A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins

Membrane proteins constitute a large portion of the human proteome and perform a variety of important functions as membrane receptors, transport proteins, enzymes, signaling proteins, and more. The computational studies of membrane proteins are usually much more complicated than those of globular proteins. Here we propose a new continuum model for Poisson-Boltzmann calculations of membrane channel proteins. Major improvements over the existing continuum slab model are as follows: 1) The location and thickness of the slab model are fine-tuned based on explicit-solvent MD simulations. 2) The highly different accessibility in the membrane and water regions are addressed with a two-step, two-probe grid labeling procedure, and 3) The water pores/channels are automatically identified. The new continuum membrane model is optimized (by adjusting the membrane probe, as well as the slab thickness and center) to best reproduce the distributions of buried water molecules in the membrane region as sampled in explicit water simulations. Our optimization also shows that the widely adopted water probe of 1.4 {\AA} for globular proteins is a very reasonable default value for membrane protein simulations. It gives an overall minimum number of inconsistencies between the continuum and explicit representations of water distributions in membrane channel proteins, at least in the water accessible pore/channel regions that we focus on. Finally, we validate the new membrane model by carrying out binding affinity calculations for a potassium channel, and we observe a good agreement with experiment results.Comment: 40 pages, 6 figures, 5 table

A self-adapting latency/power tradeoff model for replicated search engines

For many search settings, distributed/replicated search engines deploy a large number of machines to ensure efficient retrieval. This paper investigates how the power consumption of a replicated search engine can be automatically reduced when the system has low contention, without compromising its efficiency. We propose a novel self-adapting model to analyse the trade-off between latency and power consumption for distributed search engines. When query volumes are high and there is contention for the resources, the model automatically increases the necessary number of active machines in the system to maintain acceptable query response times. On the other hand, when the load of the system is low and the queries can be served easily, the model is able to reduce the number of active machines, leading to power savings. The model bases its decisions on examining the current and historical query loads of the search engine. Our proposal is formulated as a general dynamic decision problem, which can be quickly solved by dynamic programming in response to changing query loads. Thorough experiments are conducted to validate the usefulness of the proposed adaptive model using historical Web search traffic submitted to a commercial search engine. Our results show that our proposed self-adapting model can achieve an energy saving of 33% while only degrading mean query completion time by 10 ms compared to a baseline that provisions replicas based on a previous day's traffic

CPLD-PGPS scheduling algorithm in wireless OFDM systems

In this paper, we propose a new scheduler for orthogonal frequency-division multiplexing (OFDM) wireless communication systems, called Channel-Condition and Packet-Length Dependent Packet Generalized Processor Sharing (CPLD-PGPS) scheduler. CPLD scheduler considers the condition of the physical channel and the length of packets at the same time, and optimally allocates the sub-carriers in a frame. With this scheduler, the system can achieve better system BER performance, and correspondingly superior PER performance. The system throughput is improved, at the same time the required bandwidth is guaranteed, and long term fairness for all the traffic in the system is provided. In order to reduce the algorithm complexity, a simplified CPLD is proposed, which maintains the system throughput as in the original scheduler, and guarantees the system performance with properly set system parameters. The superior performance of the proposed scheduler is demonstrated by simulation results. © 2004 IEEE.published_or_final_versio

A channel-condition and packet-length dependent scheduler in wireless OFDM systems

In this paper, a new scheduler, called Channel-Condition and Packet-Length Dependent Packet Generalized Processor Sharing (CPLD-PGPS) scheduler is proposed for orthogonal frequency-division multiplexing (OFDM) wireless communication systems. Based on PGPS, CPLD scheduler considers the condition of the physical channel and the length of packets at the same time, and optimally allocates the sub-carriers in a frame. With this scheduler, improved system BER, and correspondingly superior PER performance can be achieved. The system throughput is improved, while guaranteeing the required bandwidth, and providing long term fairness for all the traffic in the system. In order to reduce the algorithm complexity, a simplified CPLD is proposed, which maintains the system throughput as the original scheduler, and guarantees the system performance with properly set system parameters. Simulation results demonstrate the superior performance of the proposed scheduler. © 2004 IEEE.published_or_final_versio

CPLD-PGPS scheduler in wireless OFDM systems

In this paper, we propose a new scheduler for orthogonal frequency-division multiplexing (OFDM) wireless communication systems, called Channel-Condition and Packet-Length Dependent Packet Generalized Processor Sharing (CPLD-PGPS) scheduler. Based on PGPS, the CPLD scheduler considers both the physical channel condition and the length of packets, and optimally allocates the sub-carriers to different users. The total transmit power is adaptively allocated to each subcarrier. With this scheduler, the system can achieve better system BER performance, and correspondingly superior PER performance. The system throughput is improved, the required bandwidth is guaranteed, and long term fairness for all traffic in the system is provided. In order to reduce the complexity, a simplified algorithm is proposed, which maintains the system throughput as in the original scheduler, and guarantees the system performance with properly set system parameters. The superior performance of the proposed schedulers is demonstrated by simulation with multimedia traffic. © 2006 IEEE.published_or_final_versio

Performance analysis of space-time codes with channel information errors

Many space-time codes (STC) have been proposed to enhance the performance of wireless communications in flat fading channels. All of them rely on the knowledge of the channel, and are hence affected by the channel estimation errors. Most previous research on STC performance evaluation assume perfect channel information. In this paper, we investigate STC robustness under imperfect channel knowledge. We first define the concept of "closeness" by comparing the BER under channel estimation errors with that of perfect channel knowledge, aiming to characterize STC performance degradation due to imperfect channel knowledge. Then the robustness of STC can be compared by their "closeness" to perfect results. In our computer simulations, we apply the same channel estimator to different STCs in Orthogonal Frequency Division Multiplexing (OFDM) communication systems. We find that for systems with two and three transmit antennas, the space time block codes (STBC) are always more robust to channel estimation errors than space time trellis codes (STTC). With the increase of receive diversity, all STCs become more robust to the channel estimation errors. For STTC, as the number of trellis states increases, the codes become less robust to the channel estimation errors. We also compare the BER performance of STC in the presence of channel estimation errors. For the two-transmit-antenna system, the performance of STBC is always better than that of the 4-state STTC, but is always worse than 16-state STTC. For systems with three transmit antennas, the BER performance of STTC is much better than that of STBC. © 2004 IEEE.published_or_final_versio

Robustness of space-time codes in the presence of channel estimation errors in OFDM systems

Many space-time codes (STC) have been proposed to enhance the performance of wireless communications in flat fading channels. All of them rely on the knowledge of the channel, and are hence affected by the channel estimation errors. In this paper, we investigate STC robustness under imperfect channel knowledge. We first define the concept of "closeness" by comparing the BER under channel estimation errors with that under perfect channel knowledge, aiming to characterize STC performance degradation due to imperfect channel knowledge. Then the robustness of STC can be compared by their "closeness" to perfect results. We find that for systems with two and three transmit antennas, the space time block codes (STBC) are always more robust to channel estimation errors than space time trellis codes (STTC). With the increase of receive diversity, all STCs become more robust to the channel estimation errors. For STTC, as the number of trellis states increases, the codes become less robust to the channel estimation errors. We also compare the BER performance of STC in the presence of channel estimation errors. For the two-transmit-antenna system, the performance of STBC is always better than that of the 4-state STTC, but is always worse than 16-state STTC. For systems with three transmit antennas, the BER performance of STTC is much better than that of STBC.published_or_final_versio

Exactness of the Original Grover Search Algorithm

It is well-known that when searching one out of four, the original Grover's search algorithm is exact; that is, it succeeds with certainty. It is natural to ask the inverse question: If we are not searching one out of four, is Grover's algorithm definitely not exact? In this article we give a complete answer to this question through some rationality results of trigonometric functions.Comment: 8 pages, 2 figure

An adaptive packet scheduling algorithm in OFDM systems with smart antennas

To maximize system throughput and guarantee the quality of service (QoS) of multimedia traffic in Orthogonal Frequency Division Multiplexing (OFDM) systems with smart antennas, a new packet scheduler is introduced to consider QoS requirements, packet location in the frame, and modulation scheme. In OFDM, several consecutive subcarriers are grouped as a frequency subband. Each subband in a frame can be reused by several users with smart antennas. In this paper, based on the Best-Fit algorithm proposed for TDMA and the physical features of OFDM, a new packet scheduler is proposed to allocate different BER-classified traffics into the frame. Adaptive modulation is also applied in the scheduler. When compared with existing schedulers, our scheduler achieves higher system capacity with much reduced complexity. The use of adaptive modulation further enhances the system capacity. Simulation results demonstrate that as the traffic load increases, the new scheduler has much better performance in system throughput, average delay, and packet loss rate. © 2005 IEEE.published_or_final_versio