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Truck platooning is a form of convoy cooperative driving of connected trucks assisted by a lead truck. The aim is to reduce the fuel and driving costs, improve road safety, and reduce CO 2 emission. Being semi-autonomous, platoons must be trustworthy in many perspectives. This paper presents a high-level trustworthy requirements analysis on three key perspectives: driver, communication, and security. In addition, we observed that any trustworthy requirement analysis is incomplete if perspectives are addressed independently. Therefore, we propose a simple holistic methodology that addresses the different perspectives as well as their dependencies, and we exemplify the use of the methodology with two use cases presented in the paper. However, we draw attention to the importance of more research to drive a more exhaustive and validated methodology1.

This paper presents our experience in coordinating and teaching a novel graduate systems and computing course named “Successful Systems in Production” (SSP). The course targets graduate students of different research interests in Computer Science. The course aims at giving a breadth knowledge on cutting-edge well-known systems in production, and exploring the potential synergies across different areas of research. Having its roots in Distributed Computing, SSP addresses those systems that overlap with other research areas like Computational Systems, Parallel Computing, Databases, Cloud Computing, Artificial Intelligence, Security, etc. SSP exhibits an agile topic selection model that fits several students’ backgrounds in each academic year. The topics focus on the practical aspects of each selected system that is considered “successful”, i.e., based on its worldwide impact and technical significance. This is important for graduate students to acquire best practices in industry and academia, necessary to build practical computing systems. In the same vein, the assessment method includes a project that is based on one of the presented systems and also intersects with the student’s own research plan. Based on our teaching experience and the excellent feedback of the students, we strongly recommend this graduate course to be taught at other universities.

Strongly consistent systems supporting distributed transactions can be prone to high latency and do not tolerate partitions. The present trend of using weaker forms of consistency, to achieve high availability, poses notable challenges in writing applications due to the lack of linearizability, e.g., to ensure global invariants, or perform mutator operations on a distributed datatype. This paper addresses a specific problem: the exactly-once transfer of a "quantity" from one node to another on an unreliable network (coping with message duplication, loss, or reordering) and without any form of global synchronization. This allows preserving a global property (the sum of quantities remains unchanged) without requiring global linearizability and only through using pairwise interactions between nodes, therefore allowing partitions in the system. We present the novel quantity-transfer algorithm while focusing on a specific use-case: a redistribution protocol to keep the quantities in a set of nodes balanced; in particular, averaging a shared real number across nodes. Since this is a work in progress, we briefly discuss the correctness of the protocol, and we leave potential extensions and empirical evaluations for future work., This work is financed by the FCT Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project UID/EEA/50014/2013; and by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement 609551, SyncFree project., info:eu-repo/semantics/publishedVersion

Enabling anonymous communication over the Internet is crucial. The first protocols that have been devised for anonymous communication are subject to freeriding. Recent protocols have thus been proposed to deal with this issue. However, these protocols do not scale to large systems, and some of them further assume the existence of trusted servers. In this paper, we present RAC, the first anonymous communication protocol that tolerates freeriders and that scales to large systems. Scalability comes from the fact that the complexity of RAC in terms of the number of message exchanges is independent from the number of nodes in the system. Another important aspect of RAC is that it does not rely on any trusted third party. We theoretically prove, using game theory, that our protocol is a Nash equilibrium, i.e, that freeriders have no interest in deviating from the protocol. Further, we experimentally evaluate RAC using simulations. Our evaluation shows that, whatever the size of the system (up to 100.000 nodes), the nodes participating in the system observe the same throughput.

Notable Byzantine Fault Tolerant protocols have been designed so far. These protocols are often evaluated on simple benchmarks, and few times on NFS systems. On the contrary, studies that addressed the behavior of BFT on large back-ends, like Directories, are few. We believe that studying such systems is crucial for practice community due to their popularity. In this paper, we integrate BFT with OpenLDAP Directory. We introduce the design of the integrated system, that we call BFT-LDAP. Then, we study its behavior accompanied with some useful observations. In addition, we discuss the cost overhead of this integration. Our approach ensures that OpenLDAP legacy code remains completely intact, and that the integration with BFT is straightforward using APIs. Moreover, we convey that the additional performance cost of BFT-LDAP is negligible as compared to that of stand-alone OpenLDAP. We conducted our experiments on Emulab. The experiments indicate that the performance discrepancy of BFT-LDAP is negligible whenever different state-of-the-art BFT protocols are used. Other experiments demonstrate that a little sacrifice in throughput (less than 10%) is needed in order to leverage the resiliency of OpenLDAP against Byzantine faults (i.e., through applying BFT).

An effective and simple algorithm for localization of epileptiform sources of the EEG signals within the brain has been developed here. The method includes a constrained blind source separation (CBSS) algorithm, which attempts to separate and localize the epileptifom EEG sources. The significance of the new developed algorithm is the incorporation of a proper constraint into the joint approximate diagonalization formulation. The fixed locations of the electrodes together with the normalized correlations between the estimated sources and the observed EEGs provide a sufficient geometrical information to localize the sources.

A robust constrained blind source separation algorithm (CBSS) has been developed here for an effective removal of eye muscle artifacts from electroencephalograms (EEG). Presently, clinicians reject a data segment if the patient blinked or spoke. The rejected data segment may contain important information that may be masked by the artifact. In the CBSS technique we exploit a reference signals as a constraint. The constrained problem is then converted to an unconstrained problem by means of nonlinear penalty functions weighted by the penalty terms. This leads to the modification of the overall cost function, based on the natural gradient algorithm (NGA), by incorporating a reference signal.

A robust method for removal of artifacts such as eye blinks and electrocardiogram (ECG) from the electroencephalograms (EEGs) has been developed in this paper. The proposed hybrid method fuses support vector machines (SVMs) based classification and blind source separation (BSS) based on independent component analysis (ICA). The carefully chosen features for the classifier mainly represent the data higher order statistics. We use the second order blind identification (SOBI) algorithm to separate the EEG into statistically independent sources and SVMs to identify the artifact components and thereby to remove such signals. The remaining independent components are remixed to reproduce the artifact free EEGs. Objective and subjective results from the simulation studies show that the algorithm outperforms previously proposed algorithms

Many state-machine Byzantine Fault Tolerant (BFT) protocols have been introduced so far. Each protocol addressed a different subset of conditions and use-cases. However, if the underlying conditions of a service span different subsets, choosing a single protocol will likely not be a best fit. This yields robustness and performance issues which may be even worse in services that exhibit fluctuating conditions and workloads. In this paper, we reconcile existing state-machine BFT protocols in a single adaptive BFT system, called ADAPT, aiming at covering a larger set of conditions and use-cases, probably the union of individual subsets of these protocols. At anytime, a launched protocol in ADAPT can be aborted and replaced by another protocol according to a potential change (an event) in the underlying system conditions. The launched protocol is chosen according to an 'evaluation process' that takes into consideration both: protocol characteristics and its performance. This is achieved by applying some mathematical formulas that match the profiles of protocols to given user (e.g., service owner) preferences. ADAPT can assess the profiles of protocols (e.g., throughput) at run-time using Machine Learning prediction mechanisms to get accurate evaluations. We compare ADAPT with well known BFT protocols showing that it outperforms others as system conditions change and under dynamic workloads. © 2015 IEEE.

Aggregation protocols allow for distributed lightweight computations deployed on ad-hoc networks in a peer-to-peer fashion. Due to reliance on wireless technology, the communication medium is often hostile which makes such protocols susceptible to correctness and performance issues. In this paper, we study the behavior of aggregation protocols when subject to communication failures: message loss, duplication, and network partitions. We show that resolving communication failures at the communication layer, through a simple reliable communication layer, reduces the overhead of using alternative fault tolerance techniques at upper layers, and also preserves the original accuracy and simplicity of protocols. The empirical study we drive shows that tradeoffs exist across various aggregation protocols, and there is no one-size-fits-all protocol., The second author is supported by SMILES track of TEC4Growth project (NORTE-01-0145-FEDER-000020), and the third and forth authors are supported by EU H2020 LightKone project (732505).

Cryptocurrency and blockchain technologies are recently gaining wide adoption since the introduction of Bitcoin, being distributed, authority-free, and secure. Proof of Work (PoW) is at the heart of blockchain's security, asset generation, and maintenance. Although simple and secure, a hash-based PoW like Bitcoin's puzzle is often referred to as “useless”, and the used intensive computations are considered “waste” of energy. A myriad of Proof of “something” alternatives have been proposed to mitigate energy consumption; however, they either introduced new security threats and limitations, or the “work” remained far from being really “useful”. In this work, we introduce Proof of eXercise (PoX): a sustainable alternative to PoW where an eXercise is a real world matrix-based scientific computation problem. We provide a novel study of the properties of Bitcoin's PoW, the challenges of a more “rational” solution as PoX, and we suggest a comprehensive approach for PoX.