Gossip-Based Monitoring Protocol for 6G Networks

Abstract

The service function (SF) area has gained increasing attention in the last years due its ability to combine the advantages of cloud computing with network softwarization. By decoupling SFs from the physical equipment where they are executed, it is possible to make network services scalable and flexible. These advantages become even more evident in the forthcoming 6G networks, where the overall environment is expected to become more dynamic and cloud-based, with SFs deployed as cloud-native functions. However, in order to efficiently manage and compose services using these SFs, it is necessary to monitor the available resources of the nodes where they can be deployed, in addition to exchange information relevant to the operational status of active SFs. To this aim, we propose a lightweight monitoring architecture by using agents in charge of monitoring the status of SFs running in co-located clusters. These monitoring agents exchange their information by means of a gossip protocol, which allows increasing the reliability of the process. In this way, it is possible to keep service decisions as local as possible, limiting the interactions with centralized decision and orchestration platforms, and thus increasing network scalability and responsiveness. Performance evaluation shows the effectiveness of the proposed solution, and demonstrates that the network overhead of the distributed monitoring process is definitely affordable.

Distributed Average Consensus Algorithms in d-Regular Bipartite Graphs: Comparative Study

“…As seen in the literature [16][17][18][19], the application of data aggregation is beneficial in various areas e.g., the financial sector, marketing, medicine, technical industries, etc. In this paper, we consider a group of independent entities (referred to as agents) forming MAS, where data aggregation is exploited in order to optimize the applications executed in these systems in numerous aspects [20].…”