AbstractsComputer Science

The design and management of networked systems that are large-scale and decentralized is challenging. These systems are usually organized in virtual networks: the overlay networks. An overlay network lies at the application-level and on top of physical or other overlay networks. Overlay networks implement complex application and organizational functionality not supported by underlying network services. This integration and design approach results in low abstraction, modularity and reconfigurability of applications that are based on overlay networks. In contrast to this practice, this thesis introduces the conceptual architecture of ASMA, the Adaptive Self-organization in a Multi-level Architecture. ASMA is the main contribution of this thesis and is designed for building middleware systems of overlay networks that provide generic capabilities to different distributed applications: the overlay services. The abstraction, modularity and reconfigurability of ASMA is achieved by its multilevel design approach. Three conceptually defined levels of overlay networks and their interactions provide discovery, structuring and coordination of system entities without a centralized management authority. The interactions between the three levels of ASMA form feedback loops that improve the quality of an overlay service incrementally. This thesis shows that a few lines of algorithmic expressions defined by ASMA are adequate to realize the complex system functionality of two introduced overlay services: (i) AETOS, the Adaptive Epidemic Tree Overlay Service and (ii) DIAS, the Dynamic Intelligent Aggregation Service. Both overlay services advance the state of the art by providing two generic application capabilities. AETOS builds and maintains overlay networks organized in tree topologies that meet different application criteria. DIAS computes different aggregation functions over a set of dynamically changing values distributed in an overlay network. Both overlay services of ASMA provide a proof-of-concept about their higher abstraction, modularity and reconfigurability at the cost of higher communication overhead compared to related work. AETOS provides self-organization of tree topologies with the graph properties of degree- bounding, ordering, balancing and completeness. AETOS performs a gossip-based discovery of nodes in a network. These nodes, ranked according to application criteria, are clustered based on their proximity computed by their ranking distance. Clustering of nodes as candidate parents and children provides a more cost-effective search space compared to random searching. Bidirectional links are negotiated and established with these parents and children based on ‘request’, ‘acknowledgment’, ‘rejection’ and ‘removal’ interactions. Different tree topologies can be self-organized by adopting adaptation strategies that hide complex clustering and selection configurations. Experimental evaluation illustrates the performance trade-offs and reconfigurability of AETOS in various experimental settings. This evaluation concludes…