Biblio

Current Internet of Things (IoT) infrastructures, with its massive data requirements, rely on cloud storage: however, usage of a single cloud storage can place limitations on the IoT applications in terms of service requirements (performance, availability, security etc.). Multi-cloud storage architecture has been emerged as a promising infrastructure to solve this problem, but this approach has limited impact due to the lack of differentiation between competing cloud solutions. Multiple decentralized storage solutions (e.g., based on blockchains) are entering the market with distinct characteristics in terms of architecture, performance, security and availability and at a lower price compared to cloud storage. In this work, we introduce BlockAM: an adaptive middleware for the intelligent selection of storage technology for IoT applications, which jointly considers the cloud, multi-cloud and decentralized storage technologies to store large-scale IoT data. We model the cost-minimization storage selection problem and propose two heuristic algorithms: Dynamic Programming (DP) based algorithm and Greedy Style (GS) algorithm, for optimizing the choice of data storage based on IoT application's service requirements. We also employ blockchain to store IoT data on-chain in order to provide data integrity, auditability and accountability to the middleware architecture. Comparisons among the heuristic algorithms are conducted through extensive experiments, which demonstrates that DP heuristic and GS heuristic achieve up to 92% and 80% accuracy respectively. Moreover, the price associated with a specific IoT application data storage decrease by up to 31.2% by employing our middleware solution.

The success and growing popularity of blockchain technology has lead to a significant increase in load on popular permissionless blockchains such as Ethereum. With the current design, these blockchain systems do not scale with additional nodes since every node executes every transaction. Further efforts are therefore necessary to develop scalable permissionless blockchain systems. In this paper, we provide an aggregated overview of the current research on the Ethereum blockchain towards solving the scalability challenge. We focus on the concept of sharding, which aims to break the restriction of every participant being required to execute every transaction and store the entire state. This concept however introduces new complexities in the form of stateless clients, which leads to a new challenge: how to guarantee that critical data is published and stays available for as long as it is relevant. We present an approach towards solving the data availability problem (DAP) that leverages synergy effects by reusing the validators from Casper. We then propose two distinct approaches for reliable collation proposal, state transition, and state verification in shard chains. One approach is based on verification by committees of Casper validators that execute transactions in proposed blocks using witness data provided by executors. The other approach relies on a proof of execution provided by the executor proposing the block and a challenge game, where other executors verify the proof. Both concepts rely on executors for long-term storage of shard chain state.

Known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchain is seen as a disruptive technology capable of revolutionizing a wide variety of domains, ranging from finance to governance, by offering superior security, reliability, and transparency founded upon a decentralized and democratic computational model. In this tutorial, we first present the original Bitcoin design, along with Ethereum and Hyperledger, and reflect on their design choices through the academic lens. We further provide an overview of potential applications and associated research challenges, as well as a survey of ongoing research directions related to byzantine fault-tolerance consensus protocols. We highlight the new opportunities blockchain creates for building the next generation of secure middleware platforms and explore the possible interplay between AI and blockchains, or more specifically, how blockchain technology can enable the notion of "decentralized intelligence." We conclude with a walkthrough demonstrating the process of developing a decentralized application using a popular Smart Contract language (Solidity) over the Ethereum platform

Despite the very high volatility of the cryptocurrency markets, the interest in the development and adaptation of existing cryptocurrencies such as Bitcoin as well as new distributed ledger technologies is increasing. Therefore, understanding the security and vulnerability issues of such blockchain systems plays a critical role. In this work, we propose a configurable distributed simulation framework for analyzing Bitcoin-like blockchain systems which are based on Proof-of-Work protocols. The simulator facilitates investigating security properties of blockchain systems by enabling users to configure several characteristics of the blockchain network and executing different attack scenarios, such as double-spending attacks and flood attacks and observing the effects of the attacks on the blockchain network.