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.
17927523
An energy-efficient and access latency optimized indexing scheme for wireless data broadcast
Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by means of hash-based indexing and enables nonflat data broadcast to reduce access latency. The design of hash function and the optimization of bandwidth allocation are investigated in depth to refine MHash. Experimental results show that, under skewed access distribution, MHash outperforms state-of-the-art air indexing schemes and achieves access latency close to optimal broadcast scheduling
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.
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.
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.
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.