HSDN‐GRA: A hybrid software‐defined networking‐based geographic routing protocol with multi‐agent approach

We propose in this paper a Hybrid Software‐Defined Networking‐based Geographical Routing Protocol (HSDN‐GRA) with a clustering approach. It takes into account three different criteria to select the best relay to send data: (1) the contact duration between vehicles, (2) the available load of each vehicle, (3) and the log of encountered communication errors embedded in each cluster head. The multi‐criteria strategy allows the selection of the most reliable vehicles by avoiding communication problems and ensuring connection availability. Once the hybrid control plane has found out the next eligible neighbor, the data plane will be in charge of dividing and sending data. To validate our approach, HSDN‐GRA has been modeled and implemented in JADE, a multi‐agent platform, to be compared to other multi‐agent based protocols. Simulation results show that HSDN‐GRA achieves good performance with respect to the average routing overhead, the packet drop rate, and the throughput.     

物联网环境下基于情境的语义Web服务选择

当前Web服务海量增加，物联网应用技术快速发展、不断普及，而现有的Web服务选择算法低效、用户匹配度低。针对该问题提出一种物联网环境下基于情境的语义Web服务选择方法。该方法应用QoS参数的无量纲化与语义Web服务动态选择方式，将物联网环境下服务与语义Web服务相结合，并根据用户需求针对QoS选择最优的服务集。实验表明，该方法能有效地提高用户服务动态选择的成功率。     

Analysis of the risk-sharing ratio in PPP projects based on government minimum revenue guarantees

Public-private partnership (PPP) projects have been widely applied in infrastructure construction. A suitable risk distribution strategy is crucial for promoting negotiations between the government and investors. The government usually provides guarantees to investors to distribute risk. However, an excessive guarantee increases the government's financial burden, whereas an insufficient guarantee reduces the confidence of the investors participating in the project. In a minimum revenue guarantee (MRG), the government subsidizes the investors the difference between the actual revenue and the government guarantee line if there is a loss. In PPP power plant and highway projects, investors' revenues come from two sources: government guarantees and the project company's self-sale. To support project companies and to optimize the projects' benefits, the government should set a reasonable benchmark for purchase amounts. Based on the traditional principal-agent model, this paper introduces the reciprocal preference theory to analyze the risk-sharing ratio most suitable for the government. Then, an optimal incentive mechanism is established to guarantee the project's income. The results indicate that by setting a different guarantee strategy for different participants, the government can utilize reciprocal preference to incentivize investors to exert more effort during a partnership and avoid moral hazard.     

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

一种基于OPNET的DiffServ+WLAN网络多媒体端到端QoS性能仿真方法

提出一种基于OPNET的Diff Serv+WLAN网络多媒体端到端Qo S性能验证方法。该方法主要包括网络拓扑搭建和仿真配置两个模块。其中网络拓扑模块主要完成业务在Diff Serv+WLAN网络的传输过程;仿真配置模块的功能是在Diff Serv+WLAN网络拓扑中进行业务参数的配置、收集统计数据等。利用Pro-C高级语言和Visual C++6.0软件搭建Diff Serv与WLAN网络环境,对原网络和加入IPv6流标签的网络进行多媒体业务端到端Qo S性能验证方法仿真,结果表明该方法具有简单、方便等特点。     

小型煤矿低浓度瓦斯发电技术及应用效果研究

针对云南富源县辖区内大量小型煤矿抽采的低浓度瓦斯未开展有效利用的问题，以区内某小型煤矿为背景，采用现场调研、分析归纳、理论计算相结合的方法对其低浓度瓦斯发电项目展开分析研究。研究表明，某小型煤矿低浓度瓦斯发电项目成功的关键是“瓦斯治理先行”理念主导下的气源保障综合技术体系。在气源得以保障的基础上，该小型煤矿低浓度瓦斯发电项目已经持续高效运行4年，每年创造经济收益约403.2万元，减排CO2约4.47万t；同时促进了煤矿瓦斯治理工作有效落实，提高了煤矿安全生产水平，保障了煤矿产量的达标。     

Machine learning assisted OSP approach for improved QoS performance on 3D charge-trap based SSDs

Three-dimensional (3D) charge-trap based solid-state-drivers (SSDs) have become an emerging storage solution in recent years. One-shot-programming in 3D charge-trap based SSDs could deliver a maximized system input/output (I/O) throughput at the cost of degraded Quality-of-Service (QoS) performance. This paper proposes reinforcement-learning based one-shot-programming (RLOSP), a reinforcement learning based approach to improve the QoS performance for 3D charge-trap based SSDs. By learning the I/O patterns of the workload environments as well as the device internal status, the proposed approach could properly choose requests in the device queue, and allocate physical addresses for these requests during one-shot-programming. In this manner, the storage device could deliver an improved QoS performance. Experimental results reveal that the proposed approach could reduce the worst-case latency at the 99.9th percentile by 37.5%–59.2%, with an optimal system I/O throughput.     

Telesurgery QoS improvement over SDN based on a Type‐2 fuzzy system and enhanced cuckoo optimization algorithm

Telemedicine is a new area based on the information and communication technology for collecting, storing, organizing, retrieving and exchanging medical information. One of the most important applications of telemedicine is indeed telesurgery in which an efficient telecommunication infrastructure between the surgery room and remote surgeons need to be established. One of the most important issues to be tackled in telesurgery is to find favorable links for routing as well as providing high Quality of Service (QoS). In this paper, an efficient model based on the hybridization of Type‐2 Fuzzy System (T2FS) and Cuckoo Optimization Algorithm (COA) over the Software Defined Networks (SDN) is proposed in order to achieve optimal and reliable routes for telesurgery application. Using T2FS, the fitness of the links is determined; then, a COA is conducted over the Constraint Shortest Path (CSP) problem to find the best routes. Delay is considered as a CSP problem which is satisfied by trying to find the paths with minimum cost. Due to the NP‐completeness of the CSP problem, an Enhanced COA (so‐called E‐COA) is proposed and utilized as a metaheuristic solver. To the best of our knowledge, this paper is the first SDN‐based communication model that applies both T2FS and E‐COA for assigning proper costs to the network's links, and solves the consequence CSP problem according to the QoS requirement for telesurgery. The model also recognizes and preserves the second‐best routes in order to keep the reliability for such a critical application. In addition to the simulations, the performance evaluation is also conducted on a real experimental scenario. Many comparisons are carried out between the proposed model and other conventional methods, and the evaluation study shows the superiority of the proposed model on all the three QoS‐related metrics, i.e. average end‐to‐end delay, packet loss ratio and PSNR.     

FogMed: A Fog-Based Framework for Disease Prognosis Based Medical Sensor Data Streams

Recently, an increasing number of works start investigating the combination of fog computing and electronic health (ehealth) applications. However, there are still numerous unresolved issues worth to be explored. For instance, there is a lack of investigation on the disease prediction in fog environment and only limited studies show, how the Quality of Service (QoS) levels of fog services and the data stream mining techniques influence each other to improve the disease prediction performance (e.g., accuracy and time efficiency). To address these issues, we propose a fog-based framework for disease prediction based on Medical sensor data streams, named FogMed. This framework aims to improve the disease prediction accuracy by achieving two objectives: QoS guarantee of fog services and anomaly prediction of Medical data streams. We build a virtual FogMed environment and conduct comprehensive experiments on the public ECG dataset to validate the performance of FogMed. The experiment results show that it performs better than the cloud computing model for processing tasks with different complexities in terms of time efficiency.