Speedy Routing Recovery Protocol for Large Failure Tolerance in Wireless Sensor Networks

Wireless sensor networks are expected to play an increasingly important role in data collection in hazardous areas. However, the physical fragility of a sensor node makes reliable routing in hazardous areas a challenging problem. Because several sensor nodes in a hazardous area could be damaged simultaneously, the network should be able to recover routing after node failures over large areas. Many routing protocols take single-node failure recovery into account, but it is difficult for these protocols to recover the routing after large-scale failures. In this paper, we propose a routing protocol, referred to as ARF (Adaptive routing protocol for fast Recovery from large-scale Failure), to recover a network quickly after failures over large areas. ARF detects failures by counting the packet losses from parent nodes, and upon failure detection, it decreases the routing interval to notify the neighbor nodes of the failure. Our experimental results indicate that ARF could provide recovery from large-area failures quickly with less packets and energy consumption than previous protocols

Locality-driven checkpoint and recovery

Checkpoint and recovery are important fault-tolerance techniques for distributed systems. The two categories of existing strategies incur unacceptable performance cost either at run time or upon failure recovery, when applied to large-scale distributed systems. In particular, the large number of messages and processes in these systems causes either considerable checkpoint as well as logging overhead, or catastrophic global-wise recovery effect. This thesis proposes a locality-driven strategy for efficiently checkpointing and recovering such systems with both affordable runtime cost and controllable failure recoverability. Messages establish dependencies between distributed processes, which can be either preserved by coordinated checkpoints or removed via logging. Existing strategies enforce a uniform handling policy for all message dependencies, and hence gains advantage at one end but bears disadvantage at the other. In this thesis, a generic theory of Quasi-Atomic Recovery has been formulated to accommodate message handling requirements of both kinds, and to allow using different message handling methods together. Quasi-atomicity of recovery blocks implies proper confinement of recoveries, and thus enables localization of checkpointing and recovery around such a block and consequently a hybrid strategy with combined advantages from both ends. A strategy of group checkpointing with selective logging has been proposed, based on the observation of message localization around 'locality regions' in distributed systems. In essence, a group-wise coordinated checkpoint is created around such a region and only the few inter-region messages are logged subsequently. Runtime overhead is optimized due to largely reduced logging efforts, and recovery spread is as localized as region-wise. Various protocols have been developed to provide trade-offs between flexibility and performance. Also proposed is the idea of process clone that can be used to effectively remove program-order recovery dependencies among successive group checkpoints and thus to stop inter-group recovery spread. Distributed executions exhibit locality of message interactions. Such locality originates from resolving distributed dependency localization via message passing, and appears as a hierarchical 'region-transition' pattern. A bottom-up approach has been proposed to identify those regions, by detecting popular recurrence patterns from individual processes as 'locality intervals', and then composing them into 'locality regions' based on their tight message coupling relations between each other. Experiments conducted on real-life applications have shown the existence of hierarchical locality regions and have justified the feasibility of this approach. Performance optimization of group checkpoint strategies has to do with their uses of locality. An abstract performance measure has been-proposed to properly integrate both runtime overhead and failure recoverability in a region-wise marner. Taking this measure as the optimization objective, a greedy heuristic has been introduced to decompose a given distributed execution into optimized regions. Analysis implies that an execution pattern with good locality leads to good optimized performance, and the locality pattern itself can serve as a good candidate for the optimal decomposition. Consequently, checkpoint protocols have been developed to efficiently identify optimized regions in such an execution, with assistance of either design-time or runtime knowledge