Exploiting demand-side heterogeneous flexible resources in risk management of power system frequency

More demand-side flexible resources(DFRs)are participating in the frequency regulation of renewable power systems,whose heterogeneous characteristics have a significant impact on the system frequency response.Consequently,selecting suitable DFRs poses a formidable challenge for independent system operators(ISO).In this paper,a reserve allocation methodology for heterogeneous DFRs is proposed to manage the risk of power system frequency.Firstly,a performance curve is developed to describe the cost,capacity,and response speed of DFRs.Moreover,a clustering method for multiple distributed DFRs is conducted to calculate the aggregated performance curves and uncertainty coefficients.Then,the frequency security criterion considering DFRs’performance is constructed,whose linearity makes it can be easily coupled into the system scheduling model and solved.Furthermore,a risk management model for DFRs considering frequency-chance-constraint is proposed to make a trade-off between cost and frequency security.Finally,the model is transformed into mixed integer second-order cone programming(MISOCP)and solved by the commercial solver.The proposed model is validated by the IEEE 30 and IEEE 118 bus systems.

Resource Control Architecture in Heterogeneous Networks

TISPAN,from a fixed access perspective,proposes Resource and Admission Control Subsystem[0](RACS) as a solution to Quality of Service(QoS) problem for NGN bearer network.In contrast,3GPP has an approach to this from the perspective of mobile access.In the latest 3GPP R7 draft,integration of Policy Control Function(PCF) with Flow Based Charging(FBC) function of the R6 brought forward policy control and charging.With the development of fixed mobile convergence,the inconsistence in architectures and interfaces of different resource and admission control[0] solutions will have a huge impact on manufacture and network implementation of NGN related equipment.To solve this problem,both 3GPP and TISPAN have been working on the convergence of Gq’/Rx reference points.Harmonized Policy Control and Charging(PCC) proposed by the Next Generation Mobile Network(NGMN) forum,i.e.cooperative resource control architecture for heterogeneous networks,represents an evolutional sign post for resource control technology for heterogeneous network architecture.

Intelligent Scheduling Strategies for Computing Power Resources in Heterogeneous Edge Networks

The edge computing model enables real-time and low-power processing of data,while contributing to data security and privacy protection.However,the heterogeneity and diversity of edge computing devices pose a great challenge to task scheduling and migration.Most of the existing studies only consider the allocation of computational resources,but lack comprehensive consideration of data resources,storage space,etc.In this paper,we proposed intelligent scheduling strategies for computing power resources in heterogeneous edge networks.We define the relevant models and construct a comprehensive matching matrix in terms of task matching with computing resources,data resources,storage resources,load balancing of computing devices and storage space matching,and design an intelligent scheduling algorithm based on iteration and load balancing according to the matching degree of tasks and computing devices in the heterogeneous edge network environment.The iterative and load-balanced scheduling algorithm is based on the least-cost flow solution scheduling strategy,which effectively reduces the task computation response time and improves the computation and storage resource utilization of computing devices.Experimental validation of the proposed intelligent scheduling strategy is carried out based on a simulation environment.The experimental results show that the proposed intelligent scheduling strategy has obvious advantages over random scheduling methods in terms of task processing delay,computing power resource utilization and number of satisfactory tasks.

Minimizing Energy Cost for Green Data Center by Exploring Heterogeneous Energy Resource

With the deteriorating effects resulting from global warming in many areas, geographically distributed data centers contribute greatly to carbon emissions, because the major energy supply is fossil fuels. Considering this issue, many geographically distributed data centers are attempting to use clean energy as their energy supply, such as fuel cells and renewable energy sources. However, not all workloads can be powered by a single power sources, since different workloads exhibit different characteristics. In this paper, we propose a fine-grained heterogeneous power distribution model with an objective of minimizing the total energy costs and the sum of the energy gap generated by the geographically distributed data centers powered by multiple types of energy resources. In order to achieve these two goals, we design a two-stage online algorithm to leverage the power supply of each energy source. In each time slot, we also consider a chance-constraint problem and use the Bernstein approximation to solve the problem. Finally, simulation results based on real-world traces illustrate that the proposed algorithm can achieve satisfactory performance.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.

Genetic algorithm for autonomic joint radio resource management in end-to-end reconfigurable systems

This article presents the genetic algorithm （GA） as an autonomic approach for the joint radio resource management （JRRM） amongst heterogeneous radio access technologies （RATs） in the end-to-end reconfigurable systems. The joint session admission control （JOSAC） and the bandwidth allocation are combined as a specific decision made by the operations of the genetic algorithm with certain advisable modifications. The proposed algorithm is triggered on the following two conditions When a session is initiated, it is triggered for the session to camp on the most appropriate RAT and select the most suitable bandwidth for the desired service. When a session terminates, it is also used to adjust the distribution of the ongoing sessions through the handovers. This will increase the adjustment frequency of the JRRM controller for the best system performance. Simulation results indicate that the proposed autonomic JRRM scheme not only effectively reduces the handover times, but also achieves well trade-off between the spectrum utility and the blocking probability.

The relative and combined effects of herbivore assemblage and soil nitrogen on plant diversity

Plant diversity can be affected by both herbivore grazing and soil resources. However, it is unclear if the joint effects of herbivores and soil resources might vary with components of plant diversity. Here, we evaluated the relative and combined effects of herbivore assemblage and soil nitrogen(N) quantity and heterogeneity on the α and β components of plant diversity in a grassland that was subjected to four years of grazing under differing herbivore assemblages(no grazing, cattle grazing, sheep grazing, and mixed grazing). We found that herbivore assemblage combined with soil N quantity explained 41% of the variation in plant α-diversity, while herbivore assemblage combined with soil N heterogeneity explained 15% of the variation in plant β-diversity. The independent effects of herbivore assemblage explained more than those of soil N for both α-and β-diversity(α-diversity: 12% vs. 4%;β-diversity: 18% vs. 16%). We concluded that the effects of herbivores are stronger than those of soil N,and that grazing-induced changes in soil resources are important drivers of plant diversity change, especially α-diversity.Therefore, we suggest that managing herbivore species by accounting for the effects that their grazing can have on soil resources may be significant for plant diversity maintenance.