Towards Correct and Efficient Program Execution in Decentralized Networks: Programming Languages, Semantics, and Resource Management

Abstract: The Internet as of 2014 connects billions of devices, and is expected to connect tens of billions by 2020. To meet escalating requirements, networks must be scalable, easy to manage, and be able to efficiently execute programs and disseminate data. The prevailing use of centralized systems and control in, e.g., pools of computing resources, clouds, is problematic for scalability. A promising approach to management of large networks is decentralization, where independently acting network nodes communicate with their immediate neighbors to achieve desirable results at the global level.The research in this thesis addresses three distinct but interrelated problems in the context of cloud computing, networks, and programs running in clouds. First, we show how implementation correctness of active objects can be achieved in decentralized networks using location independent routing. Second, we investigate the feasibility of decentralized adaptive resource allocation for active objects in such networks, with promising results. Third, we automate an initial step of a process for converting programs with thread-based concurrency using shared memory to programs with message passing concurrency, which can then run efficiently in clouds.Specifically, starting from fragments of the distributed object modeling language ABS, we give network-oblivious descriptions of runtime behavior of programs, where the global state is a flat collection of objects and method calls. We then provide network-aware semantics, that place objects on network nodes connected point-to-point by asynchronous message passing channels. By relying on location independent routing, which maps object identifiers to next-hop neighbors at each node, inter-object messages can be delivered, regardless of object mobility among nodes. We establish that network-oblivious and network-aware behavior in static networks correspond in the sense of contextual equivalence. Using a network protocol reminiscent of a two-phase commit for controlled node shutdown, we extend the approach to dynamic networks without failures.We investigate node-local procedures for object migration to meet requirements on balanced allocations of objects to nodes, that also attempt to minimize exchange of object-related messages between nodes. By relying on coin-flips biased on local and neighbor load to decide on migration, and heuristics to capture object communication patterns, we show that balanced allocations can be achieved that make headway towards minimizing communication and latency.Our approach to execution of object-oriented programs in networks relies on message-passing concurrency. Mainstream programming languages generally use thread-based concurrency, which relies on control-centric primitives, such as locks, for synchronization. We present an algorithm for dynamic probabilistic inference of annotations for data-centric synchronization in threaded programs. By making collections of variables in classes accessed atomically explicit, these annotations can in turn suggest objects suitable for encapsulation as a unit of message-passing concurrency.