1236122
Range-free localization and its impact on large scale sensor networks
With the proliferation of location dependent applications in sensor networks, location awareness becomes an essential capability of sensor nodes. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work, via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we provide insight into the impact of localization accuracy on various location dependent applications and suggestions on improving their performance in the presence of such inaccuracy.
16039010
Design, Implementation and Evaluation of a Real-Time Active Content Distribution Service
The phenomenal growth of the world-wide web has made it the most popular Internet application today. Web caching and content distribution services have been recognized as valuable techniques to mitigate the explosion of web traffic. An increasing fraction of web traffic today is dynamically generated and therefore intrinsically difficult to replicate or cache using present static approaches. Scalable delivery of such active content poses a myriad of challenges, including content replication, update propagation, and consistency management. This paper makes two contributions: it (1) describes a scalable architecture for transparent demand-driven distribution of active content; and (2) presents a system that can provide real-time delay guarantees on content access. Our approach involves migrating the scripts which generate dynamic web traffic, and their data, from the origin servers to active content distribution proxies nearest to the clients. We also present mechanisms on these proxies to enforce real-time delay guarantees for client requests. Our system is implemented and deployed on Planetlab (2004), a real-world distributed Internet testbed. Experimental data show that significant improvements are observed in effective throughput and client response time, and that delay bounds on content access can be guaranteed with a very high probability.
2224019
Using an Immune System Model to Explore Mate Selection in Genetic Algorithms
When Genetic Algorithms (GAs) are employed in multimodal function optimization, engineering and machine learning, identifying multiple peaks and maintaining subpopulations of the search space are two central themes. In this paper, an immune system model is adopted to develop a framework for exploring the role of mate selection in GAs with respect to these two issues. The experimental results reported in the paper will shed more light into how mate selection schemes compare to traditional selection schemes. In particular, we show that dissimilar mating is beneficial in identifying multiple peaks, yet harmful in maintaining subpopulations of the search space.
6505998
Failure factor based yield enhancement for SRAM designs
With increasing chip density, semiconductor memory yield improvement is becoming a task that can only be done collaboratively by test engineers, product engineers, process engineers, and circuit designers. Design-for-manufacturability (DFM) and design-for-yield (DFY) methodologies have an increasing impact on the yield learning of modem silicon chips. However, a major part of a system chip is typically occupied by memories, which dominate the yield of the chip. During chip integration, it is important that we pick the right design of memory cores that will maximize the yield under the specific process technology chosen. Traditionally, yield prediction is only based on layout and defect statistics. In this paper, we propose to estimate the yield with a failure factor. We thus develop a memory failure factor analyzer (FFA), based on that, we can select the memory design that is more suitable for the given process technology. Experimental results show that we can efficiently evaluate the yields of different memory designs for the same specification, so that the most robust one, that results in the highest yield, can be selected.
41992209
Synthesis of Heterogeneous Distributed Architectures for Memory-Intensive Applications
29576760
A configurable AES processor for enhanced security
2158099
Keyphrase Extraction Using Semantic Networks Structure Analysis
Keyphrases play a key role in text indexing, summarization and categorization. However, most of the existing keyphrase extraction approaches require human-labeled training sets. In this paper, we propose an automatic keyphrase extraction algorithm, which can be used in both supervised and unsupervised tasks. This algorithm treats each document as a semantic network. Structural dynamics of the network are used to extract keyphrases (key nodes) unsupervised. Experiments demonstrate the proposed algorithm averagely improves 50% in effectiveness and 30% in efficiency in unsupervised tasks and performs comparatively with supervised extractors. Moreover, by applying this algorithm to supervised tasks, we develop a classifier with an overall accuracy up to 80%.