Biblio

Distributed ledger technologies (DLTs) based on Directed Acyclic Graphs (DAGs) have been gaining much attention due to their performance advantage over the traditional blockchain. IOTA is an example of DAG-based DLT that has shown its significance in the Internet of Things (IoT) environment. Despite that, IOTA is vulnerable to double-spend attacks, which threaten the immutability of the ledger. In this paper, we propose an efficient yet simple method for detecting a parasite chain, which is one form of attempting a double-spend attack in the IOTA network. In our method, a score function measuring the importance of each transaction in the IOTA network is employed. Any abrupt change in the importance of a transaction is reflected in the 1st and 2nd order derivatives of this score function, and therefore used in the calculation of an anomaly score. Due to how the score function is formulated, this anomaly score can be used in the detection of a particular type of parasite chain, characterized by sudden changes in the in-degree of a transaction in the IOTA graph. The experimental results demonstrate that the proposed method is accurate and linearly scalable in the number of edges in the network.

Blockchain is seen as a promising technology to provide reliable and secure services due to its decentralized characteristic. However, because of the limited throughput, current blockchain platforms can not meet the transaction demand in practical use. Though researchers proposed many new solutions, they suffered either decentralization or security issues. In this paper, using Directed Acyclic Graph (DAG) structure, we improve the linear structure of traditional blockchain protocol. In the new structure, blocks are organized in levels and width, which will generate into a compacted DAG structure (CoDAG). To make CoDAG more efficient and secure, we design algorithms and protocols to place the new-generated blocks appropriately. Compared with traditional blockchain protocols, CoDAG improves the security and transaction verification time, and enjoys the consistency and liveness properties of blockchain. Taking adversary parties into consideration, two possible attack strategies are presented in this paper, and we further prove that CoDAG is a secure and robust protocol to resist them. The experimental results show that CoDAG can achieve 394 transactions per second, which is 56 times of Bitcoin's throughput and 26 times of Ethereum's.

Time and cost are the most critical performance metrics for computer systems including embedded system, especially for the battery-based embedded systems, such as PC, mainframe computer, and smart phone. Most of the previous work focuses on saving energy in a deterministic way by taking the average or worst scenario into account. However, such deterministic approaches usually are inappropriate in modeling energy consumption because of uncertainties in conditional instructions on processors and time-varying external environments. Through studying the relationship between energy consumption, execution time and completion probability of tasks on heterogeneous multi-core architectures this paper proposes an optimal energy efficiency and system performance model and the OTHAP (Optimizing Task Heterogeneous Assignment with Probability) algorithm to address the Processor and Voltage Assignment with Probability (PVAP) problem of data-dependent aperiodic tasks in real-time embedded systems, ensuring that all the tasks can be done under the time constraint with areal-time embedded systems guaranteed probability. We adopt a task DAG (Directed Acyclic Graph) to model the PVAP problem. We first use a processor scheduling algorithm to map the task DAG onto a set of voltage-variable processors, and then use our dynamic programming algorithm to assign a proper voltage to each task and The experimental results demonstrate our approach outperforms state-of-the-art algorithms in this field (maximum improvement of 24.6%).