Error and Attack Tolerance of Layered Complex Networks

Many complex systems may be described not by one, but by a number of complex networks mapped one on the other in a multilayer structure. The interactions and dependencies between these layers cause that what is true for a distinct single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of three real-life examples of two-layer complex systems that come from the fields of communication (the Internet), transportation (the European railway system) and biology (the human brain). In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multilayer systems are much more vulnerable to errors and intentional attacks than they seem to be from a single layer perspective.Comment: 5 pages, 3 figure

The unfolded protein response is activated in disease-affected brain regions in progressive supranuclear palsy and Alzheimer’s disease

Abstract Background Progressive supranuclear palsy (PSP) is a neurodegenerative disorder pathologically characterized by intracellular tangles of hyperphosphorylated tau protein distributed throughout the neocortex, basal ganglia, and brainstem. A genome-wide association study identified EIF2AK3 as a risk factor for PSP. EIF2AK3 encodes PERK, part of the endoplasmic reticulum’s (ER) unfolded protein response (UPR). PERK is an ER membrane protein that senses unfolded protein accumulation within the ER lumen. Recently, several groups noted UPR activation in Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis, multiple system atrophy, and in the hippocampus and substantia nigra of PSP subjects. Here, we evaluate UPR PERK activation in the pons, medulla, midbrain, hippocampus, frontal cortex and cerebellum in subjects with PSP, AD, and in normal controls. Results We found UPR activation primarily in disease-affected brain regions in both disorders. In PSP, the UPR was primarily activated in the pons and medulla and to a much lesser extent in the hippocampus. In AD, the UPR was extensively activated in the hippocampus. We also observed UPR activation in the hippocampus of some elderly normal controls, severity of which positively correlated with both age and tau pathology but not with Aβ plaque burden. Finally, we evaluated EIF2AK3 coding variants that influence PERK activation. We show that a haplotype associated with increased PERK activation is genetically associated with increased PSP risk. Conclusions The UPR is activated in disease affected regions in PSP and the genetic evidence shows that this activation increases risk for PSP and is not a protective response. </jats:sec

Sampling Bias in BitTorrent Measurements

Real-world measurements play an important role in understanding the characteristics and in improving the operation of BitTorrent, which is currently a popular Internet application. Much like measuring the Internet, the complexity and scale of the BitTorrent network make a single, complete measurement impractical. While a large number of measurements have already employed diverse sampling techniques to study parts of BitTorrent network, until now there exists no investigation of their sampling bias, that is, of their ability to objectively represent the characteristics of BitTorrent. In this work we present the first study of the sampling bias in BitTorrent measurements. We first introduce a novel taxonomy of sources of sampling bias in BitTorrent measurements. We then investigate the sampling among fifteen long-term BitTorrent measurements completed between 2004 and 2009, and find that different data sources and measurement techniques can lead to significantly different measurement results. Last, we formulate three recommendations to improve the design of future BitTorrent measurements, and estimate the cost of using these recommendations in practice

AVMEM - Availability-Aware Overlays for Management Operations in Non-cooperative Distributed Systems

Monitoring and management operations that query nodes based on their availability can be extremely useful in a variety of large- scale distributed systems containing hundreds to thousands of hosts, e.g., p2p systems, Grids, and PlanetLab. This paper presents decentralized and scalable solutions to a subset of such availability-based management tasks. Specifically, we propose AVMEM, which is the first availability- aware overlay to date. AVMEM is intended for generic non-cooperative scenarios where nodes may be selfish and may wish to route messages to a large set of other nodes, especially if the selfish node has low avail- ability. Under this setting, our concrete contributions are the following: (1) AVMEM allows arbitrary classes of application-specified predicates to create the membership relationships in the overlay. In order to avoid selfish nodes from exploiting the system, we focus on predicates that are random and consistent. In other words, whether a given node y is a neigh- bor of a given node x is decided based on a consistent and probabilistic predicate, dependent solely on the identifiers and availabilities of these two nodes, but without using any external inputs. (2) AVMEM protocols discover and maintain the overlay spanned by the application-specified AVMEM predicate in a scalable and fast manner. (3) We use AVMEM to execute important availability-based management operations, focus- ing on range-anycast, range-multicast, threshold-anycast, and threshold- multicast. AVMEM works well in the presence of selfish nodes, scales to thousands of nodes, and executes each of the targeted operations quickly and reliably. Our evaluation is driven by real-life churn traces from the Overnet p2p system, and shows that AVMEM works well in practical settings

A Task-Based Model for the Lifespan of Peer-to-Peer Swarms

Part 2: Peer to PeerInternational audiencePeer-to-Peer (P2P) techniques are broadly adopted in modern applications such as Xunlei and Private Tracker [1,2]. To address the problem of service availability, techniques such as bundling and implicit uploading are suggested to increase the swarm lifespan, i.e., the duration between the birth and the death of a swarm, by motivating or even forcing peers to make more contributions. In these systems, it is common for a peer to join a swarm repeatedly, which can introduce substantial bias for lifespan modeling and prediction. In this paper, we present a mathematical model to study the lifespan of a P2P swarming system in the presence of multi-participation. We perform evaluations on three traces and a well-known simulator. The result demonstrates that our model is more accurate than previous ones