Autonomous Placement and Migrationof Services in HeterogeneousEnvironments

Abstract: In this thesis, we present an autonomous placement protocol for services in smart spaces. Proposed design is a combination of computing Grids and Intelligent Agent Systems which is able to adapt to environmental changes. These changes are failing/joining/leaving nodes, changing node usage, failing/joining/leaving services, and changing service demands. Smart spaces are heterogeneous in terms of available resources for consumption and they are dynamic where available resources and services change over time. The system adapts to environmental changes by live service migration and load balancing, and provides high availability by maintaining backup replicas of services. Load in the system is balanced among available resources by taking into account heterogeneity of the environment. Complex nature of the problem space makes it difficult to manage the services and resources manually. Thus, all functionality provided by the system is fully autonomous. A novel approach is presented for migration decisions based on utility functions that represent characteristics of nodes. Fitness of the designed protocol is tested with simulations under different circumstances. Obtained test results show that it provides high degree of availability to services and adapts to environmental changes.