Obstruction-free synchronization: double-ended queues as an example

Abstract. We propose a new classification for evaluating the strength of shared objects. The classification is based on finding, for each object of type o, the strongest progress condition for which it is possible to solve consensus for any number of processes, using any number of objects of type o and atomic registers. We use the strongest progress condition to associate with each object a number call the power number of that object. Objects with higher power numbers are considered stronger. Then, we define the power hierarchy which is an infinite hierarchy of objects such that the objects at level i of the hierarchy are exactly those objects with power number i. Comparing our classification with the traditional one which is based on fixing the progress condition (namely, wait-freedom) and finding the largest number of processes for which consensus is solvable, reveals interesting results. Our equivalence and extended universality results, provide a deeper understanding of the nature of the relative computational power of shared objects.

Section: Consensus Numbers and The Wait-free Hierarchymentioning

confidence: 99%

On the Computational Power of Shared Objects

Taubenfeld

2009

“…In a recent work, Cachin et al [15] show that there is no wait-free emulation of fork-sequential consistent storage on a Byzantine server. It is important to note that these impossibility results do not rule out the existence of emulations of fork-linearizable storage with abortable operations [16] or weaker liveness guarantees such as obstruction-freedom [13]. Cachin et al [17] presents the storage service FAUST which wait-free emulates a shared memory with a new consistency semantics called weak forklinearizability.…”

Section: Related Workmentioning

confidence: 99%

“…The necessary condition for aborting is step contention [12], and thus, pending operations of crashed clients never cause other operations to abort. As a final contribution, note that the existence of abortable fork-linearizable storage implies the existence of obstruction-free [13] fork-linearizable storage.…”

Section: Introductionmentioning

confidence: 99%

Abortable Fork-Linearizable Storage

Majuntke

Dobre

Serafini

et al. 2009

Abstract. We address the problem of emulating a shared read/write memory in a message passing system using a storage server prone to Byzantine failures. Although cryptography can be used to ensure confidentiality and integrity of the data, nothing can prevent a malicious server from returning obsolete data. Fork-linearizability [1] guarantees that if a malicious server hides an update of some client from another client, then these two clients will never see each others' updates again. Fork-linearizability is arguably the strongest consistency property attainable in the presence of a malicious server. Recent work [2] has shown that there is no fork-linearizable shared memory emulation that supports wait-free operations. On the positive side, it has been shown that lockbased emulations exist [1,2]. Lock-based protocols are fragile because they are blocking if clients may crash. In this paper we present for the first time lock-free emulations of fork-linearizable shared memory. We have developed two protocols, Linear and Concur. With a correct server, both protocols guarantee linearizability and that every operation successfully completes in the absence of step contention, while interfering operations terminate by aborting. The Concur algorithm additionally ensures that concurrent operations invoked on different registers complete successfully.

“…Process q executes the loop of statements 9-20 twice. If the responses queue is not empty, the length of its first range is computed and stored to the respLen local variable (statements 11,12). Then the length of the next requests entry is computed and stored to reqsLen (statements 13,14).…”

Section: The Combining Processmentioning

confidence: 99%

“…Fich et al [4] proved an Ω(N ) time lower bound on obstruction-free [12] implementations of a wide class of shared objects, that includes counters, stacks and queues. This lower bound establishes that no nonblocking counter algorithm can improve on a central counter in terms of worst-case time complexity.…”

Section: Introductionmentioning

confidence: 99%

Constructing Shared Objects That Are Both Robust and High-Throughput

Hendler

Kutten

2006

Abstract. Shared counters are among the most basic coordination structures in distributed computing. Known implementations of shared counters are either blocking, non-linearizable, or have a sequential bottleneck. We present the first counter algorithm that is both linearizable, nonblocking, and can provably achieve high throughput in semisynchronous executions. The algorithm is based on a novel variation of the software combining paradigm that we call bounded-wait combining. It can thus be used to obtain implementations, possessing the same properties, of any object that supports combinable operations, such as stack or queue. Unlike previous combining algorithms where processes may have to wait for each other indefinitely, in the bounded-wait combining algorithm a process only waits for other processes for a bounded period of time and then 'takes destiny in its own hands'. In order to reason rigorously about the parallelism attainable by our algorithm, we define a novel metric for measuring the throughput of shared objects which we believe is interesting in its own right. We use this metric to prove that our algorithm can achieve throughput of Ω(N/ log N ) in executions where process speeds vary only by a constant factor, where N is the number of processes that can participate in the algorithm. We also introduce and use pseduo-transactions -a technique for concurrent execution that may prove useful for other algorithms.