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。     

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。     

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.     

基于开放式架构的DDS研究与实现

华睿2号嵌入式实时平台具备实时性、灵活性等优点。基于华睿2号开放式架构综合比较,选择合理的通信中间件技术,即使用DDS来构建数据分发系统。在华睿2号平台上适配DDS所需要的传输插件、硬件结构等,以完成DDS在华睿2号平台上的部署。在完成DDS基本的QOS配置同时,根据传输方式来配置额外的QOS策略。最后,在平台实现DDS的测试与分析。对比DDS UDP传输,DDS RapidIO传输、DDS RapidIO DMA传输、逐步升级与优化,达到高实时性、高稳定性、大数据量的要求。     

基于MPLS的网络服务质量分析

本文针对软交换网络服务质量中的分组丢失问题,研究了控制和业务相分离的软交换网络的体系结构,讨论了电信网络的演进趋势。论文从IP技术的角度,分析了分组丢失的原因以及以分组为对象和以网络为对象的解决方案,重点讨论了多协议标签技术对服务质量的保证措施,利用该技术解决服务质量可以保证网络良好的可靠性和安全性,系统开销也会很小。     

基于时间槽的可降带宽核心网视频业务动态资源预约算法

为了解决未来核心网络中大容量、低延时视频业务的服务质量保证问题,以视频会议业务为例,在基于软件定义网络的核心网络框架下,将视频会议请求解析为多个资源请求,以时间槽为单位进行带宽资源的提前预约,提出一种可降带宽的资源预约算法. 在进行动态资源预约时,若发现在某个时间比例内链路不满足视频业务带宽需要,则采用降带宽的方式进行处理,以避免视频业务在某个较短时间段内因带宽不满足需求而导致预约失败. 仿真实验结果表明：相比不采用降带宽的动态资源算法,该算法能够有效提高视频业务资源预约的成功率,参会方个数越多,时间槽越小,成功率的提升越大.