Cross-Layer Peer-to-Peer Track Identification and Optimization Based on Active Networking

P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a crosslayer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols

Dynamic Virtual Page-based Flash Translation Layer with Novel Hot Data Identification and Adaptive Parallelism Management

Solid-state disks (SSDs) tend to replace traditional motor-driven hard disks in high-end storage devices in past few decades. However, various inherent features, such as out-of-place update [resorting to garbage collection (GC)] and limited endurance (resorting to wear leveling), need to be reduced to a large extent before that day comes. Both the GC and wear leveling fundamentally depend on hot data identification (HDI). In this paper, we propose a hot data-aware flash translation layer architecture based on a dynamic virtual page (DVPFTL) so as to improve the performance and lifetime of NAND flash devices. First, we develop a generalized dual layer HDI (DL-HDI) framework, which is composed of a cold data pre-classifier and a hot data post-identifier. Those can efficiently follow the frequency and recency of information access. Then, we design an adaptive parallelism manager (APM) to assign the clustered data chunks to distinct resident blocks in the SSD so as to prolong its endurance. Finally, the experimental results from our realized SSD prototype indicate that the DVPFTL scheme has reliably improved the parallelizability and endurance of NAND flash devices with improved GC-costs, compared with related works.Peer reviewe

Non-Destructive Inspection of Impact Damage in Composite Aircraft Panels by Ultrasonic Guided Waves and Statistical Processing.

This paper discusses a non-destructive evaluation (NDE) technique for the detection of damage in composite aircraft structures following high energy wide area blunt impact (HEWABI) from ground service equipment (GSE), such as heavy cargo loaders and other heavy equipment. The test structures typically include skin, co-cured stringers, and C-frames that are bolt-connected onto the skin with shear ties. The inspection exploits the waveguide geometry of these structures by utilizing ultrasonic guided waves and a line scan approach. Both a contact prototype and a non-contact prototype were developed and tested on realistic test panels subjected to impact in the laboratory. The results are presented in terms of receiver operating characteristic curves that show excellent probability of detection with low false alarm rates for defects located in the panel skin and stringers

Cognitive strategic groups and long-run efficiency evaluation : the case of Spanish savings banks

In the framework of Cognitive Approach, this paper proposes a new method to identify strategic groups (SG) using Data Envelopment Analysis (DEA) methods. Two assumptions are maintained in the SG literature: first, firms grouped together value inputs and outputs similarly, and, second, some degree of stability in those valuations should be identified. Virtual weights obtained from DEA are extremely useful in the valuation of the strategic variables, but a problem emerges when longitudinal analysis is performed. This problem is addressed by defining a long run DEA evaluation. SGs are determined by means of Cluster Analysis, using virtual outputs and virtual inputs as variables and Spanish savings banks as observations. The traditional method of determining SGs by clustering on the original variables is also applied and the results are compared. It is shown that the long run DEA weights approach has advantages over the traditional methodology