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 allows business customers to scale up and down their resource usage based on needs. Many of the touted gains in the cloud model come from resource multiplexing through virtualization technology. In this paper, we present a system that uses virtualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of "skewness&#x201D; to measure the unevenness in the multidimensional resource utilization of a server. By minimizing skewness, we can combine different types of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.

Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment

Smart phones are now capable of supporting a wide range of applications, many of which demand an ever increasing computational power. This poses a challenge because smart phones are resource-constrained devices with limited computation power, memory, storage, and energy. Fortunately, the cloud computing technology offers virtually unlimited dynamic resources for computation, storage, and service provision. Therefore, researchers envision extending cloud computing services to mobile devices to overcome the smartphones constraints. The challenge in doing so is that the traditional smartphone application models do not support the development of applications that can incorporate cloud computing features and requires specialized mobile cloud application models. This article presents mobile cloud architecture, offloading decision affecting entities, application models classification, the latest mobile cloud application models, their critical analysis and future research directions.

A Survey of Mobile Cloud Computing Application Models

The unabated flurry of research activities to augment various mobile devices by leveraging heterogeneous cloud resources has created a new research domain called Mobile Cloud Computing (MCC). In the core of such a non-uniform environment, facilitating interoperability, portability, and integration among heterogeneous platforms is nontrivial. Building such facilitators in MCC requires investigations to understand heterogeneity and its challenges over the roots. Although there are many research studies in mobile computing and cloud computing, convergence of these two areas grants further academic efforts towards flourishing MCC. In this paper, we define MCC, explain its major challenges, discuss heterogeneity in convergent computing (i.e. mobile computing and cloud computing) and networking (wired and wireless networks), and divide it into two dimensions, namely vertical and horizontal. Heterogeneity roots are analyzed and taxonomized as hardware, platform, feature, API, and network. Multidimensional heterogeneity in MCC results in application and code fragmentation problems that impede development of cross-platform mobile applications which is mathematically described. The impacts of heterogeneity in MCC are investigated, related opportunities and challenges are identified, and predominant heterogeneity handling approaches like virtualization, middleware, and service oriented architecture (SOA) are discussed. We outline open issues that help in identifying new research directions in MCC.

Heterogeneity in Mobile Cloud Computing: Taxonomy and Open Challenges

Offloading is an effective method for extending the lifetime of handheld mobile devices by executing some components of applications remotely (e.g., on the server in a data center or in a cloud). In this article, to achieve energy saving while satisfying given application execution time requirement, we present a dynamic offloading algorithm, which is based on Lyapunov optimization. The algorithm has low complexity to solve the offloading problem (i.e., to determine which software components to execute remotely given available wireless network connectivity). Performance evaluation shows that the proposed algorithm saves more energy than the existing algorithm while meeting the requirement of application execution time.

A Dynamic Offloading Algorithm for Mobile Computing

Hypervisors have been proposed as a security tool to defend against malware that subverts the OS kernel. However, hypervisors must deal with the semantic gap between the low-level information available to them and the high-level OS abstractions they need for analysis. To bridge this gap, systems have proposed making assumptions derived from the kernel source code or symbol information. Unfortunately, this information is nonbinding - rootkits are not bound to uphold these assumptions and can escape detection by breaking them.

In this paper, we introduce Patagonix, a hypervisor-based system that detects and identifies covertly executing binaries without making assumptions about the OS kernel. Instead, Patagonix depends only on the processor hardware to detect code execution and on the binary format specifications of executables to identify code and verify code modifications. With this, Patagonix can provide trustworthy information about the binaries running on a system, as well as detect when a rootkit is hiding or tampering with executing code.

We have implemented a Patagonix prototype on the Xen 3.0.3 hypervisor. Because Patagonix makes no assumptions about the OS kernel, it can identify code from application and kernel binaries on both Linux and Windows XP. Patagonix introduces less than 3% overhead on most applications.

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Hypervisor support for identifying covertly executing binaries

We have designed and implemented VMGL, a virtual machine monitor (VMM) independent, graphics processing unit (GPU) independent, and cross-platform OpenGL virtualization solution. VMGL allows applications executing within virtual machines (VMs) to leverage hardware rendering acceleration, thus solving a problem that has limited virtualization of a growing class of graphics-intensive applications. VMGL also provides applications running within VMs with suspend and resume capabilities across GPUs from different vendors. Our experimental results from a number of graphics-intensive applications show that VMGL provides excellent rendering performance, within 14% or better of that obtained with native graphics hardware acceleration. Further, VMGL's performance is two orders of magnitude better than that of software rendering, the commonly available alternative today for graphics-intensive applications running in virtualized environments. Our results confirm VMGL's portability across VMware Workstation and Xen (on VT and non-VT hardware), and across Linux (with and without paravirtualization), FreeBSD, and Solaris. Our results also show that the resource demands of VMGL align well with the emerging trend of multi-core processors.

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VMM-independent graphics acceleration

Modern cloud computing infrastructures use virtual machine monitors (VMMs) that often include a large and complex administrative domain with privileges to inspect client VM state. Attacks against or misuse of the administrative domain can compromise client security and privacy. Moreover, these VMMs provide clients inflexible control over their own VMs, as a result of which clients have to rely on the cloud provider to deploy useful services, such as VM introspection-based security tools.We introduce a new self-service cloud (SSC) computing model that addresses these two shortcomings. SSC splits administrative privileges between a system-wide domain and per-client administrative domains. Each client can manage and perform privileged system tasks on its own VMs, thereby providing flexibility. The system-wide administrative domain cannot inspect the code, data or computation of client VMs, thereby ensuring security and privacy. SSC also allows providers and clients to establish mutually trusted services that can check regulatory compliance while respecting client privacy. We have implemented SSC by modifying the Xen hypervisor. We demonstrate its utility by building user domains to perform privileged tasks such as memory introspection, storage intrusion detection, and anomaly detection.

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Self-service cloud computing

Idle desktop systems are frequently left powered, often because of applications that maintain network presence or to enable potential remote access. Unfortunately, an idle PC consumes up to 60% of its peak power. Solutions have been proposed that perform consolidation of idle desktop virtual machines. However, desktop VMs are often large requiring gigabytes of memory. Consolidating such VMs, creates bulk network transfers lasting in the order of minutes, and utilizes server memory inefficiently. When multiple VMs migrate simultaneously, each VM's experienced migration latency grows, and this limits the use of VM consolidation to environments in which only a few daily migrations are expected for each VM. This paper introduces Partial VM Migration, a technique that transparently migrates only the working set of an idle VM. Jettison, our partial VM migration prototype, can deliver 85% to 104% of the energy savings of full VM migration, while using less than 10% as much network re- sources, and providing migration latencies that are two to three orders of magnitude smaller.

Jettison: efficient idle desktop consolidation with partial VM migration

Snowbird is a middleware system based on virtual machine (VM) technology that simplifies the development and deployment of bimodal applications. Such applications alternate between phases with heavy computational-resource needs and phases rich in user interaction. Examples include digital animation, as well as scientific, medical, and engineering diagnostic and design tools. Traditionally, these applications have been manually partitioned into distributed components to take advantage of remote computational resources, while still providing low-latency user interaction. Instead, Snowbird lets developers design their applications as monolithic units within a VM, and automatically migrates the application to the optimal execution site to achieve short completion time and crisp interactive performance. Snowbird does not require that applications be written in a specific language, or use specific libraries, and it can be used with existing applications, including closed-source ones, without requiring recompilation or relinking. Snowbird achieves these goals by augmenting VM migration with an interaction-aware migration manager, support for graphics hardware acceleration, and a wide-area peer-to-peer storage system. Experiments conducted with a number of real-world applications, including commercial closed-source tools, show that applications running under Snowbird come within 4% of optimal compute time, and provide crisp interactive performance that is comparable to native local execution.

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H. Andrés Lagar-Cavilla

Papers

Hypervisor support for identifying covertly executing binaries

VMM-independent graphics acceleration

Self-service cloud computing

Jettison: efficient idle desktop consolidation with partial VM migration

Interactive resource-intensive applications made easy