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.
12656146
Session-affinity aware request allocation for Web clusters
Persistent connections are increasingly being used in Web retrieval due to wide adoption of HTTP/1.1 standards. With persistent connections, the request allocation algorithm used by Web clusters is often session-grained. This article studies the caching performance of Web clusters under session-grained request allocation. It is shown that although content-based algorithms considerably improve caching performance over content-blind algorithms at the request-grained level, most performance gain is offset by the allocation dependency that arises when the requests are allocated at the session-grained level. The performance loss increases with cluster size and connection holding time. An optimization problem is then formulated for improving the caching effectiveness of session-grained allocation. The problem is proven to be NP-complete. Based on a heuristic approach, a session-affinity aware algorithm is presented that makes use of the correlation between the requests in a session. The new algorithm is shown to significantly outperform the content-based algorithm under session-grained allocation. It is also shown that optimizing session-grained allocation cannot fully compensate for the performance loss caused by allocation dependency.
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.
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.
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.
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
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
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.
1083190
Streaming media caching algorithms for transcoding proxies
Streaming media is expected to become one of the most popular types of Web content in the future. Due to increasing variety of client devices and the range of access speeds to the Internet, multimedia contents may be required to be transcoded to match the client's capability. With transcoding, both the network and the proxy CPU are potential bottlenecks for streaming media delivery. This paper discusses and compares various caching algorithms designed for transcoding proxies. In particular we propose a new adaptive algorithm that dynamically selects an appropriate metric for adjusting the management policy. Experimental results show that the proposed algorithm significantly outperforms those that cache only untranscoded or only transcoded objects. Moreover motivated by the characteristics of many video compression algorithms, we investigate partitioning a video object into sections based on frame type and handling them individually for proxy caching. It is found that partitioning improves performance when CPU power rather than network bandwidth is the limiting resource, particularly when the reference pattern is not highly skewed.
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.
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/).