A Compression-Based Filtering Mechanism in Content-Based Publish/Subscribe System

Bloom filters (BFs) are space-efficient randomized data structures used for fast set membership queries in many applications. The standard BF allows a small fraction of false positives for high space efficiency, but does not support deletions of items. The state-of-the-art cuckoo filter (CF) extends the standard BF to support deletions while achieving higher performance and lower space cost. However, the CF suffers a critical issue of varying space cost per item. This is because the exclusive-OR (XOR) operation used by the CF requires the total number of buckets to be a power of two, leading to the inflation of space. To address the issue, in this paper we propose a scalable variant of the CF called tagged cuckoo filter (TCF). The TCF uses a tagged fingerprint of an item, instead of an untagged fingerprint used by the CF, to compute its two candidate bucket indexes. With a tag of a fingerprint, the TCF does not require the number of buckets to be a power of two, which results in low space cost per item. Experimental results show that the TCF improves the space efficiency while sustaining high performance. Compared to the CF, the TCF reduces up to 2x space cost per item as well as achieves comparable lookup and update performance. In addition, the TCF outperforms other filters in both space cost and performance for same false positive rates.

Matching and packing problems have formed an important class of NP-hard problems. There have been a number of recently developed techniques for parameterized algorithms for these problems, including greedy localization, color-coding plus dynamic programming, and randomized divide-and-conquer. In this paper, we provide further theoretical study on the structures of these problems, and develop improved algorithmic methods that combine existing and new techniques to obtain improved algorithms for matching and packing problems. For the 3-set packing problem, we present a deterministic algorithm of time O *(4.613k), which significantly improves the previous best deterministic algorithm of time O *(12.83k). For the 3-d matching problem, we develop a new randomized algorithm of running time O *(2.323k) and a new deterministic algorithm of running time O *(2.773k). Our randomized algorithm improves the previous best randomized algorithm of running time O *(2.523k), and our deterministic algorithm significantly improves the previous best deterministic algorithm of running time O *(12.83k). Our results also imply improved algorithms for various triangle packing problems in graphs.KeywordsTime ComplexityDynamic ProgrammingMatch ProblemPacking ProblemDynamic Programming AlgorithmThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Geographic routing is recognized as an appealing approach to achieve efficient communications with low computational complexity and space cost. In order to apply this technology in Cyber-Physical Systems (CPSs), a comprehensive consideration must be given to performance issues such as throughput, delay, and load balance. In this paper, we provide a new routing scheme based on forwarding packets to multiple geographic directions. The proposed routing protocols are studied and analyzed theoretically. Theoretical bounds of throughput, delays and space cost are presented. Simulations show that our method performs more efficiently than traditional geographic routing schemes in terms of throughput, delay, and load balance with acceptable space cost. Our experiments also verify the tradeoff between performance metrics.

Geographic routing is recognized as an appealing approach to achieve efficient communications with low computational complexity and space cost. In order to apply this technology in Cyber-Physical Systems (CPSs), a comprehensive consideration must be given to performance issues such as throughput, delay, and load balance. In this paper, we provide a new routing scheme based on forwarding packets to multiple geographic directions. The proposed routing protocols are studied and analyzed theoretically. Theoretical bounds of throughput, delays and space cost are presented. Simulations show that our method performs more efficiently than traditional geographic routing schemes in terms of throughput, delay, and load balance with acceptable space cost. Our experiments also verify the tradeoff between performance metrics.

The inverse spanning-tree problem is to modify edge weights in a graph so that a given tree T is a minimum spanning tree. The objective is to minimize the cost of the deviation. The cost of deviation is typically a convex function. We propose algorithms here that are faster than all known algorithms for the problem. Our algorithm's run time for any convex inverse spanning-tree problem is O(nm log2 n) for a graph on n nodes and m edges plus the time required to find the minima of the n convex deviation functions. This not only improves on the complexity of previously known algorithms for the general problem, but also for algorithms devised for special cases. For the case when the objective is weighted absolute deviation, Sokkalingam et al. (1999) devised an algorithm with run time O(n 2 m log(nC)) for C the maximum edge weight. For the sum of absolute deviations our algorithm runs in time O(n 2 log n), matching the run time of a recent (Ahuja and Orlin 2000) improvement for this case. A new algorithm for bipartite matching in path graphs is reported here with complexity of O(n 1.5 log n). This leads to a second algorithm for the sum of absolute deviations running in O(n 1.5 log n log C) steps.

This article examines the EOQ analysis for bulky, inexpensive, low risk items. These items occupy a disproportionately large space in the warehouse and, therefore, incur a high storage space cost. The traditional EOQ model, however, does not recognize the high space cost associated with these items and recommends the ordering of such materials in large quantities due to their low unit cost. In a traditional EOQ model, the space cost is implicitly assumed to be proportional to the price of the item. This article suggests modifications in the EOQ formula to take storage space costs into account explicitly for bulky items. An actual case illustration is presented to show how storage space and costs can be saved through the use of the proposed EOQ-Space model.

Based on analyzing the traditional image matching algorithms, a fast image matching method, which integrates improved sequential similarity detection algorithm (SSDA) and wavelet transformation, is presented in this paper. Firstly, some basic principles of SSDA image matching and wavelet transformation are introduced. Secondly, according to the shortcoming of traditional SSDA algorithm, a new SSDA algorithm is studied for improving the determining velocity of the threshold in SSDA searching match. By integrating wavelet transformation, an integrated matching algorithm is given out. Finally, the new method is compared with the traditional matching algorithms in experiments. The experimental results show that the new method has higher efficiency and accuracy in image matching and is suitable for the realization of real-time underwater navigation.

Contour segment (CS) is the fundamental element of partial boundaries or edges in shapes and images. So far, CS has been widely used in many applications, including object detection/matching and open curve matching. To increase the matching accuracy and efficiency, a variety of CS descriptors have been proposed. A CS descriptor is formed by a chain of boundary or edge points and is able to encode the geometric configuration of a CS. Because many different CS descriptors exist, a structured overview and quantitative evaluation are required in the context of CS matching. This paper assesses 27 CS descriptors in a structured way. Firstly, the analytical invariance properties of CS descriptors are explored with respect to scaling, rotation and transformation. Secondly, their distinctiveness is evaluated experimentally on three datasets. Lastly, their computation complexity is studied. Based on results, we find that both CS lengths and matching algorithms affect the CS matching performance while matching algorithms have higher affection. The results also reveal that, with different combinations of CS descriptors and matching algorithms, several requirements in terms of matching speed and accuracy can be fulfilled. Furthermore, a proper combination of CS descriptors can improve the matching accuracy over the individuals.

This paper designs and implements a multi-dimensional dynamic weight matching algorithm based on Python for intelligent matching of sustainable development education resources. The algorithm constructs a multi-dimensional feature system covering knowledge content, educational goals, and audience characteristics, introduces a dynamic weight adjustment mechanism, and can update weights in real time based on user feedback and resource usage data. The experiment uses 12,000 educational resources and 5,000 user demand data sets. Compared with the content-based matching algorithm and collaborative filtering algorithm, the accuracy of this algorithm reaches 89.2%, the recall rate is 87.6%, and the F1 value is 88.4%, which are 12.3%, 10.5%, 11.4% and 9.8%, 8.7%, 9.2% higher than the comparison algorithm respectively; the weight update response time is 0.3 seconds, which is 62.5% shorter than the comparison algorithm, covering 92.3% of scarce resources, and processing 10,000 data for a single match takes 1.2 seconds. The results show that the algorithm can improve matching accuracy, efficiency and resource coverage, and provide strong support for sustainable development education.

The automatic similarity measurement of source code can be applied to the detection of both plagiarism and code clone effectively. Suffix array is an effective way to construct the index of the full text, which has showed big applied potential in research areas such as genome analysis and character search currently. This paper introduces the relevant technologies of the similarity measurement of source code, especially the match algorithms for similar source code firstly, and then proposes a quick match algorithm that is applicable for quick similarity measurement of source code based on suffix array. Theory and experiments show that this new match algorithm for similar source code has the same similarity measurement result with current match algorithms, but it has obviously lower running time complexity.

Impact of prescription coverage on hospital and physician costs: a case study of medicare beneficiaries with chronic obstructive pulmonary disease

Region formation is an important step in dynamic binary translation to select hot code regions for translation and optimization. The quality of the formed regions determines the extent of optimizations and thus determines the final execution performance. Moreover, the overall performance is very sensitive to the formation overhead, because region formation can have a non-trivial cost. For addressing the dual issues of region quality and region formation overhead, this article presents a lightweight region formation method guided by processor tracing, e.g., Intel PT. We leverage the branch history information stored in the processor to reconstruct the program execution profile and effectively form high-quality regions with low cost. Furthermore, we present the designs of lightweight hardware performance monitoring sampling and the branch instruction decode cache to minimize region formation overhead. Using ARM64 to x86-64 translations, the experiment results show that our method achieves a performance speedup of up to 1.53× (1.16× on average) for SPEC CPU2006 benchmarks with reference inputs, compared to the well-known software-based trace formation method, Next Executing Tail (NET). The performance results of x86-64 to ARM64 translations also show a speedup of up to 1.25× over NET for CINT2006 benchmarks with reference inputs. The comparison with a relaxed NETPlus region formation method further demonstrates that our method achieves the best performance and lowest compilation overhead.

Image enhancement and minutiae matching in fingerprint verification

Many location-based services require a pre-processing step of map matching. Due to the error of the original position data and the complexity of the road network, the matching algorithm will have matching errors when the complex road network is implemented, which is therefore challenging. Aiming at the problems of low matching accuracy and low efficiency of existing algorithms at Y-shaped intersections and roundabouts, this paper proposes a space-time-based continuous window average direction feature trajectory map matching algorithm (STDA-matching). Specifically, the algorithm not only adaptively generates road network topology data, but also obtains more accurate road network relationships. Based on this, the transition probability is calculated by using the average direction feature of the continuous window of the track points to improve the matching accuracy of the algorithm. Secondly, the algorithm simplifies the trajectory by clustering the GPS trajectory data aggregation points to improve the matching efficiency of the algorithm. Finally, we use a real and effective data set to compare the algorithm with the two existing algorithms. Experimental results show that our algorithm is effective.

The large distributed interactive simulation system which based on the publish/subscribe model has considerable data, it needs to disseminate accurate data to the interested users quickly, so improving the match efficient is a very important method to solve this problem. Based on the study and comparison of current matching algorithm, we have proposed a predicate priority based event matching algorithm(hereinafter referred to as PPEM). Performance analysis and detailed experimentations are carried out to verify the effectiveness of PPEM. When the number of subscriptions is 10000, the average time of matching one event is only 22.6ms and when we change the type of data distribution or increase the number of event attribute, the average matching time of PPEM is almost unchangeable comparing with bucket and multi-dimension algorithms. All the results show that PPEM achieves high matching efficiency and also has good scalability and robustness.