Capabilities and Limitations of Payment Channel Networks for Blockchain Scalability

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Constant-SNR, rate control and entropy coding for predictive lossy hyperspectral image compression

Predictive lossy compression has been shown to represent a very flexible framework for lossless and lossy onboard compression of multispectral and hyperspectral images with quality and rate control. In this paper, we improve predictive lossy compression in several ways, using a standard issued by the Consultative Committee on Space Data Systems, namely CCSDS-123, as an example of application. First, exploiting the flexibility in the error control process, we propose a constant-signal-to-noise-ratio algorithm that bounds the maximum relative error between each pixel of the reconstructed image and the corresponding pixel of the original image. This is very useful to avoid low-energy areas of the image being affected by large errors. Second, we propose a new rate control algorithm that has very low complexity and provides performance equal to or better than existing work. Third, we investigate several entropy coding schemes that can speed up the hardware implementation of the algorithm and, at the same time, improve coding efficiency. These advances make predictive lossy compression an extremely appealing framework for onboard systems due to its simplicity, flexibility, and coding efficiency

CLoTH: A Lightning Network Simulator

3noPayment-channel networks are one of the most promising solution to the well-known issue of blockchain scalability. In this work we present CLoTH, a simulator of the Lightning Network — the mainstream payment-channel network, used in Bitcoin. CLoTH simulates the execution of payments in a payment-channel network and produces performance measures such as the probability of payment success and the average payment time. To the best of our knowledge, CLoTH is the only simulator that faithfully reproduces the Lightning Network code functions, and this ensures the reliability of simulation results. In this work we provide a detailed description of the new, refactored, publicly-usable version of CLoTH, and we show simulations on the multi-path-payment feature, a recent Lightning Network feature that aims to minimize payment failures.openopenConoscenti, Marco; Vetrò, Antonio; De Martin, Juan CarlosConoscenti, Marco; Vetrò, Antonio; De Martin, Juan Carlo

Peer to Peer for Privacy and Decentralization in the Internet of Things

In the Internet of Things (IoT) era new connected devices will spread highly sensitive personal data. Sending this type of data to centralized companies represents a serious risk for people’s privacy, since economical or political interests could lead to an illegitimate use of personal information (as shown by Snowden’s revelations). With the purpose of overcoming such status-quo, our research goal is to develop software systems according to the notion of decentralized private-by-design IoT. The basic idea is that data produced by personal IoT devices are safely stored in a distributed system whose design guarantees privacy, leaving to the people -the real data owners- the decision of which of them to share and with whom. To achieve this goal, a possible solution is to leverage the use of Peer-to-Peer storage networks in combination with the blockchain. However, such architecture, despite promising, embeds still limitations, especially in terms of scalability. In this paper we discuss our research motivation, we describe our research idea applied in a possible scenario and we present the scalability problem

Combining Data Analytics with Team Feedback to Improve the Estimation Process in Agile Software Development

We apply a mixed research method to improve the user stories estimation process in a German company following agile software development. We combine software project data analytics with elicitation of teams' feedback, identify root causes for wrong estimates and propose an improved version of the estimation process. Three major changes are adopted in the new process: a shorter non numerical scale for story points, an analogy-based estimation process, and retrospectives analyses on the accuracy of previous sprints estimates. The new estimation process is applied on a new project, and an improvement of estimates accuracy from 10% to 45% is observed

Hubs, Rebalancing and Service Providers in the Lightning Network

Payment channel networks are the most developed proposal to address the well-known issue of blockchain scalability. Currently, the Lightning Network (LN) is the mainstream and most used payment channel network. In a previous work we introduced CLoTH, a payment channel network simulator we developed to analyze capabilities and limitations of such networks. In this work, using CLoTH, we present results of three groups of simulations on a recent snapshot of the LN, aimed to shed a light on the following aspects. Firstly, we investigated how hubs influence the LN performance. Then, we analyzed the effectiveness of two different channel rebalancing approaches, an active and a passive one. Eventually, we studied performance of the LN when a few service-providers nodes receive payments from the other network nodes, which is a typical use case of payment channel networks. We found that the LN is resilient to the removal of hubs, that our passive rebalancing approach reduces of about one fourth the payments failures due to channel unbalancing, and that in the service-providers scenario a consistent part of payments fails because channels directing to the service providers become unbalanced. Our work contributes to prove the strengthen of the Lightning Network when removing hubs and its weakness in the service-provider scenario. In addition, the passive rebalancing approach proposed in this work is a good candidate for the implementation in the Lightning Network protocol to mitigate channel unbalancing

The CLoTH Simulator for HTLC Payment Networks with Introductory Lightning Network Performance Results

The Lightning Network (LN) is one of the most promising off-chain scaling solutions for Bitcoin, as it enables off-chain payments which are not subject to the well-known blockchain scalability limit. In this work, we introduce CLoTH, a simulator for HTLC payment networks (of which LN is the best working example). It simulates input-defined payments on an input-defined HTLC network and produces performance measures in terms of payment-related statistics (such as time to complete payments and probability of payment failure). CLoTH helps to predict issues and obstacles that might emerge in the development stages of an HTLC payment network and to estimate the effects of an optimisation action before deploying it. We conducted simulations on a recent snapshot of the HTLC payment network of LN. These simulations allowed us to identify network and payments configurations for which a payment is more likely to fail than to succeed. We proposed viable solutions to avoid such configurations