TrustZone as a trusted execution environment (TEE) has been proven to preserve the confidentiality of blockchain transactions supported by smart contracts. Despite some academic effort, TrustZone can only support limited languages for now. The lack of the corresponding execution environment for smart contracts seriously hinders blockchain applications from directly running on TrustZone. In this paper, we design the first virtual execution environment named TSC-VEE for performing Solidity smart contracts on TrustZone, to the best of our knowledge. TSC-VEE can be decomposed into fourfold: (1) an instruction set adapted to the isolation and world switching mechanism of TrustZone. (2) a runtime memory management mechanism that provides a pair of instructions with the corresponding processing mechanism to allocate and release the work memory. (3) a hybrid granularity resource analysis algorithm which computes and records the value of maximum stack height and static gas cost through bytecode pre-execution, avoiding runtime overflow and invalid computations. (4) a cross-isolation-environment prefetching approach that supports loading and storing the storage data from the normal world into the secure world on TrustZone before execution, thus avoiding switching the world state frequently at runtime. Extensive experimental results show that TSC-VEE can perform smart contracts correctly and efficiently on TrustZone. Compared with the most commonly used Ethereum client—Geth, TSC-VEE achieves execution performance improvements by$9.29\times$. We also implement the Ethereum virtual machine—evmoneon TrustZone. TSC-VEE can reduce the latency by 12.63% with our optimization techniques, and decrease the work memory footprint by 22.95% on average when executing various scale contracts.

With the development of information technology, a growing number of users begin to use Internet as a platform to plan their itinerary collaboratively. During the online itinerary planning process, collaboration plays an increasingly significant role. As the number of users grows, it is challenging to support more and more participants to plan itineraries online collaboratively, due to the requirement of responsiveness and data consistency. Traditional concurrency control methods (e.g. lock-based protocols, etc.) are costly because their primary copies are on a dedicated server and network latency, and concurrent operations violate CCI model. Address Space Transformation (AST) proves to the high performance in addressing the issue of interactive responsiveness and consistency maintenance. In this paper, a novel AST based approach is presented to support collaborative itinerary planning. We report how we address the emerging consistency maintenance challenges in directed graph of online itinerary planning. With this method, users are allowed to participate and leave itinerary planning tasks anytime. Moreover, collaborative itinerary planning also can be modified in real time with data consistent guarantees. A system called CLIP is implemented to evaluate its performance. Experimental results demonstrate the benefit and performance of this approach over the existing methods.

The visualization of complex physical processes is becoming a challenging topic in fields of information visualization, and attracting more and more researchers. Microstructure evolution visualization (MEV) has become an important and unsubstitutable method in the modern material processing engineering domains. A novel MEV approach combining the neutrosophic set theory (NS) and the cellular automaton technique (CA) is developed in order to precisely simulate the invisible, complex and unrepeatable physical process of metal solidification. The NS theory is applied to realize the complex evolution rules among three phases including solid phase, liquid phase and interface phase, while the CA method is used to simulate the dynamic process of dendrite growth. Experiment results of the dendrite growing simulation show strange consistency of the virtual invisible microstructure with that in practical industrial trials and production. Material experts also convince the statistical characteristics of the simulation results and further the inspirational value for the visualization of other complex physical processes.