Cache "less for more" in information-centric networks (extended version)

Ubiquitous in-network caching is one of the key aspects of information-centric networking (ICN) which has received widespread research interest in recent years. In one of the key relevant proposals known as Content-Centric Networking (CCN), the premise is that leveraging in-network caching to store content in every node along the delivery path can enhance content delivery. We question such an indiscriminate universal caching strategy and investigate whether caching less can actually achieve more. More specifically, we study the problem of en route caching and investigate if caching in only a subset of nodes along the delivery path can achieve better performance in terms of cache and server hit rates. We first study the behavior of CCN's ubiquitous caching and observe that even naïve random caching at a single intermediate node along the delivery path can achieve similar and, under certain conditions, even better caching gain. Motivated by this, we propose a centrality-based caching algorithm by exploiting the concept of (ego network) betweenness centrality to improve the caching gain and eliminate the uncertainty in the performance of the simplistic random caching strategy. Our results suggest that our solution can consistently achieve better gain across both synthetic and real network topologies that have different structural properties. We further find that the effectiveness of our solution is correlated to the precise structure of the network topology whereby the scheme is effective in topologies that exhibit power law betweenness distribution (as in Internet AS and WWW networks)

A PIMS Development Kit for New Personal Data Platforms

The web ecosystem is based on a market where stakeholders collect and sell personal data, but nowadays users expect stronger guarantees of transparency and privacy. With the PIMCity personal information management system (PIMS) development kit, we provide an open-source development kit for building PIMSs to foster the development of open and user-centric data markets

Immunomodulatory intervention in sepsis by multidrug-resistant Pseudomonas aeruginosa with thalidomide: an experimental study

BACKGROUND: Thalidomide is an inhibitor of tumour necrosis factor-alpha (TNFα) that has been proven effective for the treatment of experimental sepsis by Escherichia coli. It was tested whether it might behave as an effective immunomodulator in experimental sepsis by multidrug-resistant (MDR) Pseudomonas aeruginosa. METHODS: Sepsis was induced by the intraperitoneal injection of 1 × 10(8 )cfu/kg inoculum of the test isolate in a total of 109 Wistar rats divided in three groups as follows: group A controls; group B administered seed oil 30 minutes before bacterial challenge; and group C administered 50 mg/kg of thalidomide diluted in seed oil 30 minutes before bacterial challenge. Blood was sampled for estimation of endotoxins (LPS), TNFα, interferon-gamma (IFNγ), nitric oxide (NO) and malondialdehyde (MDA). LPS was measured by the QCL-1000 LAL assay, TNFα and IFNγ by ELISA, NO by a colorimetric assay and MDA by the thiobarbiturate assay. RESULTS: Mean (± SE) survival of groups A, B and C were 18.60 ± 1.84, 12.60 ± 0.60 and 30.50 ± 6.62 hours (p of comparisons A to C equal to 0.043 and B to C equal to 0.002). Decreased TNFα and NO levels were found in sera of animals of group C compared to group A. Plasma levels of LPS, MDA and IFNγ did not differ between groups. CONCLUSION: Intake of thalidomide considerably prolonged survival in experimental sepsis by MDR P.aeruginosa an effect probably attributed to decrease of serum TNFα

The Cache Inference Problem and its Application to Content and Request Routing (Extended Version

Abstract — In many networked applications, independent caching agents cooperate by servicing each other’s miss streams, without revealing the operational details of the caching mechanisms they employ. Inference of such details could be instrumental for many other processes. For example, it could be used for optimized forwarding (or routing) of one’s own miss stream (or content) to available proxy caches, or for making cache-aware resource management decisions. In this paper, we introduce the Cache Inference Problem (CIP) as that of inferring the characteristics of a caching agent, given the miss stream of that agent. While CIP is insolvable in its most general form, there are special cases of practical importance in which it is, including when the request stream follows an Independent Reference Model (IRM) with generalized power-law (GPL) demand distribution. To that end, we design two basic “litmus ” tests that are able to detect the LFU and LRU replacement policies, the effective size of the cache and of the object universe, and the skewness of the GPL demand for objects. Using extensive experiments under synthetic as well as real traces, we show that our methods infer such characteristics accurately and quite efficiently, and that they remain robust even when the IRM/GPL assumptions do not hold, and even when the underlying replacement policies are not “pure ” LFU or LRU. We demonstrate the value of our inference framework by considering example applications. I

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The cache inference problem and its application to content and request routing

In many networked applications, independent caching agents cooperate by servicing each other’s miss streams, without revealing the operational details of the caching mechanisms they employ. Inference of such details could be instrumental for many other processes. For example, it could be used for optimized forwarding (or routing) of one’s own miss stream (or content) to available proxy caches, or for making cache-aware resource management decisions. In this paper, we introduce the Cache Inference Problem (CIP) as that of inferring the characteristics of a caching agent, given the miss stream of that agent. While CIP is insolvable in its most general form, there are special cases of practical importance in which it is, including when the request stream follows an Independent Reference Model (IRM) with generalized power-law (GPL) demand distribution. To that end, we design two basic “litmus” tests that are able to detect the LFU and LRU replacement policies, the effective size of the cache and of the object universe, and the skewness of the GPL demand for objects. Using extensive experiments under synthetic as well as real traces, we show that our methods infer such characteristics accurately and quite efficiently, and that they remain robust even when the IRM/GPL assumptions do not hold, and even when the underlying replacement policies are not “pure” LFU or LRU. We demonstrate the value of our inference framework by considering example applications

Immunomodulatory Clarithromycin Treatment of Experimental Sepsis and Acute Pyelonephritis Caused by Multidrug-Resistant Pseudomonas aeruginosa

Clarithromycin was administered intravenously to 55 rabbits to evaluate its effect on experimental sepsis caused by multidrug-resistant Pseudomonas aeruginosa. Acute pyelonephritis was induced after ligation of the right ureter and injection of 10(8) CFU of the test isolate per kg of body weight into the renal pelvis. The animals were divided into six groups: group A, controls; group B, rabbits that received one intravenous dose of 80 mg of clarithromycin per kg concomitantly with bacterial challenge; group C, rabbits that received two doses of clarithromycin, the second one of which was given 2 h after the first one; group D, rabbits that received 15 mg of amikacin per kg; group E, rabbits that received one dose of clarithromycin and amikacin; and group F, rabbits that received two doses of clarithromycin and amikacin. Serum endotoxin levels were estimated by the QCL-1000 Limulus amoebocyte lysate assay, tumor necrosis factor alpha (TNF-α) levels were measured by a bioassay, and malondialdehyde (MDA) levels were measured by the thiobarbiturate assay. Viable bacterial counts in various tissue samples were also assessed. The mean survival times of the animals in groups A, B, C, D, E, and F were 4.50, 7.69, 4.07, 4.55, 11.55, and 11.60 days, respectively (P = 0.033 for group D versus group F, P = 0.006 for group D versus group E, P = not significant for group B versus group E, P = 0.042 for group C versus group F). Serum endotoxin levels were similar between groups at all sampling times; TNF-α and MDA levels in groups B, C, E, and F decreased significantly over follow-up. The numbers of viable bacterial cells in the infected kidney were similar among the groups; those in the liver, spleen, lungs, and mesenteral lymph nodes were significantly decreased in groups B, E, and F compared to those in groups A and D. It is concluded that a prolongation of survival in animals with experimental sepsis caused by multidrug-resistant P. aeruginosa was achieved after coadministration of clarithromycin and amikacin and that the increased survival was probably attributable to the immunomodulatory properties of clarithromycin

Future Media Internet Architecture Reference Model (v1.0)

Future Media Internet Architecture Think Tank White PaperThe Future Internet (FI) is expected to be a communication and delivery ecosystem, which will interface, interconnect, integrate and expand today's Internet, public and private intranets and communication networks of any type and scale, in order to provide efficiently, transparently and securely highly demanding services to humans and systems. This complex networking environment may be considered from various interrelated perspectives: the networks & infrastructure viewpoint, the services viewpoint, the media & information viewpoint. This document has been produces by a discussion forum of experts in the area of media and networks, named: Future Media Internet - Think Tank (FMIA-TT). FMIA-TT aims to create a reference model of a “Future Media Internet Architecture”, covering delivery, in the network adaptation/enrichment and consumption of media over the Future Internet ecosystem. This white paper concludes the first phase of the working group by proposing a FMIA reference model