Optimizing Write Performance in Decentralized Personal Data Ecosystems

In the past 2 decades, the once decentralized web has become increasingly centralized. This centralization is bad for the web and its users, there is a need to decentralize the web again. The Solid initiative is one such decentralization initiative rapidly gaining support. The initiative strives to provide a personal data store to each user. These stores differ both in data stored by the user, and interface exposed. Heterogeneity is key for decentralization, but makes interacting with data stores complex for data consumers. There is a need to abstract these complexities, shielding consumers from the heterogeneity inherent to decentralization. Previous and ongoing research focusing on abstracting read queries proves to be successful. No research has been done to abstract updates to these data stores, but updates are essential to data management. In this PhD project, I focus on abstracting update queries over a permissioned decentralized environment, optimizing write performance. To do so, I research the requirements on interfaces, interface trade-offs, transactions, and query processing techniques. Future research will be able to refine the algorithms I propose and create alternatives. In research about read-queries, adaptive query planning seems promising. Future research might try to incorporate that idea in update-queries.