Jason Flinn

Agile application-aware adaptation for mobility

In this paper we show that application-aware adaptation, a collaborative partnership between the operating system and applications, offers the most general and effective approach to mobile information access. We describe the design of Odyssey, a prototype implementing this approach, and show how it supports concurrent execution of diverse mobile applications. We identify agility as a key attribute of adaptive systems, and describe how to quantify and measure it. We present the results of our evaluation of Odyssey, indicating performance improvements up to a factor of 5 on a benchmark of three applications concurrently using remote services over a network with highly variable bandwidth.

Energy-aware adaptation for mobile applications

In this paper, we demonstrate that a collaborative relationship between the operating system and applications can be used to meet user-specified goals for battery duration. We first show how applications can dynamically modify their behavior to conserve energy. We then show how the Linux operating system can guide such adaptation to yield a battery-life of desired duration. By monitoring energy supply and demand, it is able to select the correct tradeoff between energy conservation and application quality. Our evaluation shows that this approach can meet goals that extend battery life by as much as 30%.

PowerScope: a tool for profiling the energy usage of mobile applications

We describe the design and implementation of PowerScope, a tool for profiling energy usage by applications. PowerScope maps energy consumption to program structure, in much the same way that CPU profilers map processor cycles to specific processes and procedures. Our approach combines hardware instrumentation to measure current level with kernel software support to perform statistical sampling of system activity. Postprocessing software maps the sample data to program structure and produces a profile of energy usage by process and procedure. Using PowerScope, we have been able to reduce the energy consumption of an adaptive video playing application by 46%.

Self-tuning wireless network power management

Current wireless network power management often substantially degrades performance and may even increase overall energy usage when used with latency-sensitive applications. We propose self-tuning power management (STPM) that adapts its behavior to the access patterns and intent of applications, the characteristics of the network interface, and the energy usage of the platform. We have implemented STPM as a Linux kernel module---our results show substantial benefits for distributed file systems, streaming audio, and thin-client applications. Compared to default 802.11b power management, STPM reduces the total energy usage of an iPAQ running the Coda distributed file system by 21% while also reducing interactive file system delay by 80%. Further, STPM adapts to diverse operating conditions: it yields good results on both laptops and handhelds, supports 802.11b network interfaces with substantially different characteristics, and performs well across a range of application network access patterns.

The case for cyber foraging

In this paper, we propose cyber foraging: a mechanism to augment the computational and storage capabilities of mobile devices. Cyber foraging uses opportunistically discovered servers in the environment to improve the performance of interactive applications and distributed file systems on mobile clients. We show how the performance of distributed file systems can be improved by staging data at these servers even though the servers are not trusted. We also show how the performance of interactive applications can be improved via remote execution. Finally, we present VERSUDS: a virtual interface to heteregeneous service discovery protocols that can be used to discover these servers.

Balancing performance, energy, and quality in pervasive computing

We describe Spectra, a remote execution system for battery-powered clients used in pervasive computing. Spectra enables applications to combine the mobility of small devices with the greater processing power of static compute servers. Spectra is self-tuning: it monitors both application resource usage and the availability of resources in the environment, and dynamically determines how and where to execute application components. In making this determination, Spectra balances the competing goals of performance, energy conservation, and application quality. We have validated Spectras approach on the Compaq Itsy v2.2 and IBM ThinkPad 560X using a speech recognizer a document preparation system, and a natural language translator. Our results confirm that Spectra almost always selects the best execution plan, and that its few suboptimal choices are very close to optimal.

Virtualized in-cloud security services for mobile devices

Modern mobile devices continue to approach the capabilities and extensibility of standard desktop PCs. Unfortunately, these devices are also beginning to face many of the same security threats as desktops. Currently, mobile security solutions mirror the traditional desktop model in which they run detection services on the device. This approach is complex and resource intensive in both computation and power. This paper proposes a new model whereby mobile antivirus functionality is moved to an off-device network service employing multiple virtualized malware detection engines. Our argument is that it is possible to spend bandwidth resources to significantly reduce on-device CPU, memory, and power resources. We demonstrate how our in-cloud model enhances mobile security and reduces on-device software complexity, while allowing for new services such as platform-specific behavioral analysis engines. Our benchmarks on Nokias N800 and N95 mobile devices show that our mobile agent consumes an order of magnitude less CPU and memory while also consuming less power in common scenarios compared to existing on-device antivirus software.

Managing battery lifetime with energy-aware adaptation

We demonstrate that a collaborative relationship between the operating system and applications can be used to meet user-specified goals for battery duration. We first describe a novel profiling-based approach for accurately measuring application and system energy consumption. We then show how applications can dynamically modify their behavior to conserve energy. We extend the Linux operating system to yield battery lifetimes of user-specified duration. By monitoring energy supply and demand and by maintaining a history of application energy use, the approach can dynamically balance energy conservation and application quality. Our evaluation shows that this approach can meet goals that extend battery life by as much as 30%.

Self-tuned remote execution for pervasive computing

Pervasive computing creates environments saturated with computing and communication capability, yet gracefully integrated with human users. Remote execution has a natural role to play, in such environments, since it lets applications simultaneously leverage the mobility of small devices and the greater resources of large devices. In this paper, we describe Spectra, a remote execution system designed for pervasive environments. Spectra monitors resources such as battery, energy and file cache state which are especially important for mobile clients. It also dynamically balances energy use and quality goals with traditional performance concerns to decide where to locate functionality. Finally, Spectra is self-tuning-it does not require applications to explicitly specify intended resource usage. Instead, it monitors application behavior, learns functions predicting their resource usage, and uses the information to anticipate future behavior.

Quantifying the energy consumption of a pocket computer and a Java virtual machine

In this paper, we examine the energy consumption of a state-of-the-art pocket computer. Using a data acquisition system, we measure the energy consumption of the Itsy Pocket Computer, developed by Compaq Computer Corporations Palo Alto Research Labs. We begin by showing that the energy usage characteristics of the Itsy differ markedly from that of a notebook computer. Then, since we expect that flexible software environments will become increasingly prevalent on pocket computers, we consider applications running in a Java environment. In particular, we explain some of the Java design tradeoffs applicable to pocket computers, and quantify their energy costs. For the design options we considered and the three workloads we studied, we find a maximum change in energy use of 25%.