The study of shared memory concurrency is extensive. There exist many state-of-the-art strategies for dealing with fundamental concurrency problems, such as race conditions or deadlocks, to leverage massive performance boosts out of modern multiprocessors. With the introduction of blockchain technology as a popular financial tool, we observe many decades-old concurrency problems re-emerge within the context of decentralized networks. These challenges introduce additional constraints, such as the lack of hardware atomic instructions like Compare-And-Swap, or the potential for malicious clients to join the network. In this dissertation, we propose key algorithms which adapt knowledge from the domain of shared memory concurrency to solve emerging concurrency problems in decentralized networks. We propose three key algorithms which further the state of the art in decentralized networks. (1) We present Hash-Mark-Set, a concurrent algorithm for providing a read-uncommitted view of the blockchain state, enabling a higher success rate in transaction use cases where state changes frequently in relation to the block interval. (2) We propose Proof of Descriptor, a descriptor based consensus mechanism for decentralized networks. Proof of Descriptor utilizes well-known techniques from shared memory concurrent programming to create an efficient and scalable algorithm for blockchain consensus. (3) We propose a descriptor-based algorithm for concurrent execution of smart contracts that efficiently captures the concurrent execution as a graph of descriptors, enabling validators to analyze the concurrent execution and verify its results through re-execution.