Gossip-based service monitoring platform for wireless edge cloud computing

Edge cloud computing proposes to support shared services, by using the infrastructure at the network's edge. An important problem is the monitoring and management of services across the edge environment. Therefore, dissemination and gathering of data is not straightforward, differing from the classic cloud infrastructure. In this paper, we consider the environment of community networks for edge cloud computing, in which the monitoring of cloud services is required. We propose a monitoring platform to collect near real-time data about the services offered in the community network using a gossip-enabled network. We analyze and apply this gossip-enabled network to perform service discovery and information sharing, enabling data dissemination among the community. We implemented our solution as a prototype and used it for collecting service monitoring data from the real operational community network cloud, as a feasible deployment of our solution. By means of emulation and simulation we analyze in different scenarios, the behavior of the gossip overlay solution, and obtain average results regarding information propagation and consistency needs, i.e. in high latency situations, data convergence occurs within minutes.Peer ReviewedPostprint (author's final draft

Socially aware microcloud service overlay optimization in community networks

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.Peer ReviewedPostprint (author's final draft

Leveraging deployment models on low-resource devices for cloud services in community networks

Community networks are crowd-sourced IP networks that evolved into regional-scale computing platforms. This has led to adapting the cloud computing model for services that can operate and use computing resources inside a community network. The network and computing infrastructure is contributed by individuals, companies, organizations and maintained by its members. Community cloud devices are often low-capacity computing devices, such as home gateways or cabinet servers, with limited capabilities. These devices are used to install and operate specific personal or community services, but can be turned into multi-purpose execution environments applying machine or operating system (container) virtualization. However that requires addressing the problems of resource sharing in low-capacity devices, related to predictable performance and isolation. Our comparative analysis with the current infrastructure in community networks gives evidence about how devices can concurrently run multiple services, the trade offs between the number and resource requirements of services and the degradation of quality that services may suffer.Peer ReviewedPostprint (author's final draft

Leveraging deployment models on low-resource devices for cloud services in community networks

Community networks are crowd-sourced IP networks that evolved into regional-scale computing platforms. This has led to adapting the cloud computing model for services that can operate and use computing resources inside a community network. The network and computing infrastructure is contributed by individuals, companies, organizations and maintained by its members. Community cloud devices are often low-capacity computing devices, such as home gateways or cabinet servers, with limited capabilities. These devices are used to install and operate specific personal or community services, but can be turned into multi-purpose execution environments applying machine or operating system (container) virtualization. However that requires addressing the problems of resource sharing in low-capacity devices, related to predictable performance and isolation. Our comparative analysis with the current infrastructure in community networks gives evidence about how devices can concurrently run multiple services, the trade offs between the number and resource requirements of services and the degradation of quality that services may suffer.Peer Reviewe

Socially aware microcloud service overlay optimization in community networks

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.Peer Reviewe

Gossip-based service monitoring platform for wireless edge cloud computing

Edge cloud computing proposes to support shared services, by using the infrastructure at the network's edge. An important problem is the monitoring and management of services across the edge environment. Therefore, dissemination and gathering of data is not straightforward, differing from the classic cloud infrastructure. In this paper, we consider the environment of community networks for edge cloud computing, in which the monitoring of cloud services is required. We propose a monitoring platform to collect near real-time data about the services offered in the community network using a gossip-enabled network. We analyze and apply this gossip-enabled network to perform service discovery and information sharing, enabling data dissemination among the community. We implemented our solution as a prototype and used it for collecting service monitoring data from the real operational community network cloud, as a feasible deployment of our solution. By means of emulation and simulation we analyze in different scenarios, the behavior of the gossip overlay solution, and obtain average results regarding information propagation and consistency needs, i.e. in high latency situations, data convergence occurs within minutes.Peer Reviewe