications and users. Specifically, we argue that a computational model is needed in which the ways that data flows through networks, and the ways in which decisions are made based on that data, is transparently distributable and relocatable as requirements evolve. In this paper we present an approach to achieving this using high-level mission specifications from which we can automatically derive transparently distributable programs.Postprin

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily enhance the quality of the obtained results and, more importantly, make it feasible to tackle two main compiler optimization problems: optimization selection (choosing which optimizations to apply) and phase-ordering (choosing the order of applying optimizations). The compiler optimization space continues to grow due to the advancement of applications, increasing number of compiler optimizations, and new target architectures. Generic optimization passes in compilers cannot fully leverage newly introduced optimizations and, therefore, cannot keep up with the pace of increasing options. This survey summarizes and classifies the recent advances in using machine learning for the compiler optimization field, particularly on the two major problems of (1) selecting the best optimizations and (2) the phase-ordering of optimizations. The survey highlights the approaches taken so far, the obtained results, the fine-grain classification among different approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated quarterly here (Send me your new published papers to be added in the subsequent version) History: Received November 2016; Revised August 2017; Revised February 2018; Accepted March 2018

Architecture, design and source code comparison of ns-2 and ns-3 network simulators

Ns-2 and its successor ns-3 are discrete-event simulators. Ns- 3 is still under development, but offers some interesting characteristics for developers while ns-2 still has a big user base. This paper remarks current differences between both tools from developers point of view. Leaving performance and resources consumption aside, technical issues described in the present paper might help to choose one or another alternative depending of simulation and project management requirements.Ministerio de Educación y Ciencia TIN2006-15617-C03-03Junta de Andalucía P06-TIC-229