Mathematical and Computer Modelling最新文献

With the rapid development of wireless communication, the growth of Cognitive Radio (CR) is increasing day by day. Because CR is flexible and operates on the wireless network, there are more security threats to CR technology than to the traditional radio environment. In addition, there is no comprehensive framework for achieving security in Cognitive Radio Networks (CRNs), and the role of trust for achieving security in CRNs has not been explored previously. Security vulnerability in cognitive radio technology is unavoidable due to the intrinsic nature of the technology, so it is critical to ensure system security in CRNs. The issue of secure communication in CRNs thus becomes more important than it is in conventional wireless networks. In this paper, we propose a conjoint trust assessment approach (combining trust assessment from the Primary User Network and the Secondary User Network) in a CRN to solve the security threats brought about by untrustworthy entities, such as selfish, malicious, and faultless nodes, and to ensure secure spectrum sharing in CRNs. A numerical analysis shows the feasibility of our proposed approach.

Widespread environmental concern provides an opportunity for the development of environmental auditing. This study aims to analyze ideas that address evaluation difficulties in an environmental performance audit and to promote the application of environmental performance audit in energy saving and emission reduction toward a high-end direction. An improved data envelopment analysis (DEA) model is applied in the environmental performance audit by data translation and the transformation method. With benchmark management considered, a two-phase DEA model algorithm is proposed to solve restricted inputs and outputs for pollutants or wastes as well as to overcome the relative efficiency of defects in traditional DEA evaluation. In the case study of a domestic sewage treatment plant, the model is found to improve the flexibility and effectiveness of the application.

Non-delegatability is an interesting property of designated verifier signatures (DVS) as it technically makes a signer responsible for the signer’s actions and protects the privacy of the signer. This property is critical for some financial scenarios when a user is required to do something by itself. As more financial applications are running in a mobile and ubiquitous computing environment, an efficient scheme with a non-delegatability property is desirable. This paper proposes such a scheme in an identity-based setting with detailed proofs. Technically, the scheme combines an identity-based Schnorr style signature and an identification method with an OR proof technique gluing the two parts. It is the second scheme secure in a strict model proposed by Huang et al. And it saves about half the communication and computation costs of the first one.

Recently, user demands for integrated searches over different information sources have been increasing rapidly. However, it is not easy to seamlessly integrate distributed heterogeneous information retrieval systems. In particular, resolving the discrepancies in the structures and semantics in the databases that are to be integrated is one of the most challenging research issues. In this paper, we propose an iKRISTAL system that integrates distributed, heterogeneous information retrieval systems without requiring source code-level modifications of the participating systems. The key element of our approach to address the structural and semantic discrepancies is to make use of schema mapping and a standardized framework for metadata registry. We have implemented and deployed a prototype implementation that integrates six different information sources, each of which is built upon heterogeneous schemas. Furthermore, we evaluated the performance of our approach under various configurations.

We employ a two-stage approach to analyze the determinants of energy efficiency of 28 provinces in China. In the first stage, we apply the Data Envelopment Analysis (DEA) technique to annual panel data from 2000 to 2006 to assess provincial industrial energy efficiency, taking into consideration the minimization of energy consumption and the effects of undesirable outputs. In the second stage, we study the determinants of energy efficiency by selecting four independent variables including the marketization index, GDP per capita, industrial R&D investment per capita and coal consumption percentage and performing random effects tobit regressions at country and regional levels. The results show that in most circumstances energy efficiency increases with the marketization index, GDP per capita, and industrial R&D investment per capita, and decreases with coal consumption percentage at country level. However, marketization and GDP per capita lose their explanatory power on energy efficiency in central and western regions, and coal consumption percentage loses its explanatory power in all regions. We also investigate the time effect and the differences in individual effects among regions. Based on these findings, we propose policy measures to enhance provincial industrial energy efficiency.

Economic growth in China needs lots of energy to support, but how to obtain a sufficient energy supply is now a problem. Meanwhile, environmental pollution caused by energy consumption is a problem that urgently needs to be solved. In order to adapt China’s fast developing economy, and on the basis of current policies, paying more attention to energy saving and environmental protection is more important. Therefore, to reasonably analyze China’s regional environmental efficiency and its determinants has practical significance. This article uses the Super-SBM model under undesirable outputs to measure regional environmental efficiency in China, and then explores influential factors of China’s environmental efficiency between 1991–2001 by means of the Tobit regression model. The empirical results show that during the sample period, the overall average level of China’s environmental efficiency is low, and the gap between different provinces and areas is large. The eastern area’s efficiency is obviously superior to the central and western area, which shows the necessity at present to optimize regional integration and promote innovation of energy conservation and emission reduction technology. At the same time, the “Eleven-Five ” year plan clearly states the energy saving and consumption reducing index, which motivates a great increase in China’s overall environmental efficiency, and promotes the fast development of resource conservation and environmentally friendly societal construction. The analysis of the influence factors by the Tobit model shows that fiscal decentralization and technology progress can increase environmental efficiency on the whole while economic scale and regional difference can also influence the efficiency. However, these factors’ influence is not the same in different areas. Finally, based on the research results, this paper gives policy recommendations on reducing pollution emissions and increasing China’s environmental efficiency.

Powerful data centers are the essential supporting infrastructure for mobile, ubiquitous, and cognitive computing, which are the most popular computing paradigms to utilize all kinds of physical resources and provide various services. To ensure the high quality of services, the performance and cost of a data center is a critical factor. In this paper, we investigate the issue of increasing the resource utilization of data centers to improve their performance and lower the cost. It is an efficient way to increase resource utilization via resource sharing. Technically, server virtualization provides the opportunity to share resources in data centers. However, it also introduces other problems, the primary problem being virtual machine placement (VMP), which is to choose a proper physical machine (PM) to deploy virtual machines (VMs) in runtime. We study the virtual machine placement problem with the target of minimizing the total energy consumption by the running of PMs, which is also an indication of resource utilization and the cost of a data center. Due to the multiple dimensionality of physical resources, there always exists a waste of resources, which results from the imbalanced use of multi-dimensional resources. To characterize the multi-dimensional resource usage states of PMs, we present a multi-dimensional space partition model. Based on this model, we then propose a virtual machine placement algorithm EAGLE, which can balance the utilization of multi-dimensional resources, reduce the number of running PMs, and thus lower the energy consumption. We also evaluate our proposed balanced algorithm EAGLE via extensive simulations and experiments on real traces. Experimental results show, over the long run, that EAGLE can save as much as 15% more energy than the first fit algorithm.

How to allocate initial emission permits is vital for the cap-and-trade system in controlling the total emission level and improving the operation efficiency of the trade mechanism. And data envelopment analysis (DEA) has been proved to be more suitable to fairly resolve the problem as a performance-based allocation is involved here. In this paper, we present a novel DEA approach for fair reduction and reallocation of emission permits for areas under administration. The presented DEA models are based on the ideas, where, according to their eco-efficiency and current emission levels, all decision making units (DMUs) compete with each other for the least reduction amount by introducing a bargaining game, on the other hand, the central authority can improve the overall efficiency by reallocating the remaining emission permits. The approach is applied on the dataset of agricultural greenhouse gas emissions from 15 European Union members (EU15). The results of the application show that the reduction and reallocation mechanism is fair, which benefits the countries that work at the optimal scale operation while punishes those that fail to operate on the optimal scale. Furthermore, it is effective in improving the overall efficiency of the system.

Resource allocation, as an important issue in management science, has drawn a lot of attention from both relative researchers and corporate managers. In recent years, data envelopment analysis (DEA) has been popularly applied in this field. In this paper, we propose some new DEA models, which consider both economic and environmental factors in the allocation of a given resource. Three scenarios of the given resource in the next period will be considered: one is larger than that in the present period, another is smaller than that in this period and the third is equal to that in this period. Two objective functions are formulated for the three scenarios, i.e., maximizing the total desirable outputs and minimizing the total undesirable outputs. The approach retains the advantages of traditional DEA, unit-invariant property, objectively-determined weights of inputs and outputs, and perfect dealing with multi-inputs and multi-outputs. An example is also employed to illustrate the approach.

The relationship between forest ecosystems and the forestry industry requires a balance between the needs of forestry development and the development of natural ecosystems, which is the core issue of sustainable international economy development. In this paper, the forestry industry is studied. Based on the establishing of the connection between forest ecology and the forestry industry, an analysis for this relationship in terms of a systems perspective is done by using quantitative methods. Furthermore, the model of forestry industry economic evaluation is established based on the construction of the evaluation index system of forestry industry economic benefits, which is performed by data envelopment analysis (DEA). Finally, we analyze more than a dozen instances in Yichun Forest. Through this case-study analysis, the extent of coupling between systems of forest ecology and forestry industry is examined, and the economic benefit of the forestry industry is evaluated.