The Sharing Management of Digital Communication Network Resource

Along with the mature development of the domestic computer technology and communication technology, it is an inevitable trend to integrate the two major information technologies together in the future reform of the social communication model. Under this background, the principle of digital communication is introduced first in this paper, and accordingly the role of the communication network resources sharing is analyzed, and finally the sharing management of digital communication network resources is proposed. Hopefully. this paper can play a help in the future subsequent study.

The Sharing Management of Digital Communication Network Resource

Along with the mature development of the domestic computer technology and communication technology, it is an inevitable trend to integrate the two major information teclmologies together in the future reform of the social communication model. Under this background, the principle of digital co,nmunication is introduced first in this paper, and accordingly the role of the communication network resources sharing is analyzed, and finally the sharing management of digital communication network resources is proposed. Hopefully, this paper can play a help in the future subsequent study.

A Self-Attention Based Dynamic Resource Management for Satellite-Terrestrial Networks

The satellite-terrestrial networks possess the ability to transcend geographical constraints inherent in traditional communication networks,enabling global coverage and offering users ubiquitous computing power support,which is an important development direction of future communications.In this paper,we take into account a multi-scenario network model under the coverage of low earth orbit(LEO)satellite,which can provide computing resources to users in faraway areas to improve task processing efficiency.However,LEO satellites experience limitations in computing and communication resources and the channels are time-varying and complex,which makes the extraction of state information a daunting task.Therefore,we explore the dynamic resource management issue pertaining to joint computing,communication resource allocation and power control for multi-access edge computing(MEC).In order to tackle this formidable issue,we undertake the task of transforming the issue into a Markov decision process(MDP)problem and propose the self-attention based dynamic resource management(SABDRM)algorithm,which effectively extracts state information features to enhance the training process.Simulation results show that the proposed algorithm is capable of effectively reducing the long-term average delay and energy consumption of the tasks.

A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks

As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.

ICI Management for Efficient Radio Resource Allocation in Multi-Cell OFDMA Networks

Two Inter-cell Interference (ICI) management algorithms: Primary Interference Balancing (PIB) algorithm and Interfering Bits Loading Avoidance (IBLA) algorithm are proposed for canceling the ICI effects which the existing efficient radio resource allocation algorithms do not consider. The efficient radio resource allocation algorithm, i.e., Pre-assignment and Reassignment (PR) algorithm, obtains the lowest complexity and achieves good throughput performance in single cell OFDMA system. However, in multi-cell multi-sector OFDMA networks, PR algorithm is not applicable because it does not take ICI into consideration. The proposed PIB algorithm balances the number of loading bits for the desired User Equipment (UE) and the major interfering UE, as well as optimizes the SINR performance; meanwhile, IBLA avoids loading certain number of interfering bits which would make SINR unqualified. Simulations confirm the ICI management effectiveness and feasibility of both the proposals.

What to Cache：Differentiated Caching Resource Allocation and Management in Information-Centric Networking

Information-centric networking(ICN) aims to improve the efficiency of content delivery and reduce the redundancy of data transmission by caching contents in network nodes. An important issue is to design caching methods with better cache hit rate and achieve allocating on-demand. Therefore, an in-network caching scheduling scheme for ICN was designed, distinguishing different kinds of contents and dynamically allocating the cache size on-demand. First discussing what was appropriated to be cached in nodes, and then a classification about the contents could be cached was proposed. Furthermore, we used AHP to weight different contents classes through analyzing users' behavior. And a distributed control process was built, to achieve differentiated caching resource allocation and management. The designed scheme not only avoids the waste of caching resource, but also further enhances the cache availability. Finally, the simulation results are illustrated to show that our method has the superior performance in the aspects of server hit rate and convergence.

Traffic Characteristics Based Dynamic Radio Resource Management in Heterogeneous Wireless Networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks(HWNs)has radically increased the complexity of radio resource management and its performance analysis.In this paper,a Simplified Dynamic Hierarchy Resource Management(SDHRM)algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic.In network-level resource allocation,the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility.In connection-level network selection,based on the above resource allocation and the pre-defined QoS requirement,three typical network selection policies are provided to assign traffic flow to the most appropriate network.Furthermore,based on multidimensional Markov model,we analyse the performance of SDHRM in HWNs with heavy tailed traffic.Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.

AMAD:Adaptive Mapping Approach for Datacenter Networks,an Energy-Friend Resource Allocation Framework via Repeated Leader Follower Game

Cloud Datacenter Network(CDN)providers usually have the option to scale their network structures to allow for far more resource capacities,though such scaling options may come with exponential costs that contradict their utility objectives.Yet,besides the cost of the physical assets and network resources,such scaling may also imposemore loads on the electricity power grids to feed the added nodes with the required energy to run and cool,which comes with extra costs too.Thus,those CDNproviders who utilize their resources better can certainly afford their services at lower price-units when compared to others who simply choose the scaling solutions.Resource utilization is a quite challenging process;indeed,clients of CDNs usually tend to exaggerate their true resource requirements when they lease their resources.Service providers are committed to their clients with Service Level Agreements(SLAs).Therefore,any amendment to the resource allocations needs to be approved by the clients first.In this work,we propose deploying a Stackelberg leadership framework to formulate a negotiation game between the cloud service providers and their client tenants.Through this,the providers seek to retrieve those leased unused resources from their clients.Cooperation is not expected from the clients,and they may ask high price units to return their extra resources to the provider’s premises.Hence,to motivate cooperation in such a non-cooperative game,as an extension to theVickery auctions,we developed an incentive-compatible pricingmodel for the returned resources.Moreover,we also proposed building a behavior belief function that shapes the way of negotiation and compensation for each client.Compared to other benchmark models,the assessment results showthat our proposed models provide for timely negotiation schemes,allowing for better resource utilization rates,higher utilities,and grid-friend CDNs.

HAS Dynamic Buffer-Driven Resource Management to Enhance QoE in Mobile Network

Hypertext transfer protocol(HTTP) adaptive streaming(HAS) plays a key role in mobile video transmission. Considering the multi-segment and multi-rate features of HAS, this paper proposes a buffer-driven resource management(BDRM) method to enhance HAS quality of experience(QoE) in mobile network. Different from the traditional methods only focusing on base station side without considering the buffer, the proposed method takes both station and client sides into account and end user's buffer plays as the drive of whole schedule process. The proposed HAS QoE influencing factors are composed of initial delay, rebuffering and quality level. The BDRM method decomposes the HAS QoE maximization problem into client and base station sides separately to solve it in multicell and multi-user video playing scene in mobile network. In client side, the decision is made based on buffer probe and rate request algorithm by each user separately. It guarantees the less rebuffering events and decides which HAS segment rate to fetch. While, in the base station side, the schedule of wireless resource is made to maximize the quality level of all access clients and decides the final rate pulled from HAS server. The drive of buffer and twice rate request schemes make BDRMtake full advantage of HAS's multi-segment and multi-rate features. As to the simulation results, compared with proportional fair(PF), Max C/I and traditional HAS schedule(THS) methods, the proposed BDRM method decreases rebuffering percent to 1.96% from 11.1% with PF and from 7.01% with THS and increases the mean MOS of all users to 3.94 from 3.42 with PF method and from 2.15 with Max C/I method. It also guarantees a high fairness with 0.98 from the view of objective and subjective assessment metrics.

A Frameless Network Architecture for the Way Forward of C-RAN

The key technologies involved in the evolution of the Cloud-based Radio Access Network(C-RAN) are discussed in this paper. Taking the Frameless Network Architecture(FNA) as a starting point, a cell-lessbased network topology for a multi-tier Heterogeneous Network(Het Net) and ultra-dense network is proposed. The FNA network topology modeling is researched with centralized processing and distributed antenna deployments. The Antenna Element(AE) is released as a new dimensional radio resource that is included in the centralized Radio Resource Management(RRM) processes. This contributes to the on-demand user-centric serving-set associations with cell-edge effect elimination. The Control Plane(CP) and User Plane(UP) separation and adaptation are introduced for energy efficiency improvements. The centralized RRM and different optimization goals are discussed for fully exploring the merits from the centralized computing of C-RAN. Considering the complexity, near-optimal approaches for specific users' Quality-of-Service(Qo S) requirements are addressed. Finally, based on the research highlighted above, the way forward of C-RAN evolution is discussed.

Optimizing Resource Management for IoT Devices in Constrained Environments

Embedded computing device implementation on the Internet of Things (IoT) requires careful assessment of their intrinsic resource limitations. These constraints are not limited to memory and processing capabilities but extend to the network interfaces, particularly due to the low-power radio standards that these devices typically employ. The IPv6 protocol is shown to be a strong option for guaranteeing interoperability in the IoT, mostly because of its large address space, the range of current IP-based protocols, and its intrinsic versatility. Considering these benefits, we investigate if current IP-based network management protocols can be implemented on devices with limited resources. We investigate the resource needs in particular for implementing Network Configuration Protocol (NETCONF) and Simple Network Management Protocol (SNMP) on an 8-bit AVR-based device. Our investigation reveals the specific memory and processing demands of these protocols, providing valuable insights into their practicality and efficiency in constrained IoT environments. This study underscores the potential and challenges of leveraging IPv6-based network management protocols to enhance the functionality and interoperability of IoT devices while operating within stringent resource limitations.

Differential Game Based Link Resource Management for Next Generation Optical Network

In this paper, we investigate the link resource management problem for optical networks, to achieve the resource cost during the information transmission. We use the differential game to formulate the cost control problem for the link resource management, to minimize the resource allocation cost functions, which dynamic behaviours are described by differential equations. Each link controls its transmission bandwidth based on the Nash equilibriums of the differential game. The effectiveness of the proposed model is given through numerical simulations.

Efficient Resource Allocation with Improved Interference Mitigation in FFR-Aided OFDMA Heterogeneous Networks

Fractional frequency reuse(FFR) has recently emerged as an efficient inter-cell interference coordination technique for orthogonal frequency division multiple access(OFDMA) based multi-tier cellular networks due to its low complexity, minimal signaling over-head, and coverage improvement. In this work, an intermediary region(IR) at the border of the center region(CR) and edge region(ER) is defined, which prevents severe cross-tier interference and is usually ignored by other schemes. Furthermore, a strategic resource allocation scheme is proposed, which allows macro users in this new region to be served more resources due to their good channel conditions close to the serving base station(BS), while femto users are assigned resource blocks from sub-bands that receive the least net interference from a set of usable sub-bands in any region. We find by analysis and simulation the optimal threshold for IR, which minimizes the cross-tier interference, and show that the femto throughput is also maximized for this threshold. Numerical results show the proposed scheme outperforms other notable schemes in terms of throughput and outage performances.

Ultra Dense Satellite-Enabled 6G Networks:Resource Optimization and Interference Management

With the evolution of the sixth generation(6G)mobile communication technology,ample attention has gone to the integrated terrestrial-satellite networks.This paper notes that four typical application scenarios of integrated terrestrial-satellite networks are integrated into ultra dense satellite-enabled 6G networks architecture.Then the subchannel and power allocation schemes for the downlink of the ultra dense satellite-enabled 6G heterogeneous networks are introduced.Satellite mobile edge computing(SMEC)with edge caching in three-layer heterogeneous networks serves to reduce the link traffic of networks.Furthermore,a scheme for interference management is presented,involving quality-of-service(QoS)and co-tier/cross-tier interference constraints.The simulation results show that the proposed schemes can significantly increase the total capacity of ultra dense satellite-enabled 6G heterogeneous networks.

An Analysis of the Value of Additional Information Provided by Water Quality Measurement Network

European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationalization of monitoring networks and, therefore, on the economic value of information produced by these networks. The aim of this article is to contribute to this reflection. To do so, we used the Bayesian framework to define the value of additional information in relation to the following three parameters: initial assumptions (prior probabilities) on the states of nature, costs linked to a poor decision (error costs) and accuracy of additional information. We then analyzed the impact of these parameters on this value, particularly the combined role of prior probabilities and error costs that increased or decreased the value of information depending on the initial uncertainty level. We then illustrated the results using a case study of a stream in the Bas-Rhin department in France.

Machine Learning for Network Slicing Resource Management:A Comprehensive Survey

The emerging technology of multi-tenancy network slicing is considered as an es sential feature of 5G cellular networks.It provides network slices as a new type of public cloud services and therewith increases the service flexibility and enhances the network re source efficiency.Meanwhile,it raises new challenges of network resource management.A number of various methods have been proposed over the recent past years,in which machine learning and artificial intelligence techniques are widely deployed.In this article,we provide a survey to existing approaches of network slicing resource management,with a highlight on the roles played by machine learning in them.

Agricultural Water Resources Utilization and Management under Agricultural Safety Aim Based on Fuzzy Neural Network Algorithm

[Objectives]To explore the agricultural water resources utilization and management under the agricultural safety aim.[Methods]Fuzzy neural network algorithm was adopted.The evaluation model of agricultural water resources utilization and management carrying capacity based on quantitative system was established.[Results]With the remarkable improvement of China's national income,great progress has been made in China's agricultural development.However,in the process of agricultural safety production,the problem of sustainable development has not been noticed,the problem of water resources exceeding the limit bearing capacity frequently occurs.[Conclusions]It is of great significance to effectively solve the problem of water resources utilization and management.In the feasibility test for the algorithm,further tests on various indicators show that the research is feasible.

Construction of overlay network based on P2P technology in Grid environment

Based on the advantages of both Grid and peer-to-peer （P2P） networks, an overlay network in the Grid environment is constructed by P2P technologies by a modified version of the Chord protocol. In this mechanism, different nodes＇ accesses to different resources are determined by their contribution. Therefore, the heterogeneous resources of virtual organizations in large-scale Grid can be effectively integrated, and the key node failure as well as system bottleneck in the traditional Grid environment is eliminated. The experimental results indicate that this management mechanism can achieve better average performance in the Grid environment and maintain the P2P characteristics as well.

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.

Blockchain-enabled resource management and sharing for 6G communications

The sixth-generation(6G)network must provide better performance than previous generations to meet the requirements of emerging services and applications,such as multi-gigabit transmission rate,higher reliability,and sub-1 ms latency and ubiquitous connection for the Internet of Everything(IoE).However,with the scarcity of spectrum resources,efficient resource management and sharing are crucial to achieving all these ambitious requirements.One possible technology to achieve all this is the blockchain.Because of its inherent properties,the blockchain has recently gained an important position,which is of great significance to the 6G network and other networks.In particular,the integration of the blockchain in 6G will enable the network to monitor and manage resource utilization and sharing efficiently.Hence,in this paper,we discuss the potentials of the blockchain for resource management and sharing in 6G using multiple application scenarios,namely,Internet of things,deviceto-device communications,network slicing,and inter-domain blockchain ecosystems.