This paper presents a distributed random linear network coding approach for transmitting and compressing information in general multisource multicast networks. The approach involves network nodes independently and randomly selecting linear mappings from inputs onto output links over a finite field. The authors show that this method achieves capacity with probability exponentially approaching 1 as the code length increases. Additionally, random linear coding performs compression when necessary, generalizing error exponents for linear Slepian–Wolf coding. The benefits of this approach include decentralized operation and robustness to network changes or link failures. The paper also demonstrates how this approach can take advantage of redundant network capacity to improve success probability and robustness. Two practical scenarios—distributed network operation and networks with dynamically varying connections—are used to illustrate the advantages of random linear network coding over routing. The paper provides a new bound on the required field size for centralized network coding on general multicast networks and discusses the potential applications and future research directions.This paper presents a distributed random linear network coding approach for transmitting and compressing information in general multisource multicast networks. The approach involves network nodes independently and randomly selecting linear mappings from inputs onto output links over a finite field. The authors show that this method achieves capacity with probability exponentially approaching 1 as the code length increases. Additionally, random linear coding performs compression when necessary, generalizing error exponents for linear Slepian–Wolf coding. The benefits of this approach include decentralized operation and robustness to network changes or link failures. The paper also demonstrates how this approach can take advantage of redundant network capacity to improve success probability and robustness. Two practical scenarios—distributed network operation and networks with dynamically varying connections—are used to illustrate the advantages of random linear network coding over routing. The paper provides a new bound on the required field size for centralized network coding on general multicast networks and discusses the potential applications and future research directions.