Mobile devices primarily processing multimedia data need to support multimedia quality with limited battery energy. To address this challenging problem, researchers have introduced adaptation into multiple system layers, ranging from hardware to applications. Given these adaptive layers, a new challenge is how to coordinate them to fully exploit the adaptation benefits. This paper presents a novel cross-layer adaptation framework, called GRACE-1, that coordinates the adaptation of the CPU hardware, OS scheduling, and multimedia quality based on users' preferences. To balance the benefits and overhead of cross-layer adaptation, GRACE-1 takes a hierarchical approach: It globally adapts all three layers to large system changes, such as application entry or exit, and internally adapts individual layers to small changes in the processed multimedia data. We have implemented GRACE-1 on an HIP laptop with the adaptive Athlon CPU, Linux-based OS, and video codecs. Our experimental results show that, compared to schemes that adapt only some layers or adapt only to large changes, GRACE-1 reduces the laptop's energy consumption up to 31.4 percent while providing better or the same video quality.

This article presents the design, implementation, and evaluation of EScheduler , an energy-efficient soft real-time CPU scheduler for multimedia applications running on a mobile device. EScheduler seeks to minimize the total energy consumed by the device while meeting multimedia timing requirements. To achieve this goal, EScheduler integrates dynamic voltage scaling into the traditional soft real-time CPU scheduling: It decides at what CPU speed to execute applications in addition to when to execute what applications. EScheduler makes these scheduling decisions based on the probability distribution of cycle demand of multimedia applications and obtains their demand distribution via online profiling.We have implemented EScheduler in the Linux kernel and evaluated it on a laptop with a variable-speed CPU and typical multimedia codecs. Our experimental results show four findings: first, the cycle demand distribution of our studied codecs is stable or changes slowly. This stability implies the feasibility to perform our proposed energy-efficient scheduling with low overhead. Second, EScheduler delivers soft performance guarantees to these codecs by bounding their deadline miss ratio under the application-specific performance requirements. Third, EScheduler reduces the total energy of the laptop by 14.4% to 37.2% relative to the scheduling algorithm without voltage scaling and by 2% to 10.5% relative to voltage scaling algorithms without considering the demand distribution. Finally, EScheduler saves energy by 2% to 5% by explicitly considering the discrete CPU speeds and the corresponding total power of the whole laptop, rather than assuming continuous speeds and cubic speed-power relationship.

It is difficult to write device drivers. One factor is that writing low-level code for accessing devices and manipulating their registers is tedious and error-prone. For many system-on-chip based systems, buggy hardware, imprecise documentation, and code reuse worsen the situation further. This paper presents HAIL (Hardware Access Interface Language), a language-based approach to simplify device access programming and generate error checking code against bugs in software, hardware, and documentation. HAIL is a domain-specific language that specifies all aspects of a device's programming interface and the access methods in a particular system and OS. A compiler automatically checks the specification and translates it into C code for device access, with optional debugging code. The generated code can be included directly into device driver code. In the paper, we argue that HAIL lowers development effort, incurs minimal runtime overhead, and reduces device access related bugs. We also show that the HAIL specification can be reused for different operating systems, thereby reducing porting costs.

This paper presents the design, implementation, and evaluation of a practical voltage scaling (PDVS) algorithm for mobile devices primarily running multimedia applications. PDVS seeks to minimize the total energy of the whole device while meeting multimedia timing requirements. To do this, PDVS extends traditional real-time scheduling by deciding what execution speed in addition to when to execute what applications. PDVS makes these decisions based on the discrete speed levels of the CPU, the total power of the device at different speeds, and the probability distribution of CPU demand of multimedia applications. We have implemented PDVS in the Linux kernel and evaluated it on an HP laptop. Our experimental results show that PDVS saves energy substantially without affecting multimedia performance. It saves energy by 14.4% to 37.2% compared to scheduling algorithms without voltage scaling and by up to 10.4% compared to previous voltage scaling algorithms that assume an ideal CPU with continuous speeds and cubic power-speed relationship.

In traditional computer systems, security is typically provided in a one-or-nothing manner; the system is either secure or insecure. Such an approach is insufficient for pervasive environments that contain heterogenous devices with varying computing resources. The small, portable handheld devices are often left unsecured due to their limited computing power. The approach is also inadequate for multimedia applications that require security as a controllable service attribute to maintain performance quality of service to levels that are acceptable to the users. Hence, we need a tunable and differentiable security framework. In this paper, we present a quality of protection (QoP) framework that resolves the inadequacies of the one-or-nothing approach by providing differential security levels for different device, user and application security requirements and preferences. We show that our QoP framework is necessary for multimedia applications to achieve the best possible security and performance levels in pervasive environments.

Networked video sensors need to execute two dependent periodic tasks: video encoding and transmission. The dependency and periodicity often result in small idle intervals of CPU and wireless network interface card (WNIC). In this paper, we present a sender-buffering approach to exploit such idle intervals for energy saving. Specifically, a video sensor encodes frames in a timely fashion, but buffers encoded frames and transmits them in bursts at longer intervals. In doing so, it (1) accumulates short WNIC idle intervals into longer ones, during which the WNIC can enter the lower-power sleep mode, and (2) slows down the CPU by avoiding CPU idle intervals, which are resulted from both early completion of frame encoding and waiting for frame transmission. Our experimental results show that the buffering approach can save 32-80% CPU energy and 35- 54% WNIC energy, while increasing the overall end-to-end transmission delay by at most 2 frames.

We present an advance reservation scheme for CPU and energy resources, called ReCalendar. The goal is to enable soft real-time applications on mobile devices to achieve desired performance and lifetime. ReCalendar achieves this goal via two distinctive phases, calendaring and scheduling. In the calendaring phase, a calendar is used to arrange applications and to request CPU and energy reservations for calendared applications. In the scheduling phase, the resource manager enforces admitted reservations via CPU frequency/voltage adaptation and frequency-aware soft real-time scheduling. We have implemented the ReCalendar prototype and experimentally shown that, compared with previous approaches that support only immediate reservation or CPU advance reservation, ReCalendar achieves longer battery lifetime and higher overall system utility.

This paper presents GRACE-OS, an energy-efficient soft real-time CPU scheduler for mobile devices that primarily run multimedia applications. The major goal of GRACE-OS is to support application quality of service and save energy. To achieve this goal, GRACE-OS integrates dynamic voltage scaling into soft real-time scheduling and decides how fast to execute applications in addition to when and how long to execute them. GRACE-OS makes such scheduling decisions based on the probability distribution of application cycle demands, and obtains the demand distribution via online profiling and estimation. We have implemented GRACE-OS in the Linux kernel and evaluated it on an HP laptop with a variable-speed CPU and multimedia codecs. Our experimental results show that (1) the demand distribution of the studied codecs is stable or changes smoothly. This stability implies that it is feasible to perform stochastic scheduling and voltage scaling with low overhead; (2) GRACE-OS delivers soft performance guarantees by bounding the deadline miss ratio under application-specific requirements; and (3) GRACE-OS reduces CPU idle time and spends more busy time in lower-power speeds. Our measurement indicates that compared to deterministic scheduling and voltage scaling, GRACE-OS saves energy by 7% to 72% while delivering statistical performance guarantees.

Battery-powered mobile devices are becoming increasingly important computing platforms, which require low energy consumption while meeting the resource demands of a dynamic application workload. Most proposed dynamic voltage scaling (DVS) algorithms, targeting either best-effort or hard real-time systems, however, cannot be directly applied to such open mobile systems. This paper presents a framework to integrate DVS into soft real-time (SRT) scheduling for open mobile systems, achieving energy saving of DVS while preserving resource guarantees of SRT scheduling. The integrated framework makes three major contributions. First, multimedia applications reserve resource based on their average resource usage, without the knowledge of worst-case execution time, which is difficult to estimate in an open mobile environment. Second, the SRT scheduling ensures the correctness of reservation admission and enforcement in a variable speed context. Finally, the DVS manager reduces the processor energy consumption by utilizing the unallocated resource, reclaiming the allocated but unused resource, or avoiding the unused resource. Our extensive simulation results demonstrate that our framework is able to save 4% to 32% energy while slightly affecting application performance.

It is challenging to reduce the processor power consumption while meeting the processor resource requirement of distributed multimedia applications in portable computers. This paper presents a middleware framework coordinating the processor/power resource management (PPRM) in a mobile computing environment. Our framework has four major contributions: (1) providing a power-aware resource reservation mechanism, where admission control is based on the processor utilization and power availability; (2) adjusting the speed and corresponding power consumption of the processor depending upon events and triggered by the change of the system workload or power availability; (3) updating reservation contracts of multimedia applications to maintain their resource requirements while adjusting the processor speed; (4) notifying applications about the change of resource status to enable them to adapt their behavior and complete tasks before the power drains. Our experimental results show the effectiveness of the coordinating PPRM framework to save energy and maintain the resource requirements of multimedia applications.