Enabling collaboration in virtual reality navigators

In this paper we characterize a feature superset for Collaborative Virtual Reality Environments (CVRE), and derive a component framework to transform stand-alone VR navigators into full-fledged multithreaded collaborative environments. The contributions of our approach rely on a cost-effective and extensible technique for loading software components into separate POSIX threads for rendering, user interaction and network communications, and adding a top layer for managing session collaboration. The framework recasts a VR navigator under a distributed peer-to-peer topology for scene and object sharing, using callback hooks for broadcasting remote events and multicamera perspective sharing with avatar interaction. We validate the framework by applying it to our own ALICE VR Navigator. Experimental results show that our approach has good performance in the collaborative inspection of complex models.Postprint (published version

A Novel Workload Allocation Strategy for Batch Jobs

The distribution of computational tasks across a diverse set of geographically distributed heterogeneous resources is a critical issue in the realisation of true computational grids. Conventionally, workload allocation algorithms are divided into static and dynamic approaches. Whilst dynamic approaches frequently outperform static schemes, they usually require the collection and processing of detailed system information at frequent intervals - a task that can be both time consuming and unreliable in the real-world. This paper introduces a novel workload allocation algorithm for optimally distributing the workload produced by the arrival of batches of jobs. Results show that, for the arrival of batches of jobs, this workload allocation algorithm outperforms other commonly used algorithms in the static case. A hybrid scheduling approach (using this workload allocation algorithm), where information about the speed of computational resources is inferred from previously completed jobs, is then introduced and the efficiency of this approach demonstrated using a real world computational grid. These results are compared to the same workload allocation algorithm used in the static case and it can be seen that this hybrid approach comprehensively outperforms the static approach

Tools for distributed application management

Distributed application management consists of monitoring and controlling an application as it executes in a distributed environment. It encompasses such activities as configuration, initialization, performance monitoring, resource scheduling, and failure response. The Meta system (a collection of tools for constructing distributed application management software) is described. Meta provides the mechanism, while the programmer specifies the policy for application management. The policy is manifested as a control program which is a soft real-time reactive program. The underlying application is instrumented with a variety of built-in and user-defined sensors and actuators. These define the interface between the control program and the application. The control program also has access to a database describing the structure of the application and the characteristics of its environment. Some of the more difficult problems for application management occur when preexisting, nondistributed programs are integrated into a distributed application for which they may not have been intended. Meta allows management functions to be retrofitted to such programs with a minimum of effort

Efficient Resource Matching in Heterogeneous Grid Using Resource Vector

In this paper, a method for efficient scheduling to obtain optimum job throughput in a distributed campus grid environment is presented; Traditional job schedulers determine job scheduling using user and job resource attributes. User attributes are related to current usage, historical usage, user priority and project access. Job resource attributes mainly comprise of soft requirements (compilers, libraries) and hard requirements like memory, storage and interconnect. A job scheduler dispatches jobs to a resource if a job's hard and soft requirements are met by a resource. In current scenario during execution of a job, if a resource becomes unavailable, schedulers are presented with limited options, namely re-queuing job or migrating job to a different resource. Both options are expensive in terms of data and compute time. These situations can be avoided, if the often ignored factor, availability time of a resource in a grid environment is considered. We propose resource rank approach, in which jobs are dispatched to a resource which has the highest rank among all resources that match the job's requirement. The results show that our approach can increase throughput of many serial / monolithic jobs.Comment: 10 page

ATP: a Datacenter Approximate Transmission Protocol

Many datacenter applications such as machine learning and streaming systems do not need the complete set of data to perform their computation. Current approximate applications in datacenters run on a reliable network layer like TCP. To improve performance, they either let sender select a subset of data and transmit them to the receiver or transmit all the data and let receiver drop some of them. These approaches are network oblivious and unnecessarily transmit more data, affecting both application runtime and network bandwidth usage. On the other hand, running approximate application on a lossy network with UDP cannot guarantee the accuracy of application computation. We propose to run approximate applications on a lossy network and to allow packet loss in a controlled manner. Specifically, we designed a new network protocol called Approximate Transmission Protocol, or ATP, for datacenter approximate applications. ATP opportunistically exploits available network bandwidth as much as possible, while performing a loss-based rate control algorithm to avoid bandwidth waste and re-transmission. It also ensures bandwidth fair sharing across flows and improves accurate applications' performance by leaving more switch buffer space to accurate flows. We evaluated ATP with both simulation and real implementation using two macro-benchmarks and two real applications, Apache Kafka and Flink. Our evaluation results show that ATP reduces application runtime by 13.9% to 74.6% compared to a TCP-based solution that drops packets at sender, and it improves accuracy by up to 94.0% compared to UDP

Dynamic resource allocation scheme for distributed heterogeneous computer systems

This invention relates to a resource allocation in computer systems, and more particularly, to a method and associated apparatus for shortening response time and improving efficiency of a heterogeneous distributed networked computer system by reallocating the jobs queued up for busy nodes to idle, or less-busy nodes. In accordance with the algorithm (SIDA for short), the load-sharing is initiated by the server device in a manner such that extra overhead in not imposed on the system during heavily-loaded conditions. The algorithm employed in the present invention uses a dual-mode, server-initiated approach. Jobs are transferred from heavily burdened nodes (i.e., over a high threshold limit) to low burdened nodes at the initiation of the receiving node when: (1) a job finishes at a node which is burdened below a pre-established threshold level, or (2) a node is idle for a period of time as established by a wakeup timer at the node. The invention uses a combination of the local queue length and the local service rate ratio at each node as the workload indicator

Incentives in peer-to-peer and grid networking

Today, most peer-to-peer networks are based on the assumptionthat the participating nodes are cooperative. Thisworks if the nodes are indifferent or ignorant about the resourcesthey offer, but limits the usability of peer-to-peernetworks to very few scenarios. It specifically excludes theirusage in any non-cooperative peer-to-peer environment, beit Grid networks or mobile ad-hoc networks. By introducingsoft incentives to offer resources to other nodes, we seean overall performance gain in traditional file-sharing networks.We also see soft incentives promoting the convergenceof peer-to-peer and Grid networks, as they increasethe predictability of the participating nodes, and thereforethe reliability of the services provided by the system as awhole. Reliability is what is required by Grid networks, butmissing in peer-to-peer networks