Scalable and Reliable Location Services Through Decentralized Replication

Abstract—One of the critical challenges for service oriented computing systems is the capability to guarantee scalable and reliable service provision. This paper presents Reliable GeoGrid, a decentralized service computing architecture based on geographical location aware overlay network for supporting reliable and scalable mobile information delivery services. The reliable GeoGrid approach offers two distinct features. First, we develop a distributed replication scheme, aiming at providing scalable and reliable processing of location service requests in decentralized pervasive computing environments. Our replica management operates on a network of heterogeneous nodes and utilizes a shortcut-based optimization to increase the resilience of the system against node failures and network failures. Second, we devise a dynamic load balancing technique that exploits the service processing capabilities of replicas to scale the system in anticipation of unexpected workload changes and node failures by taking into account of node heterogeneity, network proximity, and changing workload at each node. Our experimental evaluation shows that the reliable GeoGrid architecture is highly scalable under changing service workloads with moving hotspots and highly reliable in the presence of both individual node failures and massive node failures. I

2009 IEEE International Conference on Web Services Scalable and Reliable Location Services Through Decentralized Replication

Abstract—One of the critical challenges for service oriented computing systems is the capability to guarantee scalable and reliable service provision. This paper presents Reliable GeoGrid, a decentralized service computing architecture based on geographical location aware overlay network for supporting reliable and scalable mobile information delivery services. The reliable GeoGrid approach offers two distinct features. First, we develop a distributed replication scheme, aiming at providing scalable and reliable processing of location service requests in decentralized pervasive computing environments. Our replica management operates on a network of heterogeneous nodes and utilizes a shortcut-based optimization to increase the resilience of the system against node failures and network failures. Second, we devise a dynamic load balancing technique that exploits the service processing capabilities of replicas to scale the system in anticipation of unexpected workload changes and node failures by taking into account of node heterogeneity, network proximity, and changing workload at each node. Our experimental evaluation shows that the reliable GeoGrid architecture is highly scalable under changing service workloads with moving hotspots and highly reliable in the presence of both individual node failures and massive node failures. I