Transmission in mobile cloudlet systems with intermittent connectivity in emergency areas

The recent development of Mobile Cloud Computing has helped in solving numerous real-life problems. The rate of growth of mobile devices has been increasing at a very high pace. Mobile devices have made substantial contributions in managing emergency situations. Owing to the mobility of mobile devices, cloudlets, and their intermittent connectivity, it may become very difficult to handle emergency situations. To address this problem, a transmission model is proposed for mobile cloudlet systems, where a mobile device is used to designate a cloudlet by using the Borda scores Method and the mobile device can offload a part of its application to this cloudlet. The simulation results demonstrated that the proposed work makes a significant comtribution toward alleviating the problems associated with emergency situations.     

Edge Computing Based Applications in Vehicular Environments: Comparative Study and Main Issues

Journal of Computer Science and Technology - Despite the expanded efforts, the vehicular ad-hoc networks (VANETs) are still facing many challenges such as network performances, network scalability...     

Cloudlet-based Efficient Data Collection in Wireless Body Area Networks

Wireless Body Area Networks (WBANs) have developed as an effective solution for a wide range of healthcare, military and sports applications. Most of the proposed works studied efficient data collection from individual and traditional WBANs. Cloud computing is a new computing model that is continuously evolving and spreading. This paper presents a novel cloudlet-based efficient data collection system in WBANs. The goal is to have a large scale of monitored data of WBANs to be available at the end user or to the service provider in reliable manner. A prototype of WBANs, including Virtual Machine (VM) and Virtualized Cloudlet (VC) has been proposed for simulation characterizing efficient data collection in WBANs. Using the prototype system, we provide a scalable storage and processing infrastructure for large scale WBANs system. This infrastructure will be efficiently able to handle the large size of data generated by the WBANs system, by storing these data and performing analysis operations on it. The proposed model is fully supporting for WBANs system mobility using cost effective communication technologies of WiFi and cellular which are supported by WBANs and VC systems. This is in contrast of many of available mHealth solutions that is limited for high cost communication technology, such as 3G and LTE. Performance of the proposed prototype is evaluated via an extended version of CloudSim simulator. It is shown that the average power consumption and delay of the collected data is tremendously decreased by increasing the number of VMs and VCs.     

交互感知应用微云服务框架

当前,开发使用微云服务的交互感知应用时存在开发困难以及重复开发的问题.为解决这些问题,设计并实现了为交互感知应用提供微云服务的框架Bolt.Bolt服务框架以ZeroMQ消息处理队列为基础,分为三部分：Bolt Client Lib库、Bolt Service Lib库以及Bolt Broker代理,构成“Client-Broker-Service”的三级架构.Bolt Client Lib和Bolt Service Lib分别为移动端应用和微云端处理引擎分别提供API,使应用与处理引擎的开发得以分离,降低了开发难度并减少重复开发的情况.实验结果表明,与Gabriel等应用相比,Bolt服务框架使用的通信端口降低到2个,同时,将系统开销降低到1ms左右的时间.     

移动微云任务迁移与调度

为了解决移动微云中时间期限约束下的任务能效调度问题,提出一种基于自适应概率的分布式任务调度算法。算法分为两个阶段:资源发现阶段和自适应概率调度阶段。第一阶段主要通过修正的QoS OLSR协议,使发送任务执行请求的源节点周期性地收集邻近处理节点的资源信息;第二阶段主要根据源节点的任务到达率,以概率计算方式选择最优的处理节点执行任务,在满足时间约束的同时,达到最优的能效。经过大量仿真场景的验证,结果表明该算法在维持较高的任务完成率的同时,还可以降低任务完成的平均能耗。     

Multiobjective computation offloading for workflow management in cloudlet‐based mobile cloud using NSGA‐II

Cloudlet is a novel computing paradigm, introduced to the mobile cloud service framework, which moves the computing resources closer to the mobile users, aiming to alleviate the communication delay between the mobile devices and the cloud platform and optimize the energy consumption for mobile devices. Currently, the mobile applications, modeled by the workflows, tend to be complicated and computation‐intensive. Such workflows are required to be offloaded to the cloudlet or the remote cloud platform for execution. However, it is still a key challenge to determine the offloading resolvent for the deadline‐constrained workflows in the cloudlet‐based mobile cloud, since a cloudlet often has limited resources. In this paper, a multiobjective computation offloading method, named MCO, is proposed to address the above challenge. Technically, an energy consumption model for the mobile devices is established in the cloudlet‐based mobile cloud. Then, a corresponding computation offloading method, by improving Nondominated Sorting Genetic Algorithm II, is designed to achieve the goal of energy saving for all the mobile device while satisfying the deadline constraints of the workflows. Finally, extensive experimental evaluations are conducted to demonstrate the efficiency and effectiveness of our proposed method.     

基于多微云协作的计算任务卸载

针对多微云计算模式下计算任务卸载过程复杂、任务响应时间长的问题,构建面向多微云协作的计算任务卸载模型,并提出加权自适应惯性权重的粒子群优化（WAIW-PSO）算法,快速求解最优卸载策略。首先,对移动终端-微云-远程云的任务执行过程进行建模;其次,考虑多用户对计算资源的竞争,构建基于多微云协作的任务卸载模型;最后,针对求解最佳任务卸载策略复杂度过高的情况,提出WAIW-PSO算法求解卸载问题。仿真实验结果表明,与标准粒子群优化（PSO）算法以及基于高斯函数递减惯性权重的粒子群优化（GDIWPSO）算法相比,WAIW-PSO算法可以根据进化代数和个体适应度综合调整惯性权重,寻优能力较强,求解最优卸载策略的时间最短;在不同设备数、任务数等情况下选择不同任务卸载策略进行对比实验的结果表明,基于WAIW-PSO算法的卸载策略可以明显缩短任务总完成时间。