1896644
Sketch Guided Sampling - Using On-Line Estimates of Flow Size for Adaptive Data Collection
Monitoring the traffic in high-speed networks is a data intensive problem. Uniform packet sampling is the most popular technique for reducing the amount of data the network monitoring hardware/software has to process. However, uniform sampling captures far less information than can be potentially obtained with the same overall sampling rate. This is because uni- form sampling (unnecessarily) draws the vast majority of samples from large flows, and very few from small and medium flows. This information loss on small and medium flows significantly affects the accuracy of the estimation of various network statistics. In this work, we develop a new packet sampling methodol- ogy called "sketch-guided sampling" (SGS), which offers better statistics than obtainable from uniform sampling, given the same number of raw samples gathered. Its main idea is to make the probability with which an incoming packet is sampled a decreasing sampling function f of the size of the flow the packet belongs to. This way our scheme is able to significantly increase the packet sampling rate of the small and medium flows at slight expense of the large flows, resulting in much more accurate estimations of various network statistics. However, the exact sizes of all flows are available only if we keep per-flow information for every flow, which is prohibitively expensive for high-speed links. Our SGS scheme solves this problem by using a small (lossy) synopsis data structure called counting sketch to encode the approximate sizes of all flows. Our evaluation on real-world Internet traffic traces shows that our sampling theory based the approximate flow size estimates from the counting sketch works almost as well as if we know the exact sizes of the flows.
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.
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.
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.
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?".
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.
207162632
Utility-based anonymization for privacy preservation with less information loss
Privacy becomes a more and more serious concern in applications involving microdata. Recently, efficient anonymization has attracted much research work. Most of the previous methods use global recoding, which maps the domains of the quasi-identifier attributes to generalized or changed values. However, global recoding may not always achieve effective anonymization in terms of discernability and query answering accuracy using the anonymized data. Moreover, anonymized data is often used for analysis. As well accepted in many analytical applications, different attributes in a data set may have different utility in the analysis. The utility of attributes has not been considered in the previous methods.
 In this paper, we study the problem of utility-based anonymization. First, we propose a simple framework to specify utility of attributes. The framework covers both numeric and categorical data. Second, we develop two simple yet efficient heuristic local recoding methods for utility-based anonymization. Our extensive performance study using both real data sets and synthetic data sets shows that our methods outperform the state-of-the-art multidimensional global recoding methods in both discernability and query answering accuracy. Furthermore, our utility-based method can boost the quality of analysis using the anonymized data.
2460253
Approximate processing of massive continuous quantile queries over high-speed data streams
Quantile computation has many applications including data mining and financial data analysis. It has been shown that an /spl epsi/-approximate summary can be maintained so that, given a quantile query (/spl phi/,/spl epsi/), the data item at rank /spl lceil//spl phi/N/spl rceil/ may be approximately obtained within the rank error precision /spl epsi/N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different /spl phi/ and /spl epsi/ poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.
7149198
A fault-tolerant approach to secure information retrieval
Several private information retrieval (PIR) schemes were proposed to protect users' privacy when sensitive information stored in database servers is retrieved. However, existing PIR schemes assume that any attack to the servers does not change the information stored and any computational results. We present a novel fault-tolerant PIR scheme (called FT-PIR) that protects users' privacy and at the same time ensures service availability in the presence of malicious server faults. Our scheme neither relies on any unproven cryptographic assumptions nor the availability of tamper-proof hardware. A probabilistic verification function is introduced into the scheme to detect corrupted results. Unlike previous PIR research that attempted mainly to demonstrate the theoretical feasibility of PIR, we have actually implemented both a PIR scheme and our FT-PIR scheme in a distributed database environment. The experimental and analytical results show that only modest performance overhead is introduced by FT-PIR while comparing with PIR in the fault-free cases. The FT-PIR scheme tolerates a variety of server faults effectively. In certain fail-stop fault scenarios, FT-PIR performs even better than PIR. It was observed that 35.82% less processing time was actually needed for FT-PIR to tolerate one server fault.
9110982
Modelling of Features and Feature Interactions in Nokia Mobile Phones Using Coloured Petri Nets
This paper reports on the main results from an industrial cooperation project. The project is a joint project between Nokia Research Centre and the CPN group at the University of Aarhus. The purpose of the project was to investigate features and feature interactions in development of Nokia mobile phones through construction of a Coloured Petri Nets (CPN) model. The model is extended with domain-specific graphics and Message Sequence Charts to enable mobile phone user interface designers and software developers who are not familiar with Petri Nets to work with the model. The paper presents the CPN model constructed in the project, describes how domain-specific graphics and Message Sequence Charts are used in simulations of the CPN model, and discusses how the project and in particular the construction of the CPN model has influenced the development process of features in Nokia mobile phones.
16352747
Defeating memory corruption attacks via pointer taintedness detection
Most malicious attacks compromise system security through memory corruption exploits. Recently proposed techniques attempt to defeat these attacks by protecting program control data. We have constructed a new class of attacks that can compromise network applications without tampering with any control data. These non-control data attacks represent a new challenge to system security. In this paper, we propose an architectural technique to defeat both control data and non-control data attacks based on the notion of pointer taintedness. A pointer is said to be tainted if user input can be used as the pointer value. A security attack is detected whenever a tainted value is dereferenced during program execution. The proposed architecture is implemented on the SimpleScalar processor simulator and is evaluated using synthetic programs as well as real-world network applications. Our technique can effectively detect both control data and non-control data attacks, and it offers better security coverage than current methods. The proposed architecture is transparent to existing programs.