Distributed Data Management in Opportunistic Networks
Eary, Chance Ray
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Opportunistic networks (ONs) allow wireless devices, primarily mobile, to interact with one another through a series of opportunistic contacts. While ONs exploit mobility of devices to route messages and distribute information in the absence of dedicated networking infrastructure, the intermittent connections among devices make many traditional computer collaboration paradigms difficult to realize. Two such paradigms are distributed transactions and distributed shared memory (DSM). Distributed transactions are a sequence of operations, executed across multiple nodes, that must successfully complete as specified by its program, or abort with no changes to memory. DSM allows multiple, independent nodes to collectively operate on a pool of memory as if it were a single address space. Originally developed for traditional networks, both paradigms rely on relatively stable, consistent connections among participating nodes to function properly. This dissertation facilitates the employment of distributed transactions and DSM in ONs, by introducing two novel schemes specifically tailored to work in the presence of erratic inter-device connectivity, as well as a thorough investigation into optimizing the latter system to produce the most desirable functionality in a variety of exigent conditions. The first discussed is Distributed Transactions in Opportunistic Networks (DiTON), which enables the sequence of operations composing a transaction to operate on shared sets of data, hosted across multiple nodes, while providing global coherency in the event of network interruptions. An implementation of DiTON, and accompanying experimental results, demonstrate that it is possible to utilize transactions in ONs. The second scheme discussed is Delay Tolerant Lazy Release Consistency (DTLRC), a mechanism for implementing distributed shared memory in opportunistic networks. DTLRC permits mobile devices to remain independently productive while separated, and provides a mechanism for nodes to regain coherence of shared memory if and when they meet again. DTLRC allows applications to utilize the most coherent data available, even in the challenged environments typical to opportunistic networks. Simulations demonstrate that DTLRC is a viable system for deploying DSM in ONs. Finally, an model for analyzing the behavior of memory in DTLRC is presented. This model allows anyone with an interested in DTLRC to gain insight into its performance, without having to formally implement DTLRC's complicated algorithms.