A Massively Scalable Architecture For Instant Messaging & Presence

This paper analyzes the scalability of Instant Messaging & Presence (IM&P) architectures. We take a queueing-based modelling and analysis approach to find the bottlenecks of the current IM&P architecture at the Dutch social network Hyves, as well as of alternative architectures. We use the Hierarchical Evaluation Tool (HIT) to create and analyse models analytically. Based on these results, we recommend a new architecture that provides better scalability than the current one. \u

Modeling industry 4.0 based fog computing environments for application analysis and deployment

The extension of the Cloud to the Edge of the network through Fog Computing can have a significant impact on the reliability and latencies of deployed applications. Recent papers have suggested a shift from VM and Container based deployments to a shared environment among applications to better utilize resources. Unfortunately, the existing deployment and optimization methods pay little attention to developing and identifying complete models to such systems which may cause large inaccuracies between simulated and physical run-time parameters. Existing models do not account for application interdependence or the locality of application resources which causes extra communication and processing delays. This paper addresses these issues by carrying out experiments in both cloud and edge systems with various scales and applications. It analyses the outcomes to derive a new reference model with data driven parameter formulations and representations to help understand the effect of migration on these systems. As a result, we can have a more complete characterization of the fog environment. This, together with tailored optimization methods than can handle the heterogeneity and scale of the fog can improve the overall system run-time parameters and improve constraint satisfaction. An Industry 4.0 based case study with different scenarios was used to analyze and validate the effectiveness of the proposed model. Tests were deployed on physical and virtual environments with different scales. The advantages of the model based optimization methods were validated in real physical environments. Based on these tests, we have found that our model is 90% accurate on load and delay predictions for application deployments in both cloud and edge

Data-parallel agent-based microscopic road network simulation using graphics processing units

Road network microsimulation is computationally expensive, and existing state of the art commercial tools use task parallelism and coarse-grained data-parallelism for multi-core processors to achieve improved levels of performance. An alternative is to use Graphics Processing Units (GPUs) and fine-grained data parallelism. This paper describes a GPU accelerated agent based microsimulation model of a road network transport system. The performance for a procedurally generated grid network is evaluated against that of an equivalent multi-core CPU simulation. In order to utilise GPU architectures effectively the paper describes an approach for graph traversal of neighbouring information which is vital to providing high levels of computational performance. The graph traversal approach has been integrated within a GPU agent based simulation framework as a generalised message traversal technique for graph-based communication. Speed-ups of up to 43 ×  are demonstrated with increased performance scaling behaviour. Simulation of over half a million vehicles and nearly two million detectors at a rate of 25 ×  faster than real-time is obtained on a single GPU

Adaptive object management for distributed systems

This thesis describes an architecture supporting the management of pluggable software components and evaluates it against the requirement for an enterprise integration platform for the manufacturing and petrochemical industries. In a distributed environment, we need mechanisms to manage objects and their interactions. At the least, we must be able to create objects in different processes on different nodes; we must be able to link them together so that they can pass messages to each other across the network; and we must deliver their messages in a timely and reliable manner. Object based environments which support these services already exist, for example ANSAware(ANSA, 1989), DEC's Objectbroker(ACA,1992), Iona's Orbix(Orbix,1994)Yet such environments provide limited support for composing applications from pluggable components. Pluggability is the ability to install and configure a component into an environment dynamically when the component is used, without specifying static dependencies between components when they are produced. Pluggability is supported to a degree by dynamic binding. Components may be programmed to import references to other components and to explore their interfaces at runtime, without using static type dependencies. Yet thus overloads the component with the responsibility to explore bindings. What is still generally missing is an efficient general-purpose binding model for managing bindings between independently produced components. In addition, existing environments provide no clear strategy for dealing with fine grained objects. The overhead of runtime binding and remote messaging will severely reduce performance where there are a lot of objects with complex patterns of interaction. We need an adaptive approach to managing configurations of pluggable components according to the needs and constraints of the environment. Management is made difficult by embedding bindings in component implementations and by relying on strong typing as the only means of verifying and validating bindings. To solve these problems we have built a set of configuration tools on top of an existing distributed support environment. Specification tools facilitate the construction of independent pluggable components. Visual composition tools facilitate the configuration of components into applications and the verification of composite behaviours. A configuration model is constructed which maintains the environmental state. Adaptive management is made possible by changing the management policy according to this state. Such policy changes affect the location of objects, their bindings, and the choice of messaging system