A Bypass-Ring Scheme for a Fault Tolerant Multicast

We present a fault tolerant scheme for recovery from single or multiple node failures in multi-directional multicast trees. The scheme is based on cyclic structures providing alternative paths to eliminate faulty nodes and reroute the traffic. Our scheme is independent of message source and direction in the tree, provides a basis for on-the-fly repair and can be used as a platform for various strategies for reconnecting tree partitions. It only requires an underlying infrastructure to provide a reliable routing service. Although it is described in the context of a message multicast, the scheme can be used universally in all systems using tree-based overlay networks for communication among components

Analysis of the Error Propagation Phenomenon in Network Structures

The analysis of error propagation is of fundamental importance to assure safe operation and management of abnormal situations in any distributed information system. In this paper, the quantitative and qualitative methods are proposed to analyze possible error propagation scenarios based on different topologies, error types and probability distributions. The most interesting from our point of view is the course of error propagation in simple structures that are contained in more complex ones. These complex structures, which have attracted the attention of scientists for many decades, are traditionally analyzed with the use of formalisms from graph theory. Certain types of graphs are often used to model naturally occurring complex structures, such as social networks. Graph-theoretic approach proved successful when applied to social networks and other naturally occurring complex networks. The research was verified based on the experiments conducted on simulation model. The results provide some ideas of robustness -- the knowledge how to design the most error resistant architectures in complex environments

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Scalable, Data- intensive Network Computation

To enable groups of collaborating researchers at different locations to effectively share large datasets and investigate their spontaneous hypotheses on the fly, we are interested in de- veloping a distributed system that can be easily leveraged by a variety of data intensive applications. The system is composed of (i) a number of best effort logistical depots to en- able large-scale data sharing and in-network data processing, (ii) a set of end-to-end tools to effectively aggregate, manage and schedule a large number of network computations with attendant data movements, and (iii) a Distributed Hash Table (DHT) on top of the generic depot services for scalable data management. The logistical depot is extended by following the end-to-end principles and is modeled with a closed queuing network model. Its performance characteristics are studied by solving the steady state distributions of the model using local balance equations. The modeling results confirm that the wide area network is the performance bottleneck and running concurrent jobs can increase resource utilization and system throughput. As a novel contribution, techniques to effectively support resource demanding data- intensive applications using the ¯ne-grained depot services are developed. These techniques include instruction level scheduling of operations, dynamic co-scheduling of computation and replication, and adaptive workload control. Experiments in volume visualization have proved the effectiveness of these techniques. Due to the unique characteristic of data- intensive applications and our co-scheduling algorithm, a DHT is implemented on top of the basic storage and computation services. It demonstrates the potential of the Logistical Networking infrastructure to serve as a service creation platform

High Performance Frequent Subgraph Mining on Transactional Datasets

Graph data mining has been a crucial as well as inevitable area of research. Large amounts of graph data are produced in many areas, such as Bioinformatics, Cheminformatics, Social Networks, and Web etc. Scalable graph data mining methods are getting increasingly popular and necessary due to increased graph complexities. Frequent subgraph mining is one such area where the task is to find overly recurring patterns/subgraphs. To tackle this problem, many main memory-based methods were proposed, which proved to be inefficient as the data size grew exponentially over time. In the past few years several research groups have attempted to handle the frequent subgraph mining (FSM) problem in multiple ways. Many authors have tried to achieve better performance using Graphic Processing Units (GPUs) which has multi-fold improvement over in-memory while dealing with large datasets. Later, Google\u27s MapReduce model with the Hadoop framework proved to be a major breakthrough in high performance large batch processing. Although MapReduce came with many benefits, its disk I/O and non-iterative style model could not help much for FSM domain since subgraph mining process is an iterative approach. In recent years, Spark has emerged to be the De Facto industry standard with its distributed in-memory computing capability. This is a right fit solution for iterative style of programming as well. In this work, we cover how high-performance computing has helped in improving the performance tremendously in the transactional directed and undirected aspect of graphs and performance comparisons of various FSM techniques are done based on experimental results

Risk analysis of autonomous vehicle and its safety impact on mixed traffic stream

In 2016, more than 35,000 people died in traffic crashes, and human error was the reason for 94% of these deaths. Researchers and automobile companies are testing autonomous vehicles in mixed traffic streams to eliminate human error by removing the human driver behind the steering wheel. However, recent autonomous vehicle crashes while testing indicate the necessity for a more thorough risk analysis. The objectives of this study were (1) to perform a risk analysis of autonomous vehicles and (2) to evaluate the safety impact of these vehicles in a mixed traffic stream. The overall research was divided into two phases: (1) risk analysis and (2) simulation of autonomous vehicles. Risk analysis of autonomous vehicles was conducted using the fault tree method. Based on failure probabilities of system components, two fault tree models were developed and combined to predict overall system reliability. It was found that an autonomous vehicle system could fail 158 times per one-million miles of travel due to either malfunction in vehicular components or disruption from infrastructure components. The second phase of this research was the simulation of an autonomous vehicle, where change in crash frequency after autonomous vehicle deployment in a mixed traffic stream was assessed. It was found that average travel time could be reduced by about 50%, and 74% of conflicts, i.e., traffic crashes, could be avoided by replacing 90% of the human drivers with autonomous vehicles

Ontwerp en evaluatie van content distributie netwerken voor multimediale streaming diensten.

Traditionele Internetgebaseerde diensten voor het verspreiden van bestanden, zoals Web browsen en het versturen van e-mails, worden aangeboden via één centrale server. Meer recente netwerkdiensten zoals interactieve digitale televisie of video-op-aanvraag vereisen echter hoge kwaliteitsgaranties (QoS), zoals een lage en constante netwerkvertraging, en verbruiken een aanzienlijke hoeveelheid bandbreedte op het netwerk. Architecturen met één centrale server kunnen deze garanties moeilijk bieden en voldoen daarom niet meer aan de hoge eisen van de volgende generatie multimediatoepassingen. In dit onderzoek worden daarom nieuwe netwerkarchitecturen bestudeerd, die een dergelijke dienstkwaliteit kunnen ondersteunen. Zowel peer-to-peer mechanismes, zoals bij het uitwisselen van muziekbestanden tussen eindgebruikers, als servergebaseerde oplossingen, zoals gedistribueerde caches en content distributie netwerken (CDN's), komen aan bod. Afhankelijk van de bestudeerde dienst en de gebruikte netwerktechnologieën en -architectuur, worden gecentraliseerde algoritmen voor netwerkontwerp voorgesteld. Deze algoritmen optimaliseren de plaatsing van de servers of netwerkcaches en bepalen de nodige capaciteit van de servers en netwerklinks. De dynamische plaatsing van de aangeboden bestanden in de verschillende netwerkelementen wordt aangepast aan de heersende staat van het netwerk en aan de variërende aanvraagpatronen van de eindgebruikers. Serverselectie, herroutering van aanvragen en het verspreiden van de belasting over het hele netwerk komen hierbij ook aan bod