We study practical techniques for implementing the FIFO queue abstract data type using lock-free data structures, which synchronize the operations of concurrent processes without the use of mutual exclusion. Two new algorithms based on linked lists and arrays are presented. We also propose a new solution to the ABA problem associated with the Compare&Swap instruction. The performance of our linked list algorithm is compared several other lock-free queue implementations, as well as more conventional locking techniques. 1 Introduction Concurrent access to a data structure shared among several processes must be synchronized in order to avoid conflicting updates. Conventionally this is done using mutual exclusion; processes modify the data structure only inside a critical section of code, within which the process is guaranteed exclusive access to the data structure. Typically, on a multiprocessor, critical sections are guarded with a spin-lock . We will refer to all methods using mutual ...

Very large database systems require distributed storage, which means that they need distributed search structures for fast and efficient access to the data. In this paper, we present an approach to maintaining distributed data structures that uses lazy updates, which take advantage of the semantics of the search structure operations to allow for scalable and low-overhead replication. Lazy updates can be used to design distributed search structures that support very high levels of concurrency. The alternatives to lazy update algorithms (vigorous updates) use synchronization to ensure consistency. Hence, lazy update algorithms are a distributed analogue of shared-memory lock-free search structure algorithms. Since lazy updates avoid the use of synchronization, they are much easier to implement than vigorous update algorithms. We demonstrate the application of lazy updates to the dB-tree, which is a distributed B + tree that replicates its interior nodes for highly parallel access. We d...