Mobile computing continuously evolve through the sustained effort of many researchers. It seamlessly augments users' cognitive abilities via compute-intensive capabilities such as speech recognition, natural language processing, etc. By thus empowering mobile users, we could transform many areas of human activity. This article discusses the technical obstacles to these transformations and proposes a new architecture for overcoming them. In this architecture, a mobile user exploits virtual machine (VM) technology to rapidly instantiate customized service software on a nearby cloudlet and then uses that service over a wireless LAN; the mobile device typically functions as a thin client with respect to the service. A cloudlet is a trusted, resource-rich computer or cluster of computers that's well-connected to the Internet and available for use by nearby mobile devices. Our strategy of leveraging transiently customized proximate infrastructure as a mobile device moves with its user through the physical world is called cloudlet-based, resource-rich, mobile computing. Crisp interactive response, which is essential for seamless augmentation of human cognition, is easily achieved in this architecture because of the cloudlet's physical proximity and one-hop network latency. Using a cloudlet also simplifies the challenge of meeting the peak bandwidth demand of multiple users interactively generating and receiving media such as high-definition video and high-resolution images. Rapid customization of infrastructure for diverse applications emerges as a critical requirement, and our results from a proof-of-concept prototype suggest that VM technology can indeed help meet this requirement.

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The Case for VM-Based Cloudlets in Mobile Computing

Cloud computing has recently emerged as a new paradigm for hosting and delivering services over the Internet. Cloud computing is attractive to business owners as it eliminates the requirement for users to plan ahead for provisioning, and allows enterprises to start from the small and increase resources only when there is a rise in service demand. However, despite the fact that cloud computing offers huge opportunities to the IT industry, the development of cloud computing technology is currently at its infancy, with many issues still to be addressed. In this paper, we present a survey of cloud computing, highlighting its key concepts, architectural principles, state-of-the-art implementation as well as research challenges. The aim of this paper is to provide a better understanding of the design challenges of cloud computing and identify important research directions in this increasingly important area.

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Cloud computing: state-of-the-art and research challenges

Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hard-ware and software, and facilitates fault management, load balancing, and low-level system maintenance.By carrying out the majority of migration while OSes continue to run, we achieve impressive performance with minimal service downtimes; we demonstrate the migration of entire OS instances on a commodity cluster, recording service downtimes as low as 60ms. We show that that our performance is sufficient to make live migration a practical tool even for servers running interactive loads.In this paper we consider the design options for migrating OSes running services with liveness constraints, focusing on data center and cluster environments. We introduce and analyze the concept of writable working set, and present the design, implementation and evaluation of high-performance OS migration built on top of the Xen VMM.

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Live migration of virtual machines

This paper presents MAUI, a system that enables fine-grained energy-aware offload of mobile code to the infrastructure. Previous approaches to these problems either relied heavily on programmer support to partition an application, or they were coarse-grained requiring full process (or full VM) migration. MAUI uses the benefits of a managed code environment to offer the best of both worlds: it supports fine-grained code offload to maximize energy savings with minimal burden on the programmer. MAUI decides at run-time which methods should be remotely executed, driven by an optimization engine that achieves the best energy savings possible under the mobile device's current connectivity constrains. In our evaluation, we show that MAUI enables: 1) a resource-intensive face recognition application that consumes an order of magnitude less energy, 2) a latency-sensitive arcade game application that doubles its refresh rate, and 3) a voice-based language translation application that bypasses the limitations of the smartphone environment by executing unsupported components remotely.

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MAUI: making smartphones last longer with code offload

A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Intuitive computing methods and systems

We have created Zap, a novel system for transparent migration of legacy and networked applications. Zap provides a thin virtualization layer on top of the operating system that introduces pods, which are groups of processes that are provided a consistent, virtualized view of the system. This decouples processes in pods from dependencies to the host operating system and other processes on the system. By integrating Zap virtualization with a checkpoint-restart mechanism, Zap can migrate a pod of processes as a unit among machines running independent operating systems without leaving behind any residual state after migration. We have implemented a Zap prototype in Linux that supports transparent migration of unmodified applications without any kernel modifications. We demonstrate that our Linux Zap prototype can provide general-purpose process migration functionality with low overhead. Our experimental results for migrating pods used for running a standard user's X windows desktop computing environment and for running an Apache web server show that these kinds of pods can be migrated with subsecond checkpoint and restart latencies.

The design and implementation of Zap: a system for migrating computing environments

This paper presents VMFlockMS, a migration service optimized for cross-datacenter transfer and instantiation of groups of virtual machine (VM) images that comprise an application-level solution (e.g., a three-tier web application). We dub these groups of related VM images VMFlocks. VMFlockMS employs two main techniques: first, data deduplication within the VMFlock to be migrated and between the VMFlock and the data already present at the destination datacenter, and, second, accelerated instantiation of the application at the target datacenter after transferring only a partial set of data blocks and prioritization of the remaining data based on previously observed access patterns originating from the running VMs. VMFlockMS is designed to be deployed as a set of virtual appliances which make efficient use of the available cloud resources to locally access and deduplicate the images and data in a distributed fashion with minimal requirements imposed on the cloud API to access the VM image repository. VMFlockMS provides an incrementally scalable and high-performance migration service. Our evaluation shows that VMFlockMS can reduce the data volumes to be transferred over the network to as low as 3% of the original VMFlock size, enables the complete transfer of the VM images belonging to a VMFlock over transcontinental link up to 3.5x faster than alternative approaches, and enables booting these VM images with as little as 5% of the compressed VMFlock data available at the destination.

VMFlock: virtual machine co-migration for the cloud

In a typical cloud computing environment, the users are provided with storage and compute capacity in the form of virtual machines. The underlying infrastructure for these services typically comprises large distributed clusters of commodity machines and direct-attached storage in concert with a server virtualization layer. The focus of this paper is on an enterprise storage framework that supports the timely and resource-efficient deployment of virtual machines in such a cloud environment. The proposed framework makes use of innovations in the General Parallel File System-Shared Nothing Clusters (GPFS®-SNC) file system, supports optimal allocation of resources to virtual machines in a hypervisor-agnostic fashion, achieves low latency when provisioning for new virtual machines, and adapts to the input-output needs of each virtual-machine instance in order to achieve high performance for all types of applications.

GPFS-SNC: an enterprise storage framework for virtual-machine clouds

Embodiments of the invention relate to a shared group of resource and efficient processing of one or more jobs in the share group of resources. Tools are provided in the shared group of resource to assess and organize a topology of the shared resources, including physical and virtual machines, as well as storage devices. The topology is stored in a known location and utilized for efficient assignment of one or more jobs responsive to the hierarchy.

Efficient execution of jobs in a shared pool of resources

Embodiments of the invention relate to co-migration in a shared pool of resources with similarity across data sets of a migrating application. The data sets are processed and profiled. Metadata is reviewed to remove duplicate elements and to distribute the processing load across available nodes. At the same time, a ranking may be assigned to select metadata to support a prioritized migration. Non-duplicate data chunks are migrated across the shared pool of resources responsive to the assigned prioritization.

Dinesh Kumar Subhraveti

Papers

The design and implementation of Zap: a system for migrating computing environments

VMFlock: virtual machine co-migration for the cloud

GPFS-SNC: an enterprise storage framework for virtual-machine clouds

Efficient execution of jobs in a shared pool of resources

Virtual machine image co-migration