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Our model includes a more lightweight execution engine for network microservices and a network scheduling framework to configure network processing elements to process streams and direct the appropriate traffic to them. In this article, we describe INDIANA, a complete framework for in-network microservices. We will describe how the two components-the INDIANA network Processing Element (InPE) and the Flange Network Operating System (NOS)-work together to achieve effective in-network processing to improve performance in edge to cloud environments. Our processing elements provide lightweight compute units optimized for efficient stream processing. These elements are customizable and vary in sophistication and resource consumption. The Flange NOS provides first-class flow based reasoning to drive function placement, network configuration, and load balancing that can respond dynamically to network conditions. We describe design considerations and discuss our approach and implementations. We evaluate the performance of stream processing and examine the performance of several exemplar applications on networks of increasing scale and complexity. <\/jats:p>","DOI":"10.1177\/10943420231179662","type":"journal-article","created":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T12:56:17Z","timestamp":1687784177000},"page":"442-461","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["INDIANA\u2014In-Network Distributed Infrastructure for Advanced Network Applications"],"prefix":"10.1177","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2264-8516","authenticated-orcid":false,"given":"Sabra","family":"Ossen","sequence":"first","affiliation":[{"name":"Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 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