The blooming trend of smart grid deployment is engaged by the evolution of the network technology, as the connected environment offers various alternatives for electrical data collections. Having diverse data sharing/transfer means is deemed an important aspect in enabling intelligent controls/governance in smart grid. However, security and privacy concerns also are introduced while flexible communication services are provided, such as energy depletion and infrastructure mapping attacks. This work proposes a model Permissioned Blockchain Edge Model for Smart Grid Network (PBEM-SGN) to address the two significant issues in smart grid, privacy protections and energy security, by means of combining blockchain and edge computing techniques. We use group signatures and covert channel authorization techniques to guarantee users’ validity. An optimal security-aware strategy is constructed by smart contracts running on the blockchain. Our experiments have evaluated the effectiveness of the proposed approach.

Blockchain technology has been deemed to be an ideal choice for strengthening existing computing systems in varied manners. As one of the network-enabled technologies, cloud computing has been broadly adopted in the industry through numerous cloud service models. Fusing blockchain technology with existing cloud systems has a great potential in both functionality/ performance enhancement and security/ privacy improvement. The question remains on how blockchain technology inserts into current deployed cloud solutions and enables the reengineering of cloud datacenter. This survey addresses this issue and investigates recent efforts in the technical fusion of blockchain and clouds. Three technical dimensions roughly are covered in this work. First, we concern the service model and review an emerging cloud-relevant blockchain service model, Blockchain-as-a-Service (BaaS); second, security is considered a key technical dimension in this work and both access control and searchable encryption schemes are assessed; finally, we examine the performance of cloud datacenter with supports/ participance of blockchain from hardware and software perspectives. Main findings of this survey will be theoretical supports for future reference of blockchain-enabled reengineering of cloud datacenter.

Green cloud is an emerging new technology in the computing world in which memory is a critical component. Phase-change memory (PCM) is one of the most promising alternative techniques to the dynamic random access memory (DRAM) that faces the scalability wall. Recent research has been focusing on the multi-level cell (MLC) of PCM. By precisely arranging multiple levels of resistance inside a PCM cell, more than one bit of data can be stored in one single PCM cell. However, the MLC PCM suffers from the degradation of performance compared to the single-level cell(SLC) PCM, due to the longer memory access time. In this paper, we present a genetic-based optimization algorithm for chip multiprocessor (CMP) equipped with PCM memory in green clouds. The proposed genetic-based algorithm not only schedules and assigns tasks to cores in the CMP system, but also provides a PCM MLC configuration that balances the PCM memory performance as well as the efficiency. The experimental results show that our genetic-based algorithm can significantly reduce the maximum memory usage by 76.8 percent comparing with the uniform SLC configuration, and improve the efficiency of memory usage by 127 percent comparing with the uniform 4 bits/cell MLC configuration. Moreover, the performance of the system is also improved by 24.5 percent comparing with the uniform 4 bits/cell MLC configuration in terms of total execution time.