20193865
Adaptive hash routing for a cluster of client-side web proxies
Hash routing reduces cache misses for a cluster of web proxies by eliminating the duplication of cache contents. In this paper, we investigate the optimization of hash routing performance by dynamically adapting object and DNS allocations to the traffic pattern. An analytical model is developed for hash routing that takes into consideration the original request distribution, the object allocation strategy, the speeds of the proxies and the cache hit ratios. Based on this model, the optimal hash routing problem is studied. The analytical results are applied to the design of two adaptive hash routing schemes: ADA-OBJ optimizes object allocation under static client configuration, and ADA-OBJ/DNS optimizes both object and DNS allocations under dynamic client configuration. Trace-driven simulation experiments have been conducted to evaluate the performance of the proposed schemes. The results show that they significantly outperform the intuitive static hash routing scheme based only on the speeds of the proxies.
13652007
Processing Precision-Constrained Approximate Queries in Wireless Sensor Networks
A lot of research efforts have been devoted to improving energy efficiency for wireless sensor networks by exploring distributed data storage and in-network query processing techniques. In this paper, we present a generic two-tier data storage strategy for answering precision-constrained approximate queries in a sensor network. The basic idea is to keep two versions of data in the network. A highprecision version is kept at the sensor node that captures the data while a low-precision version is maintained at the base station. We develop query processing and node refreshment strategies for various types of approximate queries under the two-tier storage. Our extensive experiments show that the two-tier storage strategy outperforms the basic centralized storage scheme by an order of magnitude in terms of network lifetime under various system configur
11687631
Optimal Replica Placement under TTL-Based Consistency
Geographically replicating popular objects in the Internet speeds up content distribution at the cost of keeping the replicas consistent and up-to-date. The overall effectiveness of replication can be measured by the total communication cost consisting of client accesses and consistency management, both of which depend on the locations of the replicas. This paper investigates the problem of placing replicas under the widely used TTL-based consistency scheme. A polynomial-time algorithm is proposed to compute the optimal placement of a given number of replicas in a network. The new replica placement scheme is compared, using real Internet topologies and Web traces, against two existing approaches which do not consider consistency management or assume invalidation-based consistency scheme. The factors affecting their performance are identified and discussed
8946964
Extending Network Lifetime for Precision-Constrained Data Aggregation in Wireless Sensor Networks
This paper exploits the tradeoff between data quality and energy consumption to extend the lifetime of wireless sensor networks. We consider the applications that require some aggregate form of sensed data with precision guarantees. Our key idea is to differentiate the precisions of data collected from different sensor nodes to balance their energy consumption. This is achieved by partitioning the precision constraint of data aggregation and allocating error bounds to individual sensor nodes in a coordinated fashion. Three factors affecting the lifetime of sensor nodes are identified: (1) the changing pattern of sensor readings; (2) the residual energy of sensor nodes; and (3) the communication cost between the sensor nodes and the base station. We analyze the optimal precision allocation in terms of network lifetime and propose an adaptive precision allocation scheme that dynamically adjusts the error bounds of sensor nodes. Experimental results using real data traces show that the proposed scheme significantly improves network lifetime compared to existing methods.
16560540
Optimizing static job scheduling in a network of heterogeneous computers
This paper investigates static job scheduling schemes that distribute workload in a network of computers with different speeds. Static schemes involve very low overhead and complexity compared to dynamic schemes, but can still provide significant performance improvement over the case of no load balancing. Optimization techniques are proposed for workload allocation and job dispatching. Workload allocation is modeled as a non-linear optimization problem and solved mathematically. It is shown that allocating a disproportionately high percentage of jobs to the more powerful computers improves system performance. The proposed job dispatching algorithm is an extension of the traditional round-robin scheme. The objective is to reduce burstiness in the job arrival stream to each computer The schemes are evaluated by simulation experiments. Performance results verify their effectiveness in terms of mean response time, mean response ratio, and fairness. The Optimized Round-Robin (ORR) strategy which combines both techniques outperforms other static scheduling algorithms examined.
206832670
Multidomain load balancing
This paper investigates dynamic load balancing issues in the multidomain environment where local area networks (LANs) are interconnected by the Internet. Because of the much slower Internet communication speed and limited bandwidth, existing load balancing algorithms for LANs are unsuitable for the multidomain environment. New issues such as lag time in updating load information and network cost of transferring jobs must be addressed. To tackle these problems, the conventional least load scheduler is extended to the multidomain environment by employing a hierarchical structure, and several quick update techniques are proposed. Also, a heuristic taking both the machine load and the network cost into consideration is developed to evaluate the benefits of sending jobs to computers in different domains. A set of experiments conducted on the BALANCE testbed showed that the proposed techniques provide significant performance improvement over existing algorithms.
3257079
Face sketch recognition
Automatic retrieval of face images from police mug-shot databases is critically important for law enforcement agencies. It can effectively help investigators to locate or narrow down potential suspects. However, in many cases, a photo image of a suspect is not available and the best substitute is often a sketch drawing based on the recollection of an eyewitness. We present a novel photo retrieval system using face sketches. By transforming a photo image into a sketch, we reduce the difference between photo and sketch significantly, thus allowing effective matching between the two. Experiments over a data set containing 188 people clearly demonstrate the efficacy of the algorithm.
6097645
Simulating Protein Motions with Rigidity Analysis
Protein motions, ranging from molecular flexibility to large-scale conformational change, play an essential role in many biochemical processes. Despite the explosion in our knowledge of structural and functional data, our understanding of protein movement is still very limited. In previous work, we developed and validated a motion planning based method for mapping protein folding pathways from unstructured conformations to the native state. In this paper, we propose a novel method based on rigidity theory to sample conformation space more effectively, and we describe extensions of our framework to automate the process and to map transitions between specified conformations. Our results show that these additions both improve the accuracy of our maps and enable us to study a broader range of motions for larger proteins. For example, we show that rigidity-based sampling results in maps that capture subtle folding differences between protein G and its mutants, NuG1 and NuG2, and we illustrate how our technique can be used to study large-scale conformational changes in calmodulin, a 148 residue signaling protein known to undergo conformational changes when binding to Ca(2+). Finally, we announce our web-based protein folding server which includes a publicly available archive of protein motions: (http://parasol.tamu.edu/foldingserver/).
8798483
Planning with Reachable Distances: Fast Enforcement of Closure Constraints
Motion planning for closed-chain systems is particularly difficult due to additional closure constraints placed on the system. In fact, the probability of randomly selecting a set of joint angles that satisfy the closure constraints is zero. We propose planning with reachable distance (PRD) to overcome this challenge by first precomputing the subspace satisfying the closure constraints, then directly sampling in it. To do so, we represent the chain as a hierarchy of sub-chains. Then we calculate the "closure" sub-space as appropriate reachable distance ranges of sub-chains satisfying the closure constraints. This provides two distinct advantages over traditional approaches: (1) configurations are quickly sampled and converted to joint angles using basic trigonometry functions instead of more expensive inverse kinematics solvers, and (2) configurations are guaranteed to be closed. In this paper, we describe this hierarchical chain representation and give a sampling algorithm with complexity linear in the number of links. We provide the necessary motion planning primitives for most sampling-based motion planners. Our experimental results show our method is fast, making sampling closed configurations comparable to sampling open chain configurations that ignore closure constraints. Our method is general, easy to implement, and also extends to other distance-related constraints besides the ones demonstrated here
9601629
Tools for Simulating and Analyzing RNA Folding Kinetics
It has recently been found that some RNA functions are determined by the actual folding kinetics and not just the RNA's nucleotide sequence or its native structure. We present new computational tools for simulating and analyzing RNA folding kinetic metrics such as population kinetics, folding rates, and the folding of particular subsequences. Our method first builds an approximate representation (called a map) of the RNA's folding energy landscape, and then uses specialized analysis techniques to extract folding kinetics from the map. We provide a new sampling strategy called Probabilistic Boltzmann Sampling (PBS) that enables us to approximate the folding landscape with much smaller maps, typically by several orders of magnitude. We also describe a new analysis technique, Map-based Monte Carlo (MMC) simulation, to stochastically extract folding pathways from the map. We demonstrate that our technique can be applied to large RNA (e.g., 200+ nucleotides), where representing the full landscape is infeasible, and that our tools provide results comparable to other simulation methods that work on complete energy landscapes. We present results showing that our approach computes the same relative functional rates as seen in experiments for the relative plasmid replication rates of ColE1 RNAII and its mutants, and for the relative gene expression rates of MS2 phage RNA and its mutants.
7128107
Biasing Samplers to Improve Motion Planning Performance
With the success of randomized sampling-based motion planners such as probabilistic roadmap methods, much work has been done to design new sampling techniques and distributions. To date, there is no sampling technique that outperforms all other techniques for all motion planning problems. Instead, each proposed technique has different strengths and weaknesses. However, little work has been done to combine these techniques to create new distributions. In this paper, we propose to bias one sampling distribution with another such that the resulting distribution out-performs either of its parent distributions. We present a general framework for biasing samplers that is easily extendable to new distributions and can handle an arbitrary number of parent distributions by chaining them together. Our experimental results show that by combining distributions, we can out-perform existing planners. Our results also indicate that not one single distribution combination performs the best in all problems, and we identify which perform better for the specific application domains studied