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.
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
14711565
The minimal cost distribution tree problem for recursive expiration-based consistency management
The expiration-based scheme is widely used to manage the consistency of cached and replicated contents such as Web objects. In this approach, each replica is associated with an expiration time beyond which the replica has to be validated. While the expiration-based scheme has been investigated in the context of a single replica, not much work has been done on its behaviors with respect to multiple replicas. To allow for efficient consistency management, it is desirable to organize the replicas into a distribution tree where a lower level replica seeks validation with a higher level replica when its lifetime expires. This paper investigates the construction of a distribution tree for a given set of replicas with the objective of minimizing the total communication cost of consistency management. This is formulated as an optimization problem and is proven to be NP-complete. The optimal distribution tree is identified in some special cases and several heuristic algorithms are proposed for the general problem. The performance of the heuristic algorithms is experimentally evaluated against two classical graph-theoretic algorithms of tree construction: the shortest-paths tree and the minimum spanning tree.
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.
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.
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.
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.