Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of Vehicles

High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.

A dynamic and resource sharing virtual network mapping algorithm

Network virtualization can effectively establish dedicated virtual networks to implement various network functions.However,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and priority.In addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation redundancy.Based on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology properties.In the node mapping process,three properties of the node are used to measure its mapping ability.Second,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link mapping.Finally,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource allocation.The former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision probability.Simulation results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenue by 15%and 38%,and reduce the network cost and link pressure by 25%and 17%.

Analysis and Optimization of Validation Procedure in Blockchain-Enhanced Wireless Resource Sharing and Transactions

To ensure the security of resource and intelligence sharing in 6G,blockchain has been widely adopted in wireless communications and applications.Although blockchain can ensure the traceability and non-tamperability of data in the concatenated blocks,it cannot guarantee the honest behaviors of users in the application before the generation of transactions.Thus,additional technologies are required to ensure that the source of blockchain data is reliable.In this paper,the detailed procedure is designed for the application-oriented task validation in the blockchainenhanced computing resource sharing and transactions in ultra dense networks(UDN).The corresponding queuing model is built and analyzed with the consideration of the wireless re-transmission and the probability of malicious deception by users.Based on the analysis results,the UDN deployment is optimized to save network cost while ensuring latency performance.Numerical results verify our analysis,and the optimized system deployment including the number and service capacities of both base stations and mobile edge computing(MEC)servers are also given with various system settings.

Starlet:Network defense resource allocation with multi-armed bandits for cloud-edge crowd sensing in IoT

The cloud platform has limited defense resources to fully protect the edge servers used to process crowd sensing data in Internet of Things.To guarantee the network's overall security,we present a network defense resource allocation with multi-armed bandits to maximize the network's overall benefit.Firstly,we propose the method for dynamic setting of node defense resource thresholds to obtain the defender(attacker)benefit function of edge servers(nodes)and distribution.Secondly,we design a defense resource sharing mechanism for neighboring nodes to obtain the defense capability of nodes.Subsequently,we use the decomposability and Lipschitz conti-nuity of the defender's total expected utility to reduce the difference between the utility's discrete and continuous arms and analyze the difference theoretically.Finally,experimental results show that the method maximizes the defender's total expected utility and reduces the difference between the discrete and continuous arms of the utility.

Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

A Pre-Selection-Based Ant Colony System for Integrated Resources Scheduling Problem at Marine Container Terminal

Marine container terminal(MCT)plays a key role in the marine intelligent transportation system and international logistics system.However,the efficiency of resource scheduling significantly influences the operation performance of MCT.To solve the practical resource scheduling problem(RSP)in MCT efficiently,this paper has contributions to both the problem model and the algorithm design.Firstly,in the problem model,different from most of the existing studies that only consider scheduling part of the resources in MCT,we propose a unified mathematical model for formulating an integrated RSP.The new integrated RSP model allocates and schedules multiple MCT resources simultaneously by taking the total cost minimization as the objective.Secondly,in the algorithm design,a pre-selection-based ant colony system(PACS)approach is proposed based on graphic structure solution representation and a pre-selection strategy.On the one hand,as the RSP can be formulated as the shortest path problem on the directed complete graph,the graphic structure is proposed to represent the solution encoding to consider multiple constraints and multiple factors of the RSP,which effectively avoids the generation of infeasible solutions.On the other hand,the pre-selection strategy aims to reduce the computational burden of PACS and to fast obtain a higher-quality solution.To evaluate the performance of the proposed novel PACS in solving the new integrated RSP model,a set of test cases with different sizes is conducted.Experimental results and comparisons show the effectiveness and efficiency of the PACS algorithm,which can significantly outperform other state-of-the-art algorithms.

Joint Management of Shared Resources, Issues and Conflicts of the Nso and Oku Tribes in the Ngongbaa Montane Forest Area, NWR of Cameroon

Wherever people live together in or near homelands that harbour joint natural resources such as forest, water, minerals, oil etc., they must collaborate, co-exist and share these resources irrespective of their genetic, social, cultural, and political peculiarities. This is not always the case when self-interest, ethnic divisions, elitist politics, economic interest and power tussle set in. The Nso and Oku people who reside in the Ngongbaa Forest area constitute an example of joint management of resources where at one period, their relationship over the management of the Oku Mountain Forest was cordial and at another, the relationship became conflictive. This study was designed to study the influence of the KIFP forest management policies on the Nso indigenous forest Management system in Ngongbaa Forest, and its implications. The data collected for the study was secured through the administration of a questionnaire to residents of 10 villages adjacent to the Ngongbaa Forest, and forest users who carried out livelihood activities there between 1963 and 2015. These forest user groups include beekeepers, rat trappers, grazers, mushroom gatherers, ground honey/tree honey harvesters, carvers, etc. The investigation also extended to the traditional leaders of Nso and Oku who are in charge of the land tenure systems. The findings show that the Oku Mountain Forest is jointly owned by the Nso and Oku people. The Nso own the eastern half of the forest known as Ngongbaa Forest while the Oku own the western half, known as the Kilum Forest. The cordial relationship that existed between these people ensured the conservation of the forest. But the conflicts that later set in, especially due to the creation of the Kilum Mountain Forest Project in 1987 later changed to the Kilum Ijim Forest Project (KIFP) in 1992 sidelined the local communities which was contrary to the dispositions of the new Cameroon forest law enacted in 1994. Thus, the indigenous conservation practices became ignored which the local population never digested well. This seriously jeopardized the wellbeing of the forest in general.

Documentation Concordance,Sharing and Utilization of Tea Germplasm Resources in Yunnan

In this paper,the research achievements and progress of Yunnan tea germplasm resource in past sixty years are systematically reviewed from the following aspects：exploration,collecting,conservation,protection,identification,evaluation and shared utilization.Simultaneously,the current problems and the suggestions about subsequent development of tea germplasm resources in Yunnan were discussed,including superior and rare germplasm collection,tea genetic diversity research,biotechnology utilization in tea germplasm innovation,super gene exploration and function,the construction of utilization platform,biological base of species and population conservation.

Intraclonal Resource Sharing and Functional Specialization of Ramets in Response to Resource Heterogeneity in Three Stoloniferous Herbs

Environments with reciprocal patchiness of resources, in which the availability of two resources such as light and soil nutrients are patchily distributed in horizontal space and negatively correlated in each patch, are common in many ecosystems. The strategies by which clonal plants adapt to this type of heterogeneous environment were examined in three stoloniferous herbs,Potentilla reptans L. var. sericophylla Franch., P. anserina L. and Halerpestes ruthenica (Jacq.) Qvcz., commonly inhabiting forest understories, grasslands and low saline meadows, respectively. As pairs of connected ramets were subjected to reciprocal patchiness of light and nutrients, stolon connection between the two ramets significantly enhanced biomass of both ramet growing in low light intensity but high soil nutrient condition (LH ramet) and ramet growing in high light intensity but low soil nutrient condition (HL ramet) as well as whole ramet pairs (consisting of LH ramets and HL ramets). Additionally, stolon connection greatly increased root/shoot ratio of LH ramet while significantly decreased that of HL ramet. The results indicate that a reciprocal transportation of resources between interconnected ramets and a functional specialization of ramets in uptake of abundant resources occurred. By resource sharing and functional specialization, clonal plants can efficiently acquire locally abundant resources and buffer the stress caused by reciprocal patchiness of resources.

Dilemma and Exploration of Resource Sharing in University Museums of Natural History——using Natural History Museum of Zhengzhou Normal University as an example

A natural history museum is a museum for collection, researching and presenting natural environment and natural heritages about natural history. In the research, based on the analysis on necessity of university museums’ services to society in resources sharing, the difficulties and dilemmas were summarized in sharing resources of museums and the approaches for resources sharing were explored with the case of Natural History Museum of Zhengzhou Normal University in order to investigate the way for better services of university museum to the public.

A Game Theoretic Approach for Hierarchical Caching Resource Sharing in 5G Networks with Virtualization

Caching and virtualization have been considered as the promising techniques in 5G Networks. In 5G networks with virtualization, the caching resources deployed by infrastructure providers (InPs) can be abstracted into isolated slices and transparently shared by mobile virtual network operators (MVNOs). In this case, one of the most important issues is how the MVNOs to share the caching resource. To solve this issue, different from previous works, a hierarchical caching architecture that core network and radio access network (RAN) have the caching capability in 5G networks with virtualization is first considered in this paper. Then, we study the problem of hierarchical caching resource sharing for MVNOs, and a competitive game to maximize their expectation revenue based on the oligopoly market model is formulated. As it is a hard problem to find the optimal solution in the hierarchical caching resource sharing problem, we decompose the optimization problem into two independent caching resource sharing problems in RAN and core network, respectively. Then the local optimal solutions are solved and the global Nash equilibrium solution is achieved. Finally, simulation results are illustrated to demonstrate the performance of the proposed scheme.

A Peer-to-Peer Resource Sharing Scheme Using Trusted Computing Technology

Facing the increasing security issues in P2P networks, a scheme for resource sharing using trusted computing technologies is proposed in this paper. We advance a RS-UCON model with decision continuity and attribute mutability to control the usage process and an architecture to illustrate how TC technologies support policy enforcement with bidirectional attestation. The properties required for attestation should include not only integrity measurement value of platform and related application, but also reputation of users and access history, in order to avoid the limitation of the existing approaches. To make a permission, it is required to evaluate both the authorization and conditions of the subject and the object in resource usage to ensure trustable resources to be transferred to trusted users and platform.

CRESS: A Platform of Infrastructure Resource Sharing for Educational Cloud Computing

Cloud computing is very attractive for schools, research institutions and enterpri- ses which need reducing IT costs, improving computing platform sharing and meeting lice- nse constraints. Sharing, management and on- demand allocation of network resources are particularly important in Cloud computing. Ho- wever, nearly all-current available cloud com- puting platforms are either proprietary or their software infrastructure is invisible to the rese- arch community except for a few open-source platforms. For universities and research insti- tutes, more open and testable experimental plat- forms are needed in a lab-level with PCs. In this paper, a platform of infrastructure resou- rce sharing system （Platform as a Service （PaaS）） is developed in virtual Cloud comput- hug environment. Its architecture, core modules, main functions, design and operational envir- onment and applications are introduced in de- tail. It has good expandability and can impr- ove resource sharing and utilization and is app- lied to regular computer science teaching and research process.

An overview of the resources and environment conditions and major geological problems in the Yangtze River economic zone, China

Focusing on the Yangtze River economic zone,the previous geological researches are systematically summarized,resources and environment conditions and major geological problems which are needing to be concerned in land planning and construction are studied.The results show that the resource conditions of cultivated land,shale gas,geotherm,lithium and so on are superior in the Yangtze River economic zone,and the resources and environment conditions are conducive to develop the modern agriculture,clean energy industry and strategic emerging industries.3×1013 m^2 farmlands without heavy metal pollution are concentrated;there are three national level shale gas exploration and development bases with explored reserves of 5.441×1011 m^3;geothermal availability is 2.4×109 t of standard coal each year,equivalent to 19% of the amount of coal in 2014;Asia's largest energy lithium metal ore deposit is found.In some parts of Yangtze River economic zone,there are some major geological problems such as active faults,karst collapse,ground subsidence,landslide-collapse-debris flow,affecting the river-crossing channels,high-speed railway,urban agglomeration and green ecological corridor planning and construction.Those problems should be concerned,and the relevant suggestions and countermeasures are put forward.Meanwhile,the ideas to further support the development of the Yangtze River economic zone are put forward.

Approximate Dynamic Programming for Stochastic Resource Allocation Problems

A stochastic resource allocation model, based on the principles of Markov decision processes(MDPs), is proposed in this paper. In particular, a general-purpose framework is developed, which takes into account resource requests for both instant and future needs. The considered framework can handle two types of reservations(i.e., specified and unspecified time interval reservation requests), and implement an overbooking business strategy to further increase business revenues. The resulting dynamic pricing problems can be regarded as sequential decision-making problems under uncertainty, which is solved by means of stochastic dynamic programming(DP) based algorithms. In this regard, Bellman’s backward principle of optimality is exploited in order to provide all the implementation mechanisms for the proposed reservation pricing algorithm. The curse of dimensionality, as the inevitable issue of the DP both for instant resource requests and future resource reservations,occurs. In particular, an approximate dynamic programming(ADP) technique based on linear function approximations is applied to solve such scalability issues. Several examples are provided to show the effectiveness of the proposed approach.

Research and Simulation of Parking Resource Sharing Mode in Old Community—Taking Yingmenkou Community as an Example

In recent years, the number of permanent residents in Chengdu, Sichuan Province, China has continued to grow, and the number of private cars keeps rising. A series of problems caused by difficult parking and random parking in old communities are common. This paper will take the parking problem of the old community in Yingmenkou community, Chengdu, China as an example to summarize the current situation and parking problems of the private car parking facilities in these old communities. Based on Chengdu’s current old community parking management policy, parking facility renovation and expansion policy, this paper researches and establishes a parking resource sharing model suitable for old communities. The simulation results show that this model has a small footprint and is easy to install and disassemble. It can be freely spliced and combined units according to the size of the old community and the needs of residents. It is suitable for old communities with no centralized parking lot and high parking demand by residents.

Generative Neural Network Based Spectrum Sharing Using Linear Sum Assignment Problems

Spectrum management and resource allocation(RA)problems are challenging and critical in a vast number of research areas such as wireless communications and computer networks.The traditional approaches for solving such problems usually consume time and memory,especially for large-size problems.Recently different machine learning approaches have been considered as potential promising techniques for combinatorial optimization problems,especially the generative model of the deep neural networks.In this work,we propose a resource allocation deep autoencoder network,as one of the promising generative models,for enabling spectrum sharing in underlay device-to-device(D2D)communication by solving linear sum assignment problems(LSAPs).Specifically,we investigate the performance of three different architectures for the conditional variational autoencoders(CVAE).The three proposed architecture are the convolutional neural network(CVAECNN)autoencoder,the feed-forward neural network(CVAE-FNN)autoencoder,and the hybrid(H-CVAE)autoencoder.The simulation results show that the proposed approach could be used as a replacement of the conventional RA techniques,such as the Hungarian algorithm,due to its ability to find solutions of LASPs of different sizes with high accuracy and very fast execution time.Moreover,the simulation results reveal that the accuracy of the proposed hybrid autoencoder architecture outperforms the other proposed architectures and the state-of-the-art DNN techniques.

Incentive Mechanism Model Design for Sharing of Information Resources in Rural Areas

In order to solve the issues concerning the cross-unit sharing of information resources in rural areas, we analyze the incentive problem of the sharing of information resources in rural areas using the incentive theory method; establish corresponding incentive mechanism model (It is divided into positive incentive model and negative incentive model, and only when the two models guarantee each other and are used at the same time can they be effective). Based on this, we put forward the institutional design for sharing of information resources in rural areas as follows: firstly, establishing an administrative agency of rural information resources sharing, above the authority of all units, responsible for related work on sharing of information resources in rural areas; secondly, establishing and improving the positive and negative incentive mechanisms, to ensure the realization of sharing of information resources in rural areas.

Inter-Network Resource Sharing in IEEE 802.22 Networks

IEEE 802.22 is the first worldwide standard for Cognitive Networks (CNs) that exploits unused spectrum of the television broadcast service. An IEEE 802.22 network is also called Wireless Regional Area Network (WRAN). An open issue in cognitive 802.22 networks is represented by the resource distribution among WRANs. In this paper a protocol for radio resource management for CNs in a multichannel environment is presented and analysed. In particular, the contribution of this work is a resource sharing method to schedule the WRAN access to the available channels in a community made by two o more coexisting WRANs. The method adapts to the continuous changes of the spectrum availability due to necessity of vacating a channel in case of the incumbent primary users. Moreover, the introduced allocation scheme allows to divide the available band in a proportional way to the cognitive user spectrum demands, taking into account the issue of spatial diversity, i.e. the case where the channel coverage area is not uniform. The effectiveness of the proposed multichannel scheme is proved through simulations. The results compared favorably with other methods already known in literature and show that the proposed algorithm optimize the spectral efficiency, keeping high fairness as demonstrated computing the Jain’s index.

Research on the Strategy of Information Resource Sharing between Governments in the Perspective of Game Theory

In order to improve the operational efficiency, the government can realize the streamlining policy through the mode of government information resource sharing. By building government information resources sharing, the government breaks the inter-departmental data island. The government realizes the development direction and trend of “Internet government”. This paper also takes the information resource sharing as the game process between the government management department and the information resource sharing body, and analyzes the policy and suggestion of the information resource sharing in the perspective of game theory by constructing the sharing model of the government information resource in the perspective of game theory.