Composing Relaxed Transactions

As the classical transactional abstraction is sometimes considered too restrictive in leveraging parallelism, a lot of work has been devoted to devising relaxed transactional models with the goal of improving concurrency. Nevertheless, the quest for improving concurrency has somehow led to neglect one of the most appealing aspects of transactions: software composition, namely, the ability to develop pieces of software independently and compose them into applications that behave correctly in the face of concurrency. Indeed, a closer look at relaxed transactional models reveals that they do jeopardize composition, raising the fundamental question whether it is at all possible to devise such models while preserving composition. This paper shows that the answer is positive. We present outheritance, a necessary and sufficient condition for a (potentially relaxed) transactional memory to support composition. Basically, outheritance requires child transactions to pass their conflict information to their parent transaction, which in turn maintains this information until commit time. Concrete instantiations of this idea have been used before, classical transactions being the most prevalent example, but we believe to be the first to capture this as a general principle as well as to prove that it is, strictly speaking, equivalent to ensuring composition. We illustrate the benefits of outheritance using elastic transactions and show how they can satisfy outheritance and provide composition without hampering concurrency. We leverage this to present a new (transactional) Java package, a composable alternative to the concurrency package of the JDK, and evaluate efficiency through an implementation that speeds up state of the art software transactional memory implementations (TL2, LSA, SwissTM) by almost a factor of 3

A Transaction Model for Executions of Compositions of Internet of Things Services

AbstractInternet of Things (IoT) is about making “things” smart in some functionality, and connecting and enabling them to perform complex tasks by themselves. The functionality can be encapsulated as services and the task executed by composing the services. Two noteworthy functionalities of IoT services are monitoring and actuation. Monitoring implies continuous executions, and actuation is by triggering. Continuous executions typically involve stream processing. Stream input data are accumulated into batches and each batch is subjected to a sequence of computations, structured as a dataflow graph. The composition may be processing several batches simultaneously. Additionally, some non-stream OLTP transactions may also be executing concurrently. Thus, several composite transactions may be executing concurrently. This is in contrast to a typical Web services composition, where just one composite transaction is executed on each invocation. Therefore, defining transactional properties for executions of IoT service compositions is much more complex than for those of conventional Web service compositions. In this paper, we propose a transaction model and a correctness criterion for executions of IoT service compositions. Our proposal defines relaxed atomicity and isolation properties for transactions in a flexible manner and can be adapted for a variety of IoT applications

A Sums-of-Squares Extension of Policy Iterations

In order to address the imprecision often introduced by widening operators in static analysis, policy iteration based on min-computations amounts to considering the characterization of reachable value set of a program as an iterative computation of policies, starting from a post-fixpoint. Computing each policy and the associated invariant relies on a sequence of numerical optimizations. While the early research efforts relied on linear programming (LP) to address linear properties of linear programs, the current state of the art is still limited to the analysis of linear programs with at most quadratic invariants, relying on semidefinite programming (SDP) solvers to compute policies, and LP solvers to refine invariants. We propose here to extend the class of programs considered through the use of Sums-of-Squares (SOS) based optimization. Our approach enables the precise analysis of switched systems with polynomial updates and guards. The analysis presented has been implemented in Matlab and applied on existing programs coming from the system control literature, improving both the range of analyzable systems and the precision of previously handled ones.Comment: 29 pages, 4 figure