Energy-Aware MPEG-4 FGS Streaming
In this paper, we propose an energy-aware MPEG-4 FGS video streaming system with client feedback. In this client-server system, the battery-powered mobile client sends its maximum decoding capability (i.e., its decoding aptitude) to the server in order to help the server determine the additional amount of data (in the form of enhancement layers on top of the base layer) per frame that it sends to the client, and thereby, set its data rate. On the client side, a dynamic voltage and frequency scaling technique is used to adjust the decoding aptitude of the client while meeting a constraint on the minimum achieved video quality. As a measure of energy efficiency of the video streamer, the notion of a normalized decoding load is introduced. It is shown that a video streaming system that maintains this normalized load at unity produces the optimum video quality with no energy waste. We implemented an MPEG-4 FGS video streaming system on an XScale-based testbed in which a server and a mobile client are wirelessly connected by a feedback channel. Based on the actual current measurements in this testbed, we obtain an average of 20% communication energy reduction in the client by making the MPEG-4 FGS streamer energy-aware.

title: Frame-Based Dynamic Voltage and Frequency Scaling for an MPEG Player
abstract: This paper describes a dynamic voltage and frequency scaling (DVFS) technique for MPEG decoding to reduce the energy consumption while maintaining a quality of service (QoS) constraint. The computational workload for an incoming frame is predicted by using a frame-based history so that the processor voltage and frequency can be scaled to provide the exact amount of computing power needed to decode the frame. More precisely, the required decoding time for each frame is separated into two parts: a frame-dependent (FD) part and a frame-independent (FI) part. The FD part varies greatly according to the type of the incoming frame whereas the FI part remains constant regardless of the frame type. Separation of the FI part from the overall decoding sequence provides two key benefits depending on the hardware platform: better compensation of the error due to workload prediction and higher level of energy saving when given a QoS degradation level. The proposed DVFS scheme has been implemented on two platforms, a low performance StrongArm-1110-based evaluation board from Intel and a high performance XScale-based testbed designed at USC. In the StrongArm-1110-based system, the FI part is used to compensate for the prediction error that may occur during the FD part, whereas in the XScale-based system, the FI part is used to reduce energy consumption by employing the lowest CPU frequency during the corresponding time intervals. Detailed current measurements in these two platforms demonstrate larger than 87 % and 80 % CPU energy saving while maintaining a user-provided frame rate, respectively. Index Terms — Dynamic voltage and frequency scaling, MPEG decoding, workload decomposition.

title: Energy-Aware Wireless Video Streaming
abstract: This paper presents a dynamic energy management policy for a wireless video streaming system, consisting of battery-powered client and server. The paper starts from the observation that the video quality in wireless streaming is a function of three factors: encoding aptitude of the server, decoding aptitude of the client, and the wireless channel. Based on this observation, the energy consumption of a wireless video streaming system is modeled and analyzed. Using the proposed model, the optimal energy assignment to each video frame is done such that the maximum system lifetime is achieved while satisfying a given minimum video quality requirement. Experimental results show that the proposed policy increases the system lifetime by 20%.

title: A game theoretic approach to low energy wireless video streaming
abstract: This paper presents a dynamic energy management policy for a wireless video streaming system, consisting of battery-powered client and server. The paper starts from the observation that the video quality in wireless streaming is a function of three factors: encoding aptitude of the server, decoding aptitude of the client, and the wireless channel. Based on this observation, the energy consumption of a wireless video streaming system is modeled and analyzed. Using the proposed model, the optimal energy assignment to each video frame is done such that the maximum system lifetime is achieved while satisfying a given minimum video quality requirement. Experimental results show that the proposed policy increases the system lifetime by 20%.

title: Energy-aware MPEG-4 FGS streaming
abstract: In this paper, we propose an energy-aware MPEG-4 FGS video streaming system with client feedback. In this client-server system, the battery-powered mobile client sends its maximum decoding capability (i.e., its decoding aptitude) to the server in order to help the server determine the additional amount of data (in the form of enhancement layers on top of the base layer) per frame that it sends to the client, and thereby, set its data rate. On the client side, a dynamic voltage and frequency scaling technique is used to adjust the decoding aptitude of the client while meeting a constraint on the minimum achieved video quality. As a measure of energy efficiency of the video streamer, the notion of a normalized decoding load is introduced. It is shown that a video streaming system that maintains this normalized load at unity produces the optimum video quality with no energy waste. We implemented an MPEG-4 FGS video streaming system on an XScale-based testbed in which a server and a mobile client are wirelessly connected by a feedback channel. Based on the actual current measurements in this testbed, we obtain an average of 20% communication energy reduction in the client by making the MPEG-4 FGS streamer energy-aware.

title: Sensitivity analysis and efficient method for identifying optimal spaced seeds
abstract: The novel introduction of spaced seed idea in the filtration stage of sequence comparison by Ma et al. (Bioinformatics 18 (2002) 440) has greatly increased the sensitivity of homology search without compromising the speed of search. Finding the optimal spaced seeds is of great importance both theoretically and in designing better search tool for sequence comparison. In this paper, we study the computational aspects of calculating the hitting probability of spaced seeds; and based on these results, we propose an efficient algorithm for identifying optimal spaced seeds.

title: Effective foreign word extraction for Korean information retrieval
abstract: In Korean text, foreign words, which are mostly transliterations of English words, are frequently used. Foreign words are usually very important index terms in Korean information retrieval since most of them are technical terms or names. So accurate foreign word extraction is crucial for high performance of information retrieval. However, accurate foreign word extraction is not easy because it inevitably accompanies word segmentation and most of the foreign words are unknown. In this paper, we present an effective foreign word recognition and extraction method. In order to accurately extract foreign words, we developed an effective method of word segmentation that involves unknown foreign words. Our word segmentation method effectively utilizes both unknown word information acquired through the automatic dictionary compilation and foreign word recognition information. Our HMM-based foreign word recognition method does not require large labeled examples for the model training unlike the previously proposed method.

title: Palindromes in SARS and Other Coronaviruses
abstract: With the identification of a novel coronavirus associated with the severe acute respiratory syndrome (SARS), computational analysis of its RNA genome sequence is expected to give useful clues to help elucidate the origin, evolution, and pathogenicity of the virus. In this paper, we study the collective counts of palindromes in the SARS genome along with all the completely sequenced coronaviruses. Based on a Markov-chain model for the genome sequence, the mean and standard deviation for the number of palindromes at or above a given length are derived. These theoretical results are complemented by extensive simulations to provide empirical estimates. Using a z score obtained from these mathematical and empirical means and standard deviations, we have observed that palindromes of length four are significantly underrepresented in all the coronaviruses in our data set. In contrast, length-six palindromes are significantly underrepresented only in the SARS coronavirus. Two other features are unique to the SARS sequence. First, there is a length-22 palindrome TCTTTAACAAGCTTGTTAAAGA spanning positions 25962-25983. Second, there are two repeating length-12 palindromes TTATAATTATAA spanning positions 22712-22723 and 22796-22807. Some further investigations into possible biological implications of these palindrome features are proposed.

title: Efficient instruction-level optimization methodology for low-power embedded systems
abstract: For low-power embedded systems, we solve the instruction scheduling and reordering problem as a Precedence Constrained Hamiltonian Path Problem for DAGs and the traveling salesman problem (TSP), both of which are NP-hard (W.J. Cook et al., 1998; V. Jain et al., 1999). We propose an efficient instruction-level optimization algorithm for solving the NP-hard problem. Minimum spanning tree (MST) and simulated annealing (SA) mechanisms are used for the optimization. We describe the methods for generating the control flow and data dependence graph (CDG), power dissipation table (PDT), and weighted strongly connected graph (SCG) for the instruction-level low-power analysis. In addition, confidence limits with error tolerance are considered for the validation of the optimization. Finally, experimental results that demonstrate the effectiveness and efficiency of the proposed algorithms are shown.

title: System level power-performance trade-offs in embedded systems using voltage and frequency scaling of off-chip buses and memory
abstract: In embedded systems, off-chip buses and memory (i.e., L2 memory as opposed to the L1 memory which is usually on-chip cache) consume significant power often more than the processor itself. In this paper for the case of an embedded system with one processor chip and one memory chip, we propose frequency and voltage scaling of the off-chip buses and the memory chip and use a known micro-architectural enhancement called a store buffer to reduce the resulting impact on execution time. Our benchmarks show a system (processor + off-chip bus + off-chip memory) power savings of 28% to 36%, an energy savings of 13% to 35%, all while increasing the execution time in the range of 1% to 29%. Previous work in power-aware computing has focused on frequency and voltage scaling of the processors or selective power-down of sub-sets of off-chip memory chips. This paper quantitatively explores voltage/frequency scaling of off-chip buses and memory as a means of trading off performance for power/energy at the system level in embedded systems.