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.

Cross-efficiency DEA model-based evaluation of allocative efficiency of rural information resources in Jiangsu Province, China

Purpose: This paper aims to compare and rank the allocative efficiency of information resources in rural areas by taking 13 rural areas in Jiangsu Province, China as the research sample.Design/methodology/approach: We designed input and output indicators for allocation of rural information resources and conducted the quantitative evaluation of allocative efficiency of rural information resources based on cross-efficiency model in combination with the classical CCR model in data envelopment analysis(DEA).Findings: Cross-efficiency DEA model can be used for our research with the objective to evaluate quantitatively and objectively whether the allocation of information resources in various rural areas is reasonable and whether the output is commensurate with the input.Research limitations: We have to give up using some indicators because of limited data availability. There is a need to further improve the cross-efficiency DEA model because it cannot identify the specific factors influencing the efficiency of decision-making units(DMUs).Practical implications: The evaluation results will help us understand the present allocative efficiency levels of information resources in various rural areas so as to provide a decisionmaking basis for formulation of the policies aimed at promoting the circulation of information resources in rural areas.Originality/value: Little or no research has been published about the allocative efficiency of rural information resources. The value of this research lies in its focus on studying rural informatization from the perspective of allocative efficiency of rural information resources and in the application of cross-efficiency DEA model to evaluate allocative efficiency of rural information resources as well.