Intelligent Resources Management System Design in Information Centric Networking

Information centric networking(ICN) is a new network architecture that is centred on accessing content. It aims to solve some of the problems associated with IP networks, increasing content distribution capability and improving users' experience. To analyse the requests' patterns and fully utilize the universal cached contents, a novel intelligent resources management system is proposed, which enables effi cient cache resource allocation in real time, based on changing user demand patterns. The system is composed of two parts. The fi rst part is a fi ne-grain traffi c estimation algorithm called Temporal Poisson traffi c prediction(TP2) that aims at analysing the traffi c pattern(or aggregated user requests' demands) for different contents. The second part is a collaborative cache placement algorithm that is based on traffic estimated by TP2. The experimental results show that TP2 has better performance than other comparable traffi c prediction algorithms and the proposed intelligent system can increase the utilization of cache resources and improve the network capacity.

PERFORMANCE-BASED INTELLIGENT RESOURCE DESCRIPTION MODEL FOR INTERNET-BASED PRODUCT DESIGN

Issues on intelligent resource description and multiple intelligent resources integration for lntemet based collaborative design are analyzed. A performance-based intelligent resource description model for lnternet-based product design is proposed, which can help to create, store, manipulate and exchange intelligent resource description information for applications, tools and systems in Interact-based product design. A method to integrate multiple intelligent resources to fulfill a complex product design and analysis via lntemet is also proposed. A real project for improving the bearing system design of a turbo-expander with many intelligent resources in prominent universities is presented as a case study.

Design and application of electrical fire monitoring system in mining industry

To protect mining areas from electrical fire, it is very important to install electrical nre momtormg system to ensure safety in development of mineral resources and for buildings. In this paper, design for electrical fire monitoring and detection system with optional sensor modules has been proposed. In addition, necessity and suitability of electrical fire monitoring and detection system with optional sensor modules in mining areas have been reviewed. The designed electrical fire monitoring and detection system suit- able for work environment of mining industry is composed by host-computer monitoring software and slave-computer detectors. Monitoring detectors are manufactured by using embedded technology. Exter- nal shells deployed have superior enclosure performances and explosion-proof properties. It is easy to install and maintain the system. In general, the system has reached, or even exceeded standards specified in national standards for performances and appearances of such devices. Test results show application of electrical fire monitoring and detection system can effectively enhance monitoring intensity over the mining areas and provide reliable guarantee to ensure orderly development of mineral resources and to protect physical and property safety of citizens in these areas.

Architecture of Intelligent Grouping and Resource Sharing Standard

The Intelligent Grouping and Resource Sharing (IGRS) standard is set to enable intelligent grouping, resource sharing and services collaboration among information devices. An IGRS system adopts open architecture, that is, the devices abide by the IGRS standard are interoperable with devices following other standards such as Universal Plug and Play (UPnP). The IGRS supports multiple application frameworks and special applications. Developers can use an IGRS media application framework with various media format standards, such as AVS and MPEG-2, to develop multimedia applications. Applied among computers, consumer electronics, and communication devices, the IGRS standard can realize resource sharing and services collaboration in a certain range of wired or wireless network domain.

Prediction of job characteristics for intelligent resource allocation in HPC systems:a survey and future directions

Nowadays,high-performance computing(HPC)clusters are increasingly popular.Large volumes of job logs recording many years of operation traces have been accumulated.In the same time,the HPC cloud makes it possible to access HPC services remotely.For executing applications,both HPC end-users and cloud users need to request specific resources for different workloads by themselves.As users are usually not familiar with the hardware details and software layers,as well as the performance behavior of the underlying HPC systems.It is hard for them to select optimal resource configurations in terms of performance,cost,and energy efficiency.Hence,how to provide on-demand services with intelligent resource allocation is a critical issue in the HPC community.Prediction of job characteristics plays a key role for intelligent resource allocation.This paper presents a survey of the existing work and future directions for prediction of job characteristics for intelligent resource allocation in HPC systems.We first review the existing techniques in obtaining performance and energy consumption data of jobs.Then we survey the techniques for single-objective oriented predictions on runtime,queue time,power and energy consumption,cost and optimal resource configuration for input jobs,as well as multi-objective oriented predictions.We conclude after discussing future trends,research challenges and possible solutions towards intelligent resource allocation in HPC systems.