Network emulation focusing on QoS-Oriented satellite communication

This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication

An overview of link-level measurement techniques for wide-area wireless networks

By building wireless link-level measurement tools we hope to improvement the design, deployment and management of wide-area wireless community networks. This paper identifies existing link-level measurement techniques and discusses the advantages and disadvantages of each in the context of measuring and monitoring such networks. Finally, we make a case for the need for more sophisticated techniques and tools which will assist both day-to-day network operations as well as wireless network research

Why (and How) Networks Should Run Themselves

The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasingly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the importance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need data-driven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detection algorithms that can make real-time, closed-loop decisions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols

Foam Rolling as a Warm-up: The Effect on Lower Extremity Flexibility Compared to Aerobic and Stretching Protocols

Foam rolling has recently become popular in the realms of athletic training, strength and conditioning, and fitness enthusiasts as a means to decrease stiffness, improve flexibility, and manage pain . However, little is known about the physiological effects of foam rolling or its role in improving flexibility pre- or post-exercise. The purpose of this project is to examine and compare the effects of foam rolling, aerobic cycling, and stretching on lower extremity flexibility. Nineteen participants (10 female, 9 male) volunteered to test sit-and-reach flexibility after performing four different warm-up protocols on different days. The warm-up protocols were: Foam Rolling for five minutes, aerobic cycling for five minutes, stretching for five minutes, or lying supine for five minutes (control). A one-way repeated measures ANOVA test was used to determine significant difference (p \u3e 0.05) compared to the control group. Results indicate that foam rolling, cycling, and stretching significantly improved lower body sit-and-reach scores over the control. No significant differences were found between protocols