Transactive microgrids are emerging as a transformative solution for the problems faced by distribution system operators due to an increase in the use of distributed energy resources and a rapid acceleration in renewable energy generation, such as wind and solar power. Distributed ledgers have recently found widespread interest in this domain due to their ability to provide transactional integrity across decentralized computing nodes. However, the existing state of the art has not focused on the privacy preservation requirement of these energy systems -- the transaction level data can provide much greater insights into a prosumer's behavior compared to smart meter data. There are specific safety requirements in transactive microgrids to ensure the stability of the grid and to control the load. To fulfil these requirements, the distribution system operator needs transaction information from the grid, which poses a further challenge to the privacy-goals. This problem is made worse by requirement for off-blockchain communication in these networks. In this paper, we extend a recently developed trading workflow called PETra and describe our solution for communication and transactional anonymity.
The Bitcoin payment system involves two agent types: Users that transact with the currency and pay fees and miners in charge of authorizing transactions and securing the system in return for these fees. Two of Bitcoin's challenges are (i) securing sufficient miner revenues as block rewards decrease, and (ii) alleviating the throughput limitation due to a small maximal block size cap. These issues are strongly related as increasing the maximal block size may decrease revenue due to Bitcoin's pay-your-bid approach. To decouple them, we analyze the “monopolistic auction” [8], showing: (i) its revenue does not decrease as the maximal block size increases, (ii) it is resilient to an untrusted auctioneer (the miner), and (iii) simplicity for transaction issuers (bidders), as the average gain from strategic bid shading (relative to bidding one's true maximal willingness to pay) diminishes as the number of bids increases.
The Spanish National Health System (SNHS) was legally defined in 1986. There are many well documented studies on how its basic traits (universality, accessibility, decentralization, integrated public health networks, public and private provision, financed by taxes, social premiums and copayments, etc.) have evolved since then.
This paper explains how the SNHS facilities and functions are deeply decentralized and how the recent economic crisis has changed this picture, with central health planning basically located into the Ministry of Finance and mainly guided by deficit control considerations.
Blockchain systems are designed to produce blocks at a constant average rate. The most popular systems currently employ a Proof of Work (PoW) algorithm as a means of creating these blocks. Bitcoin produces, on average, one block every 10 minutes. An unfortunate limitation of all deployed PoW blockchain systems is that the time between blocks has high variance. For example, 5% of the time, Bitcoin's inter-block time is at least 40 minutes. This variance impedes the consistent flow of validated transactions through the system. We propose an alternative process for PoW-based block discovery that results in an inter-block time with significantly lower variance. Our algorithm, called Bobtail, generalizes the current algorithm by comparing the mean of the k lowest order statistics to a target. We show that the variance of inter-block times decreases as k increases. If our approach were applied to Bitcoin, about 80% of blocks would be found within 7 to 12 minutes, and nearly every block would be found within 5 to 18 minutes; the average inter-block time would remain at 10 minutes. Further, we show that low-variance mining significantly thwarts doublespend and selfish mining attacks. For Bitcoin and Ethereum currently (k=1), an attacker with 40% of the mining power will succeed with 30% probability when the merchant sets up an embargo of 8 blocks; however, when k>=20, the probability of success falls to less than 1%. Similarly, for Bitcoin and Ethereum currently, a selfish miner with 40% of the mining power will claim about 66% of blocks; however, when k>=5, the same miner will find that selfish mining is less successful than honest mining. The cost of our approach is a larger block header.
Bitcoin time series dataset recording individual transactions denominated in Euro at the COINBASE market between April 23, 2015 and August 15, 2016 is analyzed. Markov switching model is applied to classify the regions of varying volatility represented by three hidden state regimes using univariate autoregressive model and dependent mixture model. Causality extraction and price prediction of daily BTCEUR exchange rates is performed by means of a recurrent neural network using the standard Elman model. Strong correlations is found between the normalized mean squared error of the Elman network (out-of-sample 5-day-ahead prediction) and the realized volatility (sum of minute returns squared throughout the trading day). The present approach is calibrated using simulated regime change in standard econometric models. Our results clearly demonstrate the applicability of recurrent neural networks to causality extraction even in the case of highly volatile cryptocurrency exchange rate time series data.
Andrea Pinna, Roberto Tonelli, Matteo Orrú, Michele Marchesi
A Blockchain is a global shared infrastructure where cryptocurrency transactions among addresses are recorded, validated and made publicly available in a peer- to-peer network. To date the best known and important cryptocurrency is the bitcoin. In this paper we focus on this cryptocurrency and in particular on the modeling of the Bitcoin Blockchain by using the Petri Nets formalism. The proposed model allows us to quickly collect information about identities owning Bitcoin addresses and to recover measures and statistics on the Bitcoin network. By exploiting algebraic formalism, we reconstructed an Entities network associated to Blockchain transactions gathering together Bitcoin addresses into the single entity holding permits to manage Bitcoins held by those addresses. The model allows also to identify a set of behaviours typical of Bitcoin owners, like that of using an address only once, and to reconstruct chains for this behaviour together with the rate of firing. Our model is highly flexible and can easily be adapted to include different features of the Bitcoin crypto-currency system.
Joshua Skewes, Dorthe Døjbak Håkonsson, Trine Bilde, Andreas Roepstorff
Collaborative decision making is central to the organization of society. Juries deliberate cases, voters elect government officials, open innovation networks converge on innovative solutions. It is common to think of such groups as decision making entities. But this language is imprecise. Real decision processes do not occur within any group or organization as an abstract entity. Collaborative decision making happens within and between autonomous individuals. This emphasizes the importance of the relationships between individual and social decision-making processes to social organization. Despite a rich body of literature on collaborative decision making we know little about how individuals decide to commit to group decision making in the first place, and how, once joined, they communicate their distributed information for optimal group performance. We introduce a general framework designed to model collaborative decision processes. Our main results are that 1) commitment and gain is enhanced when groups are designed so agents have realistic knowledge about the forgone gains and losses associated with abstaining from the group; and 2) that this effect is accelerated when communication between group members conveys more information about individual preferences. We thus demonstrate that collaborative decision making is done best when it is done by groups that are informationally open.
This letter revisits the informational efficiency of the Bitcoin market. In particular we analyze the time-varying behavior of long memory of returns on Bitcoin and volatility 2011 until 2017, using the Hurst exponent. Our results are twofold. First, R/S method is prone to detect long memory, whereas DFA method can discriminate more precisely variations in informational efficiency across time. Second, daily returns exhibit persistent behavior in the first half of the period under study, whereas its behavior is more informational efficient since 2014. Finally, price volatility, measured as the logarithmic difference between intraday high and low prices exhibits long memory during all the period. This reflects a different underlying dynamic process generating the prices and volatility.
Hyperledger Fabric (HLF) is a flexible permissioned blockchain platform designed for business applications beyond the basic digital coin addressed by Bitcoin and other existing networks. A key property of HLF is its extensibility, and in particular the support for multiple ordering services for building the blockchain. Nonetheless, the version 1.0 was launched in early 2017 without an implementation of a Byzantine fault-tolerant (BFT) ordering service. To overcome this limitation, we designed, implemented, and evaluated a BFT ordering service for HLF on top of the BFT-SMaRt state machine replication/consensus library, implementing also optimizations for wide-area deployment. Our results show that HLF with our ordering service can achieve up to ten thousand transactions per second and write a transaction irrevocably in the blockchain in half a second, even with peers spread in different continents.
Ghana’s industrial sector has evolved with the various stages of political and economic reforms since independence in 1957. Efforts to decentralize its key institutions to enhance economic growth has seen very little success especially in the area of linking industries to local institutions. Recently, the economy has been dampened by worsening macroeconomic environment, huge regional disparities and power crises. A number of policy and programme initiatives by the government have been undertaken especially in the area of revamping the local economies through the existing decentralized systems. This paper presents a critical review of the role of decentralized institutions in industrialisation in Ghana. The paper utilises annual data from the Ministry of Finance and Ghana Statistical Service from 1981 to date to show trends in growth patterns in the selected indicators.Despite key interventions, some regions in Ghana have failed to develop. The envisioned industrial geographical dispersion has not been realised as we find many Ghanaian industries concentrated in a few regions. The paper highlights the challenges facing Ghana’s decentralized institutions and identifies the opportunities that can catalyse the growth of Ghana’s industrial sector if key policy strategic reforms are undertaken. An industrial-led growth will ensure that the manufacturing sub-sector will be boosted to improve production and provide jobs. Industrialisation has been projected at the forefront of government’s development agenda. The paper provides a review that highlights the need to support decentralised institutions to enable them stimulate investment in industrial sector.
The bitcoin peer-to-peer network has drawn significant attention from researchers, but so far has mostly focused on publicly visible portions of the network, i.e., publicly reachable peers. This mostly ignores the hidden parts of the network: unreachable Bitcoin peers behind NATs and firewalls. In this paper, we characterize Bitcoin peers that might be behind NATs or firewalls from different perspectives. Using a special-purpose measurement tool we conduct a large scale measurement study of the Bitcoin network, and discover several previously unreported usage patterns: a small number of peers are involved in the propagation of 89% of all bitcoin transactions, public cloud services are being used for Bitcoin network probing and crawling, a large amount of transactions are generated from only two mobile applications. We also empirically evaluate a method that uses timing information to re-identify the peer that created a transaction against unreachable peers. We find this method very accurate for peers that use the latest version of the Bitcoin Core client.
Representing the semantic relations that exist between two given words (or entities) is an important first step in a wide-range of NLP applications such as analogical reasoning, knowledge base completion and relational information retrieval. A simple, yet surprisingly accurate method for representing a relation between two words is to compute the vector offset (\PairDiff) between the corresponding word embeddings. Despite its empirical success, it remains unclear whether \PairDiff is the best operator for obtaining a relational representation from word embeddings. In this paper, we conduct a theoretical analysis of the \PairDiff operator. In particular, we show that for word embeddings where cross-dimensional correlations are zero, \PairDiff is the only bilinear operator that can minimise the $\ell_{2}$ loss between analogous word-pairs. We experimentally show that for word embedding created using a broad range of methods, the cross-dimensional correlations in word embeddings are approximately zero, demonstrating the general applicability of our theoretical result. Moreover, we empirically verify the implications of the proven theoretical result in a series of experiments where we repeatedly discover \PairDiff as the best bilinear operator for representing semantic relations between words in several benchmark datasets.
Agung Ridwan, Syaparuddin Syaparuddin, Candra Mustika
This study aims to analyze: 1) sources of financing for fiscal decentralization, GRDP and poverty levels of regencies / cities in Jambi Province (2) the effect of sources of fiscal decentralization financing on gross domestic product in regencies and cities in Jambi Province (3) the effect of fiscal decentralization financing sources towards poverty levels in regencies and cities in Jambi Province. The analysis period is 2007 - 2013. To analyze the influence of the sources of fiscal decentralization funding on GRDP and poverty levels, using two panel data regression models. The results of the analysis found that: 1) During the 2007-2013 period, the sources of financing for fiscal decentralization consisting of Local Original Revenue, Balanced Funds and Other Other Income in regencies and cities in Jambi Province generally increased every year; 2) The GRDP regency-city growth in Jambi Province is fairly high with an average of 6.83%, higher than the national economic growth; 3) In general, the poverty rate of regencies/cities in Jambi Province has decreased significantly every year during the period 2007 – 2013. Original Regional Revenue and other legitimate income have a negative and significant effect while the balance fund does not have a significant effect on the poverty level of regencies/cities in Jambi Province.
Stefanie Roos, Pedro Moreno-Sanchez, Aniket Kate, Ian Goldberg
Path-based transaction (PBT) networks, which settle payments from one user to another via a path of intermediaries, are a growing area of research. They overcome the scalability and privacy issues in cryptocurrencies like Bitcoin and Ethereum by replacing expensive and slow on-chain blockchain operations with inexpensive and fast off-chain transfers. In the form of credit networks such as Ripple and Stellar, they also enable low-price real-time gross settlements across different currencies. For example, SilentWhsipers is a recently proposed fully distributed credit network relying on path-based transactions for secure and in particular private payments without a public ledger. At the core of a decentralized PBT network is a routing algorithm that discovers transaction paths between payer and payee. During the last year, a number of routing algorithms have been proposed. However, the existing ad hoc efforts lack either efficiency or privacy. In this work, we first identify several efficiency concerns in SilentWhsipers. Armed with this knowledge, we design and evaluate SpeedyMurmurs, a novel routing algorithm for decentralized PBT networks using efficient and flexible embedding-based path discovery and on-demand efficient stabilization to handle the dynamics of a PBT network. Our simulation study, based on real-world data from the currently deployed Ripple credit network, indicates that SpeedyMurmurs reduces the overhead of stabilization by up to two orders of magnitude and the overhead of routing a transaction by more than a factor of two. Furthermore, using SpeedyMurmurs maintains at least the same success ratio as decentralized landmark routing, while providing lower delays. Finally, SpeedyMurmurs achieves key privacy goals for routing in PBT networks.
Secret sharing is an important component of cryptography protocols and has a wide range of practical applications. However, the existing secret sharing schemes cannot apply to computationally weak devices and cannot efficiently guarantee fairness. In this study, a novel outsourcing secret sharing scheme is proposed. In the setting of outsourcing secret sharing, clients only need a small amount of decryption and verification operations, while the expensive reconstruction computation and verifiable computation can be outsourced to cloud service providers (CSP). The scheme does not require complex interactive argument or zero‐knowledge proof. The malicious behaviour of clients and CSP can be detected in time. Moreover, the CSP cannot get any useful information about the secret, and it is fair for every client to obtain the secret. At the end of this study, the authors prove the security of the proposed scheme and compare it with other secret sharing schemes.
Stefanie Roos, Pedro Moreno-Sánchez, Aniket Kate, Ian Goldberg
Path-based transaction (PBT) networks, which settle payments from one user to\nanother via a path of intermediaries, are a growing area of research. They\novercome the scalability and privacy issues in cryptocurrencies like Bitcoin\nand Ethereum by replacing expensive and slow on-chain blockchain operations\nwith inexpensive and fast off-chain transfers. In the form of credit networks\nsuch as Ripple and Stellar, they also enable low-price real-time gross\nsettlements across different currencies. For example, SilentWhsipers is a\nrecently proposed fully distributed credit network relying on path-based\ntransactions for secure and in particular private payments without a public\nledger. At the core of a decentralized PBT network is a routing algorithm that\ndiscovers transaction paths between payer and payee. During the last year, a\nnumber of routing algorithms have been proposed. However, the existing ad hoc\nefforts lack either efficiency or privacy. In this work, we first identify\nseveral efficiency concerns in SilentWhsipers. Armed with this knowledge, we\ndesign and evaluate SpeedyMurmurs, a novel routing algorithm for decentralized\nPBT networks using efficient and flexible embedding-based path discovery and\non-demand efficient stabilization to handle the dynamics of a PBT network. Our\nsimulation study, based on real-world data from the currently deployed Ripple\ncredit network, indicates that SpeedyMurmurs reduces the overhead of\nstabilization by up to two orders of magnitude and the overhead of routing a\ntransaction by more than a factor of two. Furthermore, using SpeedyMurmurs\nmaintains at least the same success ratio as decentralized landmark routing,\nwhile providing lower delays. Finally, SpeedyMurmurs achieves key privacy goals\nfor routing in PBT networks.\n
New cryptocurrencies are emerging almost daily, and many interested parties are wondering whether central banks should issue their own versions. But what might central bank cryptocurrencies (CBCCs) look like and would they be useful? This feature provides a taxonomy of money that identifies two types of CBCC – retail and wholesale – and differentiates them from other forms of central bank money such as cash and reserves. It discusses the different characteristics of CBCCs and compares them with existing payment options.
Sep 15, 2017·Lydia Y. Chen; Hans P. Reiser. Proc. of 17th IFIP Distributed Applications and Interoperable Systems, Jun 2017, Neuch{â}tel, Switzerland. Springer, 10320, pp.34-48, 2017, LNCS - Lecture Notes in Computer Science
Most online lotteries today fail to ensure the verifiability of the random process and rely on a trusted third party. This issue has received little attention since the emergence of distributed protocols like Bitcoin that demonstrated the potential of protocols with no trusted third party. We argue that the security requirements of online lotteries are similar to those of online voting, and propose a novel distributed online lottery protocol that applies techniques developed for voting applications to an existing lottery protocol. As a result, the protocol is scalable, provides efficient verification of the random process and does not rely on a trusted third party nor on assumptions of bounded computational resources. An early prototype confirms the feasibility of our approach.
Ministry of National Development Planning, Alen Ermanita
For more than a decade, Indonesia has been practicing decentralization. During this period, local governments still experience difficulties in generating local revenues to fund their development. Local government bonds (LGBs) are actually one of the finest sources for financing local development. However, until now there is no real practice in issuing local bonds in Indonesia though it is allowed in the existing regulation. There are still many considerations which hindered the realization of LGB issuance ranging from the rule of mechanism to the local governments’ readiness themselves. To gain more insights about the issue, learning from another country (in this case: Japan) on how they manage LGBs effectively and securely will be beneficial. Comparison model between the two countries is chosen to see the regulation and managerial aspects in LGB implementation including the main institution in central level, rules of the game, buyers and purposes. By having this comparison, it is expected that some crucial factors can be looked at, which may then provide us some information on why LGBs are yet to bloom in Indonesia. Moreover, the comparison is expected to provide some basics about the possibility to ease policy adoption for Indonesia in managing LGBs.
As the core of intelligent manufacturing, cyber-physical systems (CPS) have serious security issues, especially for the communication security of their terminal machine-to-machine (M2M) communications. In this paper, blockchain technology is introduced to address such a security problem of communications between different types of machines in the CPS. According to the principles of blockchain technology, we designed a blockchain for secure M2M communications. As a communication system, M2M consists of public network areas, device areas, and private areas, and we designed a sophisticated blockchain structure between the public area and private area. For validating our design, we took cotton spinning production as a case study to demonstrate our solution to M2M communication problems under the CPS framework. We have demonstrated that the blockchain technology can effectively solve the safety of expansion of machines in the production process and the communication data between the machines cannot be tampered with.
Nicolás Pérez-Mora, Federico Bava, Martin Andersen, Chris Bales · 8 authors
Both district heating and solar collector systems have been known and implemented for many years. However, the combination of the two, with solar collectors supplying heat to the district heating network, is relatively new, and no comprehensive review of scientific publications on this topic could be found. Thus, this paper summarizes the literature available on solar district heating and presents the state of the art and real experiences in this field. Given the lack of a generally accepted convention on the classification of solar district heating systems, this paper distinguishes centralized and decentralized solar district heating as well as block heating. For the different technologies, the paper describes commonly adopted control strategies, system configurations, types of installation, and integration. Real-world examples are also given to provide a more detailed insight into how solar thermal technology can be integrated with district heating. Solar thermal technology combined with thermally driven chillers to provide cooling for cooling networks is also included in this paper. In order for a technology to spread successfully, not only technical but also economic issues need to be tackled. Hence, the paper identifies and describes different types of ownership and financing schemes currently used in this field.
Open access
Integrated Energy Systems Optimization
Solar Thermal and Photovoltaic Systems
Thermodynamic and Exergetic Analyses of Power and Cooling Systems
Privacy risk assessments aim to analyze and quantify the privacy risks associated with new systems. As such, they are critically important in ensuring that adequate privacy protections are built in. However, current methods to quantify privacy risk rely heavily on experienced analysts picking the "correct" risk level on e.g. a five-point scale. In this paper, we argue that a more scientific quantification of privacy risk increases accuracy and reliability and can thus make it easier to build privacy-friendly systems. We discuss how the impact and likelihood of privacy violations can be decomposed and quantified, and stress the importance of meaningful metrics and units of measurement. We suggest a method of quantifying and representing privacy risk that considers a collection of factors as well as a variety of contexts and attacker models. We conclude by identifying some of the major research questions to take this approach further in a variety of application scenarios.
This work bridges the technical concepts underlying distributed computing and blockchain technologies with their profound socioeconomic and sociopolitical implications, particularly on academic research and the healthcare industry. Several examples from academia, industry, and healthcare are explored throughout this paper. The limiting factor in contemporary life sciences research is often funding: for example, to purchase expensive laboratory equipment and materials, to hire skilled researchers and technicians, and to acquire and disseminate data through established academic channels. In the case of the U.S. healthcare system, hospitals generate massive amounts of data, only a small minority of which is utilized to inform current and future medical practice. Similarly, corporations too expend large amounts of money to collect, secure and transmit data from one centralized source to another. In all three scenarios, data moves under the traditional paradigm of centralization, in which data is hosted and curated by individuals and organizations and of benefit to only a small subset of people.