Road traffic management has been a priority for urban city planners to mitigate urban traffic congestion. In 2018, the economic impact to US due to lost productivity of workers sitting in traffic, increased cost of transporting goods through congested areas, and all of that wasted fuel amounted to US$87 billion, an average of US$1,348 per driver. In land scare Singapore, congestion not only translates to economic impact, but also strain to the infrastructure and city land use. While techniques for traffic prediction have existed for many years, the research effort has mainly been focused on traffic prediction. The downstream impact on how city administration should predict and react to incidents and/or events has not been widely discussed. In this paper, we propose Artificial Intelligence enabled Complex Event Processing to only identify and predict incidents, but also to enable a swift response through effective deployment of critical resources to ensure well-coordinated recovery action before any incident develop into crisis.

There is increasing collaboration in new generation supply chain planning applications, where participants across a supply chain analyze and plan on a big volume of sales data over the internet together. To achieve real-time collaborative planning over big data, we have developed an unconventional t

Asynchronous transaction processing extends traditional on-line transaction processing (TP) to improve performance of distributed systems by alleviating the serializability (SR) bottleneck. For example, epsilon serializability (ESR) uses divergence control algorithms to allow more concurrency by permitting limited non-SR interleavings. In a distributed environment, ESR relaxes commit and abort dependencies among transactions, allowing transactions to commit asynchronously. A second example, chopping up transactions allows more concurrency by dividing transactions into smaller pieces and thus reduces resource holding time. Chopping transactions enforces no commit protocols among pieces from one original transaction, allowing each piece to commit asynchronously. We combine the benefits of ESR and chopping transactions by designing three new methods that chop transactions and run them under ESR. The practical applicability of our technique is enhanced by two factors: (1) chopping transactions does not require changes in existing TP systems, and (2) ESR support has already been prototyped on a commercial TP system.

Epsilon serializability (ESR) allows for more concurrency by permitting nonserializable interleavings of database operations among epsilon transactions (ETs). The authors present the design of distributed divergence control (DDC) algorithms for ESR in homogeneous and heterogeneous distributed databases. They first present a strict two-phase locking DDC algorithm (S2PLDDC) and an optimistic DDC algorithm (ODDC) for homogeneous distributed databases, where the local orderings of all the sub-ETs of a distributed ET are the same, and the total inconsistency of a distributed ET is simply the sum of that of all its sub-ETs. A superdatabase DDC algorithm is described for heterogeneous distributed databases, where the local orderings of all the sub-ETs of a distributed ET may not be the same, and the total inconsistency of a distributed ET may be greater than the sum of that of all its sub-ETs. As a result, in addition to local divergence control in each site, a global mechanism is needed to guarantee ESR.>

We propose a description language, Data Path Expressions (DPEs), for modeling the behavior of parallel programs. We have designed DPEs as a high-level debugging language, where the debugging paradigm is for the programmer to describe the expected program behavior and for the debugger to compare the actual program behavior during execution to detect program errors. We classify DPEs into five subclasses according to syntactic criteria, and characterize their semantics in terms of a hierarchy of extended Petri Net models. The characterization demonstrates the power of DPEs for modeling (true) concurrency. We also present predecessor automata as a mechanism for implementing the third subclass of DPEs, which expresses bounded parallelism. Predecessor automata extend finite state automata to recognize or generate partial ordering graphs as well as strings, and provide efficient event recognizers for parallel debugging. We briefly describe the application of DPEs race conditions, deadlock and starvation.