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Socially aware microcloud service overlay optimization in community networks
Author(s) -
Apolónia Nuno,
Freitag Felix,
Navarro Leandro,
Girdzijauskas Sarunas
Publication year - 2020
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2750
Subject(s) - computer science , overlay network , cloud computing , distributed computing , computer network , workload , the internet , peer to peer , overlay , dissemination , world wide web , telecommunications , programming language , operating system
Summary Community networks are a growing network cooperation effort by citizens to build and maintain Internet infrastructure in regions that are not available. Adding that, to bring cloud services to community networks (CNs), microclouds were started as an edge cloud computing model where members cooperate using resources. Therefore, enhancing routing for services in CNs is an attractive paradigm that benefits the infrastructure. The problem is the growing consumption of resources for disseminating messages in the CN environment. This is because the services that build their overlay networks are oblivious to the underlying workload patterns that arise from social cooperation in CNs. In this paper, we propose Select in Community Networks (SELECTinCN), which enhances the overlay creation for pub/sub systems over peer‐to‐peer (P2P) networks. Moreover, SELECTinCN includes social information based on cooperation within CNs by exploiting the social aspects of the community of practice. Our work organizes the peers in a ring topology and provides an adaptive P2P connection establishment algorithm, where each peer identifies the number of connections needed based on the social structure and user availability. This allows us to propagate messages using a reduced number of hops, thus providing an efficient heuristic to an NP‐hard problem that maps the workload graph to the structured P2P overlays resulting in a number of messages close to the theoretical minimum. Experiments show that, by using social network information, SELECTinCN reduces the number of relay nodes by up to 89% using the community of practice information versus the state‐of‐the‐art pub/sub notification systems given as baseline.