11016588
Optimal hash routing for Web proxies
Hash routing is an effective approach for coordinating a collection of Web proxies. In this paper, we present a comprehensive analytical model for hash routing which takes into consideration a number of factors: the original request distribution, the object allocation strategy, the speeds of the proxies and cache hit ratios. Based on this model, the optimal hash routing problems for static and dynamic client configurations are investigated. Two schemes, OBJ-OPT (OBJect OPTimization) and OBJ/DNS-OPT (OBJect and Domain Name Server OPTimization), are proposed to reduce the response times of Web requests. OBJ-OPT optimizes object allocation under a static client configuration, and OBJ/DNS-OPT optimizes both object and DNS allocations under a dynamic client configuration. Extensive trace-driven simulations have been conducted to evaluate the proposed schemes. The results show that they significantly outperform the intuitive scheme based only on the speeds of the proxies.
29395992
Coordinated En-Route Web Caching
Web caching is an important technique for reducing Internet access latency, network traffic, and server load. This paper investigates cache management strategies for the en-route web caching environment, where caches are associated with routing nodes in the network. We propose a novel caching scheme that integrates both object placement and replacement policies and which makes caching decisions on all candidate sites in a coordinated fashion. In our scheme, cache status information along the routing path of a request is used in dynamically determining where to cache the requested object and what to replace if there is not enough space. The object placement problem is formulated as an optimization problem and the optimal locations to cache the object are obtained using a low-cost dynamic programming algorithm. Extensive simulation experiments have been performed to evaluate the proposed scheme in terms of a wide range of performance metrics. The results show that the proposed scheme significantly outperforms existing algorithms which consider either object placement or replacement at individual caches only.
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.
12151519
QoS-aware replica placement for content distribution
The rapid growth of new information services and business-oriented applications entails the consideration of quality of service (QoS) in content distribution. This paper investigates the QoS-aware replica placement problems for responsiveness QoS requirements. We consider two classes of service models: replica-aware services and replica-blind services. In replica-aware services, the servers are aware of the locations of replicas and can therefore optimize request routing to improve responsiveness. We show that the QoS-aware placement problem for replica-aware services is NP-complete. Several heuristic algorithms for fast computation of good solutions are proposed and experimentally evaluated. In replica-blind services, the servers are not aware of the locations of replicas or even their existence. As a result, each replica only serves the requests flowing through it under some given routing strategy. We show that there exist polynomial optimal solutions to the QoS-aware placement problem for replica-blind services. Efficient algorithms are proposed to compute the optimal locations of replicas under different cost models.
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.
789322
Cache Coherency in Location-Dependent Information Services for Mobile Environment
Caching frequently accessed data at the client is an attractive technique for improving access time. In a mobile computing environment, client location becomes a piece of changing information. As such, location-dependent data may become obsolete due to data updates or client movements. Most of the previous work investigated cache invalidation issues related to data updates only, whereas few considered data inconsistency caused by client movements. This paper separates location-dependent data invalidation from traditional cache invalidation. For location-dependent invalidation, several approaches are proposed and their performance is studied by a set of simulation experiments. The results show that the proposed methods substantially outperform the NSI scheme which drops the cache contents entirely when hand-off.
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
2027823
Evolutionary Search for Faces from Line Drawings
Single 2D line drawing is a straightforward method to illustrate 3D objects. The faces of an object depicted by a line drawing give very useful information for the reconstruction of its 3D geometry. Two recently proposed methods for face identification from line drawings are based on two steps: finding a set of circuits that may be faces and searching for real faces from the set according to some criteria. The two steps, however, involve two combinatorial problems. The number of the circuits generated in the first step grows exponentially with the number of edges of a line drawing. These circuits are then used as the input to the second combinatorial search step. When dealing with objects having more faces, the combinatorial explosion prevents these methods from finding solutions within feasible time. This paper proposes a new method to tackle the face identification problem by a variable-length genetic algorithm with a novel heuristic and geometric constraints incorporated for local search. The hybrid GA solves the two combinatorial problems simultaneously. Experimental results show that our algorithm can find the faces of a line drawing having more than 30 faces much more efficiently. In addition, simulated annealing for solving the face identification problem is also implemented for comparison.
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.
47107463
Using Motion Planning to Study RNA Folding Kinetics