Resource collaboration system based on dynamic user preference and context

In a ubiquitous computing environment, service composition and collaboration among heterogeneous resources are required, thus, an infrastructure that supports these requirements is an essential factor in seamless service delivery. In this environment, users hope to get a variety of customized services by using only an individual mobile device. But the resource of the mobile device has limitations such as tiny display screens, limited input, less powerful processors, and limited storage. Moreover each user situation is different and user preferences are also various. Therefore it is one of new issues to provide a customized service for a user through resource collaboration based on various user preference and situation. To solve this issue, this paper proposes a resource collaboration system which infers customized resources for composing a user required service and collaborative with selected resources. For our collaboration system, this paper proposes the method to infer resources based on the context and user preferences including dynamic change of the preference. This paper also shows a reasonable execution environment for the proposed system through the performance evaluation in server-client and peer-to-peer environments.     

An efficient job management of computing service using integrated idle VM resources for high-performance computing based on OpenStack

In recent years, various studies on OpenStack-based high-performance computing have been conducted. OpenStack combines off-the-shelf physical computing devices and creates a resource pool of logical computing. The configuration of the logical computing resource pool provides computing infrastructure according to the user’s request and can be applied to the infrastructure as a service (laaS), which is a cloud computing service model. The OpenStack-based cloud computing can provide various computing services for users using a virtual machine (VM). However, intensive computing service requests from a large number of users during large-scale computing jobs may delay the job execution. Moreover, idle VM resources may occur and computing resources are wasted if users do not employ the cloud computing resources. To resolve the computing job delay and waste of computing resources, a variety of studies are required including computing task allocation, job scheduling, utilization of idle VM resource, and improvements in overall job’s execution speed according to the increase in computing service requests. Thus, this paper proposes an efficient job management of computing service (EJM-CS) by which idle VM resources are utilized in OpenStack and user’s computing services are processed in a distributed manner. EJM-CS logically integrates idle VM resources, which have different performances, for computing services. EJM-CS improves resource wastes by utilizing idle VM resources. EJM-CS takes multiple computing services rather than single computing service into consideration. EJM-CS determines the job execution order considering workloads and waiting time according to job priority of computing service requester and computing service type, thereby providing improved performance of overall job execution when computing service requests increase.

     

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.     

A study on virtual machine deployment for application outsourcing in mobile cloud computing

In mobile cloud computing, application offloading is implemented as a software level solution for augmenting computing potentials of smart mobile devices. VM is one of the prominent approaches for offloading computational load to cloud server nodes. A challenging aspect of such frameworks is the additional computing resources utilization in the deployment and management of VM on Smartphone. The deployment of Virtual Machine (VM) requires computing resources for VM creation and configuration. The management of VM includes computing resources utilization in the monitoring of VM in entire lifecycle and physical resources management for VM on Smartphone. The objective of this work is to ensure that VM deployment and management requires additional computing resources on mobile device for application offloading. This paper analyzes the impact of VM deployment and management on the execution time of application in different experiments. We investigate VM deployment and management for application processing in simulation environment by using CloudSim, which is a simulation toolkit that provides an extensible simulation framework to model the simulation of VM deployment and management for application processing in cloud-computing infrastructure. VM deployment and management in application processing is evaluated by analyzing VM deployment, the execution time of applications and total execution time of the simulation. The analysis concludes that VM deployment and management require additional resources on the computing host. Therefore, VM deployment is a heavyweight approach for process offloading on smart mobile devices.     

无线PKI中具有安全代理的新型CA方案

无线PKI是WAP Forum提出的用于保护无线通信安全的协议。通过使用WPKI，手持设备客户端能够利用公开密钥技术来保护数据的保密性和完整性。由于手持设备存储容量和计算速度都相当受限，只有少量的手持设备能流畅的完成WPKI所必须的计算任务。即使采用了具有强计算能力的手持设备，用户也仅能与采用了WPKI技术的部分服务器进行安全通信。手持设备用户仍然无法和Internet上的任意用户之间建立可靠的连接。通过对现有的无线PKI系统进行分析，提出了无线PKI的一种可选的运行方式。新的运行方式将客户端难以承担的计算任务移植到可信安全代理服务器端，并采用密码协议保证安全代理的正确运行。新协议降低了WPKI框架对无线手持设备的计算和存储能力的要求，同时系统的安全性也得到了进一步的保障。而无线手持设备用户也能够和Internet上的用户进行安全的通信。     

Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets

The deployment of highly interactive, media-rich applications on mobile devices is hindered by the inherent limitations on compute power, memory and battery capacity of these hand-held platforms. The cloudlet concept, opportunistically offloading computation to nearby devices, has proven to be a viable solution in offering resource-intensive applications on mobile devices. In this paper, we propose to extend the cloudlet concept with collaborative scenarios, in which not only hardware resources for processing are shared between all cloudlet users, but also the data computed.In a cloudlet, the resource demand should be spread over all available cloudlet nodes. User mobility and fluctuations in wireless bandwidth will cause the optimal resource allocation to vary over time. The cloudlet middleware must continuously balance the performance gain of reallocating components with the operational costs in terms of user experience and management complexity. In this paper, we formulate this optimization problem based on a theoretical cloudlet model capturing the infrastructure, application structure and user behavior.In order to solve this problem, two heuristic allocation algorithms based on Steepest Descent (SD) and Simulated Annealing (SA) are described. Besides optimality of the found solution, it is also important to limit the number of reallocations at runtime. To evaluate the performance and stability of the algorithms, we propose a discrete-event model for cloudlet simulation. For multiple application scenarios, we observe that SD performs 4 times less reallocations than SA. By introducing hysteresis, the number of reallocations by SA can be nearly halved without any significant degradation of application performance.     

Analytical performance models for resource allocation schemes of cloudlet in mobile cloud computing

The Journal of Supercomputing - In the cloudlet architecture of mobile cloud computing (MCC), the mobile users offload their resource-intensive tasks to a local cloud (i.e., Cloudlet) via WiFi...     

An Architecture for the Integration of Physical and Informational Spaces

While computer processing power, storage capacity, and bandwidth are continuing to experience exponential growth, individual human processing capabilities are not increasing significantly. Pervasive computing offers an opportunity for applications to interact with the physical environment and to provide a task-centric and mobile infrastructure for the user. However, this rich environment can also be distracting, in part because of a lack of convergence between the physical infrastructure observed by users and the information space seen by applications. In this paper we introduce AIPIS, an architecture that bridges the physical and informational realms of the human and the computer, respectively. The purpose of AIPIS is two-fold: (1) provide users with a hands-free computing environment that automates much of the drudgery associated with the use of computers; and (2) require human attention for only critical aspects of task execution that require their input. We also describe the Aura desktop, a first prototype of the AIPIS architecture.     

Social serendipity: mobilizing social software

Many mobile devices incorporate low-power wireless connectivity protocols, such as Bluetooth, that can be used to identify an individual to other people nearby. We have developed an architecture that leverages this functionality in mobile phones - originally designed for communication at a distance - to connect people across the room. Serendipity is an application of the architecture. It combines the existing communications infrastructure with online introduction systems' functionality to facilitate interactions between physically proximate people through a centralized server. A new mobile-phone-based system uses Bluetooth hardware addresses and a database of user profiles to cue informal, face-to-face interactions between nearby users who don't know each other, but probably should.     

IPTV service based on a content-zapping paradigm

Internet protocol television (IPTV) generically designates a real-time distribution service for multimedia contents over an IP network, such as the Internet. There are many advantages of IPTV deployment over current digital or air broadcast TV signals: integration, the use of the switched internet protocol (IP), the possibility to build home networks that can be used to share multimedia contents over different devices, the easy implementation of video on demand services and the usage of better compression and encryption standards. In order to implement this kind of service, it is extremely useful to have a system that can efficiently classify multimedia contents and users and distribute them in a customized way. This paper proposes a novel IPTV service for the distribution of personalized multimedia contents over IP networks based on the concept of content-zapping, in contrast to traditional channel-zapping: each client system receives a multimedia streaming that is automatically composed by the system based on the user preferences and the user will only interact with the system by requesting a content change or marking a content as favorite. The paper will describe the general functionality of the service and will present the detailed architecture of the IPTV server, the key component of the service infrastructure. The server must maintain a list of media contents residing in other systems and must keep a dynamic classification of the multimedia contents that are stored in its database. This classification is built and gradually refined based on the interactions between clients and multimedia contents. Special attention is given in the paper to the classification model, describing the general ideas that are used to automatically suggest multimedia contents to a specific user (that is characterized by his complete profile). A specific content may be suggested to the user based on the knowledge of the user profile and/or based on specific and dynamic information, such as the user position, the local temperature, date and time. The availability of this information obviously depends on the specific user device that is being used. The proposed system allows any client device to connect, allowing a high level of interoperability. It is also possible to use all the device capabilities and sensors, like Global Positioning System (GPS), accelerometers, light sensors, noise sensors, etc., thus creating a context environment that helps classify each user profile. These context-awareness mechanisms applied to mobile devices with wireless network (802.11b/g/n, WiMAX, GSM, UMTS, etc.) capabilities allow a better user experience and more accurate multimedia suggestions, due to the deep knowledge about the user device, network and environment. The system also allows the users to suggest contents to other users in the same “group of friends”. Several performance tests were already conducted and the results obtained show that the proposed system is very stable and fast, even for high increases on the number of users.     

Reducing the network overhead of user mobility–induced virtual machine migration in mobile edge computing

With the popularity of mobile devices (such as smartphones and tablets) and the development of the Internet of Things, mobile edge computing is envisioned as a promising approach to improving the computation capabilities and energy efficiencies of mobile devices. It deploys cloud data centers at the edge of the network to lower service latency. To satisfy the high latency requirement of mobile applications, virtual machines (VMs) have to be correspondingly migrated between edge cloud data centers because of user mobility. In this paper, we try to minimize the network overhead resulting from constantly migrating a VM to cater for the movement of its user. First, we elaborate on two simple migration algorithms (M-All and M-Edge), and then, two optimized algorithms are designed by classifying user mobilities into two categories (certain and uncertain moving trajectories). Specifically, a weight-based algorithm (M-Weight) and a mobility prediction–based heuristic algorithm (M-Predict) are proposed for the two types of user mobilities, respectively. Numerical results demonstrate that the two optimized algorithms can significantly lower the network overhead of user mobility–induced VM migration in mobile edge computing environments.     

On Cost Aware Cloudlet Placement for Mobile Edge Computing

As accessing computing resources from the remote cloud inherently incurs high end-to-end (E2E) delay for mobile users, cloudlets, which are deployed at the edge of a network, can potentially mitigate this problem. Although some research works focus on allocating workloads among cloudlets, the cloudlet placement aiming to minimize the deployment cost (i.e., consisting of both the cloudlet cost and average E2E delay cost) has not been addressed effectively so far. The locations and number of cloudlets have a crucial impact on both the cloudlet cost in the network and average E2E delay of users. Therefore, in this paper, we propose the Cost Aware cloudlet PlAcement in moBiLe Edge computing (CAPABLE) strategy, where both the cloudlet cost and average E2E delay are considered in the cloudlet placement. To solve this problem, a Lagrangian heuristic algorithm is developed to achieve the suboptimal solution. After cloudlets are placed in the network, we also design a workload allocation scheme to minimize the E2E delay between users and their cloudlets by considering the user mobility. The performance of CAPABLE has been validated by extensive simulations.      

移动中间件：移动无线Internet的将来

移动计算正成为一个迅速发展的领域。然而由于移动环境的种种限制,为开发移动应用带来巨大的挑战。文章讨论解决此问题的一种新兴技术：移动中间件技术,并提出一个移动中间件的实际应用体系结构,为移动终端设备提供一种简单、安全的方法访问已存在的分布式对象系统。     

Application-aware cloudlet selection for computation offloading in multi-cloudlet environment

Latency- and power-aware offloading is a promising issue in the field of mobile cloud computing today. To provide latency-aware offloading, the concept of cloudlet has evolved. However, offloading an application to the most appropriate cloudlet is still a major challenge. This paper has proposed an application-aware cloudlet selection strategy for multi-cloudlet scenario. Different cloudlets are able to process different types of applications. When a request comes from a mobile device for offloading a task, the application type is verified first. According to the application type, the most suitable cloudlet is selected among multiple cloudlets present near the mobile device. By offloading computation using the proposed strategy, the energy consumption of mobile terminals can be reduced as well as latency in application execution can be decreased. Moreover, the proposed strategy can balance the load of the system by distributing the processes to be offloaded in various cloudlets. Consequently, the probability of putting all loads on a single cloudlet can be dealt for load balancing. The proposed algorithm is implemented in the mobile cloud computing laboratory of our university. In the experimental analyses, the sorting and searching processes, numerical operations, game and web service are considered as the tasks to be offloaded to the cloudlets based on the application type. The delays involved in offloading various applications to the cloudlets located at the university laboratory, using proposed algorithm are presented. The mathematical models of total power consumption and delay for the proposed strategy are also developed in this paper.     

智能计算服务的需求获取方法

智能计算服务由服务提供者通过互联网为服务消费者提供数据的分析和处理，并建立学习模型完成智能计算功能。由于服务提供者与服务消费者之间缺乏有效的沟通渠道，以及服务消费者反馈的需求描述模糊、混乱，目前缺乏一种统一的服务需求获取方法对用户持续变化的需求进行有效的分析、组织和规约，导致智能计算服务无法根据用户的需求进行快速改进。针对服务开发中需求变更的持续性和不确定性等问题，提出了一种智能计算服务的需求获取方法。该方法首先从Stack Overflow问答论坛获取智能计算服务的应用反馈和问题，然后根据服务消费者所关注的需求类型采用不同的学习模型（包括支持向量机（SVM）、朴素贝叶斯和TextCNN）对其进行知识分类和优先级排序，最后采用自定义的服务需求模板统一描述智能计算服务的需求。     

一种高效存储解决方案的分析与研究

企业的关键信息以几何级速度增长,更多的数据需要保存更长的时间,面对TB甚至是PB级海量数据如何进行高效存储成为研究的重点.伴随着云计算和云存储的发展,对后端的高效存储和管理成为存储方面的重点研究问题,高效存储和管理不仅为用户提供更高质量的服务,而且还可以降低用户成本,实现高效低碳的环保型存储,这其中主要用到了多协议访问、存储虚拟化、自动精简配置、重复数据删除等关键技术.     

Context-awareness in wearable and ubiquitous computing

A common focus shared by researchers in mobile, ubiquitous and wearable computing is the attempt to break away from the traditional desktop computing paradigm. Computational services need to become as mobile as their users. Whether that service mobility is achieved by equipping the user with computational power or by instrumenting the environment, all services need to be extended to take advantage of the constantly changing context in which they are accessed. This paper will report on work carried out by the Future Computing Environments Group at Georgia Tech to provide infrastructure for context-aware computing. We will describe some of the fundamental issues involved in contextaware computing, solutions we have generated to provide a flexible infrastructure and several applications that take advantage of context awareness to allow freedom from traditional desktop computing.     

Look, Ma, My homepage is Mobile!

Much of the ongoing research in ubiquitous computing has concentrated on providing context information, e.g. location information, to the level of services and applications. Typically, mobile clients obtain location information from their environment which is used to provide “locally optimal” services. In contrast, it may be of interest to obtain information about the current context a mobile user or device is in, from a client somewhere on the Web, i.e. to use the mobile device as an information provider for Internet clients. As an instance of such services we propose the metaphor of a “location-aware” Web homepage of mobile users providing information about, e.g. the current location a mobile user is at. Requesting this homepage can be as easy as typing a URL containing the mobile user's phone number such ashttp://mhp.net/+49123456789 in an off-the-shelf browser. The homepage is dynamically constructed as Web users access it and it can be configured in various ways that are controlled by the mobile user. We present the architecture and implementation and discuss issues around this example of “inverse” ubiquitous computing.     

Social-aware hybrid mobile offloading

Mobile offloading is a promising technique to aid the constrained resources of a mobile device. By offloading a computational task, a device can save energy and increase the performance of the mobile applications. Unfortunately, in existing offloading systems, the opportunistic moments to offload a task are often sporadic and short-lived. We overcome this problem by proposing a social-aware hybrid offloading system (HyMobi), which increases the spectrum of offloading opportunities. As a mobile device is always co-located to at least one source of network infrastructure throughout of the day, by merging cloudlet, device-to-device and remote cloud offloading, we increase the availability of offloading support. Integrating these systems is not trivial. In order to keep such coupling, a strong social catalyst is required to foster user’s participation and collaboration. Thus, we equip our system with an incentive mechanism based on credit and reputation, which exploits users’ social aspects to create offload communities. We evaluate our system under controlled and in-the-wild scenarios. With credit, it is possible for a device to create opportunistic moments based on user’s present need. As a result, we extended the widely used opportunistic model with a long-term perspective that significantly improves the offloading process and encourages unsupervised offloading adoption in the wild.     

Situated Computing: A Paradigm for the Mobile User-Interaction with Multimedia Sources

Today, users interact with computers in an explicit manner and the system's response is independent from their situations. Hence, it is difficult to integrate computers with working life as embedded tools, which can facilitate users to accomplish real world objectives easily. Situated computing is a new paradigm for mobile computer users based on their physical context and activities carried out as a part of their working business. It provides the mechanism to have a mobile computer as a utility to satisfy the user's real world requirements as well as an infrastructure for the situated interaction using applications. In this paper, we are presenting a metaphor called situation metaphor to model interaction between the user and mobile computers in order to achieve expectations of situated computing. A three-layered schema is followed in developing situation metaphor. We discuss extensively the theoretical foundation and framework for the situation metaphor, and followed by applications developed based on the framework.