240982
Data streaming algorithms for estimating entropy of network traffic
Using entropy of traffic distributions has been shown to aid a wide variety of network monitoring applications such as anomaly detection, clustering to reveal interesting patterns, and traffic classification. However, realizing this potential benefit in practice requires accurate algorithms that can operate on high-speed links, with low CPU and memory requirements. In this paper, we investigate the problem of estimating the entropy in a streaming computation model. We give lower bounds for this problem, showing that neither approximation nor randomization alone will let us compute the entropy efficiently. We present two algorithms for randomly approximating the entropy in a time and space efficient manner, applicable for use on very high speed (greater than OC-48) links. The first algorithm for entropy estimation is inspired by the structural similarity with the seminal work of Alon et al. for estimating frequency moments, and we provide strong theoretical guarantees on the error and resource usage. Our second algorithm utilizes the observation that the performance of the streaming algorithm can be enhanced by separating the high-frequency items (or elephants) from the low-frequency items (or mice). We evaluate our algorithms on traffic traces from different deployment scenarios.
10184291
Efficient and scalable query routing for unstructured peer-to-peer networks
Searching for content in peer-to-peer networks is an interesting and challenging problem. Queries in Gnutella-like unstructured systems that use flooding or random walk to search must visit O(n) nodes in a network of size n, thus consuming significant amounts of bandwidth. In this paper, we propose a query routing protocol that allows low bandwidth consumption during query forwarding using a low cost mechanism to create and maintain information about nearby objects. To achieve this, our protocol maintains a lightweight probabilistic routing table at each node that suggests the location of each object in the network. Following the corresponding routing table entries, a query can reach the destination in a small number of hops with high probability. However, maintaining routing tables in a large and highly dynamic network requires non-traditional mechanisms. We design a novel data structure called an exponentially decaying bloom filter (EDBF) that encodes such probabilistic routing tables in a highly compressed manner, and allows for efficient aggregation and propagation. The search primitives provided by our system can be used to search for single keys or multiple keywords with equal ease. Analytical modeling of our design predicts significant improvements in search efficiency, verified through extensive simulations in which we observed an order of magnitude reduction in query path length over previous proposals.
47532017
On fundamental tradeoffs between delay bounds and computational complexity in packet scheduling algorithms
We clarify, extend, and solve a long-standing open problem concerning the computational complexity for packet scheduling algorithms to achieve tight end-to-end delay bounds. We first focus on the difference between the time a packet finishes service in a scheduling algorithm and its virtual finish time under a GPS (General Processor Sharing) scheduler, called GPS-relative delay. We prove that, under a slightly restrictive but reasonable computational model, the lower bound computational complexity of any scheduling algorithm that guarantees O(1) GPS-relative delay bound is /spl Omega/(logn). We also discover that, surprisingly, the complexity lower bound remains the same even if the delay bound is relaxed to O(n/sup a/) for 0<a<1. This implies that the delay-complexity tradeoff curve is flat in the "interval" [O(1),O(n)). We later conditionally extend both complexity results (for O(1) or O(n/sup a/) delay) to a much stronger computational model, the linear decision tree. Finally, we show that the same complexity lower bounds are conditionally applicable to guaranteeing tight end-to-end delay bounds, if the delay bounds are provided through the Latency Rate (LR) framework.
195710562
On fundamental tradeoffs between delay bounds and computational complexity in packet scheduling algorithms
In this work, we clarify, extend and solve an open problem concerning the computational complexity for packet scheduling algorithms to achieve tight end-to-end delay bounds. We first focus on the difference between the time a packet finishes service in a scheduling algorithm and its virtual finish time under a GPS (General Processor Sharing) scheduler, called GPS-relative delay. We prove that, under a slightly restrictive but reasonable computational model, the lower bound computational complexity of any scheduling algorithm that guarantees O(1) GPS-relative delay bound is Ω (log 2 n) (widely believed as a "folklore theorem" but never proved). We also discover that, surprisingly, the complexity lower bound remains the same even if the delay bound is relaxed to O(na) for 0‹a⋵1. This implies that the delay-complexity tradeoff curve is "flat" in the "interval" [O(1), O(n)). We later extend both complexity results (for O(1) or O(na) delay) to a much stronger computational model. Finally, we show that the same complexity lower bounds are conditionally applicable to guaranteeing tight end-to-end delay bounds. This is done by untangling the relationship between the GPS-relative delay bound and the end-to-end delay bound.
905381
On the computational complexity of maintaining GPS clock in packet scheduling
Packet scheduling is an important mechanism to provide QoS guarantees in data networks. A scheduling algorithm generally consists of two functions: one estimates how the GPS (general processor sharing) clock progresses with respect to the real time; the other decides the order of serving packets based on an estimation of their GPS start/finish times. In this work, we answer important open questions concerning the computational complexity of performing the first function. We systematically study the complexity of computing the GPS virtual start/finish times of the packets, which has long been believed to be /spl Omega/(n) per packet but has never been either proved or refuted. We also answer several other related questions such as "whether the complexity can be lower if the only thing that needs to be computed is the relative order of the GPS finish times of the packets rather than their exact values?".
16814075
On algebraic construction of Gallager and circulant low-density parity-check codes
This correspondence presents three algebraic methods for constructing low-density parity-check (LDPC) codes. These methods are based on the structural properties of finite geometries. The first method gives a class of Gallager codes and a class of complementary Gallager codes. The second method results in two classes of circulant-LDPC codes, one in cyclic form and the other in quasi-cyclic form. The third method is a two-step hybrid method. Codes in these classes have a wide range of rates and minimum distances, and they perform well with iterative decoding.
11854232
Local and parallel finite element algorithms based on two-grid discretizations
A number of new local and parallel discretization and adaptive nite element algorithms are proposed and analyzed in this paper for elliptic boundary value problems. These algorithms are motivated by the observation that, for a solution to some elliptic problems, low frequency components can be approximated well by a relatively coarse grid and high frequency components can be computed on a ne grid by some local and parallel procedure. The theoretical tools for analyzing these methods are some local a priori and a posteriori estimates that are also obtained in this paper for nite element solutions on general shape-regular grids. Some numerical experiments are also presented to support the theory. In this paper, we will propose some new parallel techniques for nite element computation. These techniques are based on our understanding of the local and global properties of a nite element solution to some elliptic problems. Simply speaking, the global behavior of a solution is mostly governed by low frequency components while the local behavior is mostly governed by high frequency compo- nents. The main idea of our new algorithms is to use a coarse grid to approximate the low frequencies and then to use a ne grid to correct the resulted residue (which contains mostly high frequencies) by some local/parallel procedures. Let us now give a somewhat more detailed but informal (and hopefully infor- mative) description of the main ideas and results in this paper. We consider the following very simple model problem posed on a convex polygonal domain R 2 : ( u + bru = f; in ;
33534823
Improved Approximation Algorithms for Maximum Resource Bin Packing and Lazy Bin Covering Problems
In this paper, we study two variants of the bin packing /covering problems called Maximum Resource Bin Packing (MRBP) and Lazy Bin Covering (LBC) problems, and present new approximation algorithms for each of them. For the offline MRBP problem, the previous best known approximation ratio is $\frac{6}{5}=1.2$, achieved by the classical First-Fit-Increasing (FFI) algorithm [1]. In this paper, we give a new FFI-type algorithm with an approximation ratio of $\frac{80}{71}\approx 1.12676$. For the offline LBC problem, it has been shown in [2] that the classical First-Fit-Decreasing (FFD) algorithm achieves an approximation ratio of $\frac{71}{60}\approx 1.18333$. In this paper, we present a new FFD-type algorithm with an approximation ratio of $\frac{17}{15}\approx 1.13333$. Both algorithms are simple, run in near linear time (i.e., O(n logn)), and therefore are practical.
872168
The super connectivity of shuffle-cubes
The shuffle-cube SQn, where n ≡ 2 (mod 4), a new variation of hypercubes proposed by Li et al. [T.-K. Li, J.J.M. Tan, L.-H. Hsu, T.-Y. Sung, The shuffle-cubes and their generalization, Inform. Process. Lett. 77 (2001) 35-41], is an n-regular n-connected graph. This paper determines that the super connectivity of SQn is 2n - 4 and the super edge-connectivity is 2n - 2 for n ≥ 6.
9688726
Motion Editing in 3D Video Database
As the next generation of media, 3D video is attracting increased attention. 3D video is a sequence of three dimensional mesh models, captured and generated for a real dynamic object. In this paper, we present a simple framework of motion editing in 3D video database to re-use 3D video data. Our system is composed of two modules. In the first module, a motion database is automatically set up from original 3D video sequences off-line by analyzing the feature vectors of each frame. It is observed that our original 3D video sequences have a two-level temporal structure. A fine-to-coarse method is proposed to extract such a structure. 3D video is segmented into the fine-level structure by a three reference frame strategy and then is clustered into the coarse-level structure. In the second module, users can synthesize the motions to edit a new 3D video sequence online. A cost function is optimized to transit between two motions with the users' requirements. All the algorithms in the system are based on the analysis in feature vector space and the edited 3D video sequence is played using OpenGL.
16343531
3D video segmentation using point distance histograms
Similar to 2D video segmentation, 3D video segmentation is to divide the 3D video in temporal domain into a set of meaningful and manageable segments (shots) that are used as basic elements for indexing. This paper proposes a temporal segmentation method for 3D video for the first time as far as we know. Point distance histograms are used considering the tradeoff between computational cost and effectiveness. In order to reflect the real motion of 3D object, three fixed points are selected, which can avoid what we call "the same sphere problem." And simulation results on total 285 frames, which are composed of four different sequences, show our method is very effective.