Optimal endorsement for network-wide distributed blockchains

Blockchains offer trust and immutability in non-trusted environments, but most are not fast enough for latency-sensitive applications. Hyperledger Fabric (HF) is a common enterprise-level platform that is being offered as Blockchain-as-a-Service (BaaS) by cloud providers. In HF, every new transaction requires a preliminary endorsement by multiple mutually untrusted parties called organizations, which contributes to the delay in storing the transaction in the blockchain. The endorsement policy is specific to each application and defines the required approvals by the endorser peers (EPs) of the involved organizations. In this paper, given an input endorsement policy, we studied the optimal choice to distribute the endorsement requests to the proper EPs. We proposed the OPEN algorithm, devised to minimize the latency due to both network delays and the processing times at the EPs. By extensive simulations, we showed that OPEN can reduce the endorsement latency up to 70% compared to the state-of-the-art solution and approximated well the introduced optimal policies while offering a negligible implementation overhead compared to them

Data plane assisted state replication with Network Function Virtualization

Modern 5G networks are capable of providing ultra-low latency and highly scalable network services by employing modern networking paradigms such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). The latter enables performance-critical network applications to be run in a distributed fashion directly inside the infrastructure. Being distributed, those applications rely on sophisticated state replication algorithms to synchronize states among each other. Nevertheless, current implementations of such algorithms do not fully exploit the potential of the modern infrastructures, thus leading to sub-optimal performance. In this paper, we propose STARE, a novel state replication system tailored for 5G networks. At its core, STARE exploits stateful SDN to offload replication-related processes to the data plane, ultimately leading to reduced communication delays and processing overhead for VNFs. We provide a detailed description of the STARE architecture alongside a publicly-available P4- based implementation. Furthermore, our evaluation shows that STARE is capable of scaling to big networks while introducing low overhead in the network