Abstract Despite its promise, RFID technology presents numerous challenges, including incomplete data, lack of location and containment information, and very high volumes. In this work, we present a novel data inference and compression substrate over RFID streams to address these challenges. Our substrate employs a time-varying graph model to efficiently capture possible object locations and interobject relationships such as containment from raw RFID streams. It then employs a probabilistic algorithm to estimate the most likely location and co ....etc

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ABSTRACT
There is growing interest in algorithms for processing and query- ing continuous data streams (i.e., data that is seen only once in a _xed order) with limited memory resources. Providing (perhaps approximate) answers to queries over such streams is a crucial re- quirement for many application environments; examples include large IP network installations where performance data from dif- ferent parts of the network needs to be continuously collected and analyzed. The ability to estimate the number of distinct (sub)tuples in the ....etc

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to get information about the topicefficient and dynamic routing topology inference from end to end measurementsrefer the page link bellow

http://seminarsprojects.net/Thread-efficient-and-dynamic-routing-topology-inference-from-end-to-end-measurements ....etc

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Abstract.
We present novel space and time-efficient algorithms for finding frequent items over general update streams. Our algorithms are based on a novel adaptation of the popular dyadic intervals method for finding frequent items. The algorithms improve upon existing algorithms in both theory and practice.
1 Introduction
There is a growing class of applications in areas of business and scientific data processing that continuously monitor large volumes of rapidly arriving data for detecting user-programmed scenarios, some of ....etc

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Abstract.
The problem of estimating the kth frequency moment Fk, for any
non-negative integral value of k, over a data stream by looking at the items exactly
once as they arrive, was considered in a seminal paper by Alon, Matias and
Szegedy . They present a sampling based algorithm to estimate Fk where,
k 2, using space O(n1 1/k)). Coppersmith and Kumar and , using
different methods, present algorithms for estimating Fk with space complexity
O
(n1 1/(k 1)). In this paper, we present an algorithm for estimati ....etc

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kindly response for this project title for efficient and dynamic routing topology inference from end to end measurements,i need some idea for this topic .please kindly response them..because i search for project idea for this title..
kindly response for this project title for efficient and dynamic routing topology inference from end to end measurements,i need some idea for this topic .please kindly response them..because i search for project idea for this title.. ....etc

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Abstract.
We present a randomized procedure named Hierarchical Sampling from Sketches (HSS) that can be used for estimating a class of functions over the frequency vector f of update streams of the form (S) = Pn i=1 ( fi ).We illustrate this by applying the HSS technique to design nearly space-optimal algorithms for estimating the pth moment of the frequency vector, for real p _ 2 and for estimating the entropy of a data stream. 3
1 Introduction
A variety of applications in diverse areas, such as, networking, database syst ....etc

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Domain
NETWORKING

Technology
JAVA

Abstract:
EFFICIENT AND DYNAMIC ROUTING TOPOLOGY INFERENCE FROM END-TO-END MEASUREMENTS

Inferring the routing topology and page link performance from a node to a set of other nodes is an important component in network monitoring and application design. In this paper we propose a general framework for designing topology inference algorithms based on additive metrics. The framework can flexibly fuse information from multiple measurements to achieve better estimation accuracy. We develop computa ....etc

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Abstract.
We present an algorithm for estimating entropy of data streams consisting of insertion and deletion operations using O(1) space.
1 1 Introduction
Recently, there has been an emergence of monitoring applications in diverse areas, including, network traf_c monitoring, network topology monitoring, sensor networks, _nancial market monitoring, web-log monitoring, etc.. In these applications, data is generated rapidly and continuously, and must be analyzed very ef_ciently, in realtime, to identify large trends, anomalies ....etc

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ABSTRACT
There is growing interest in algorithms for processing and querying continuous data streams (i.e., data that is seen only once in a _xed order) with limited memory resources. In its most general form, a data stream is actually an update stream, i.e., comprising data-item deletions as well as inser- tions. Such massive update streams arise naturally in several application domains (e.g., monitoring of large IP network installations, or processing of retail-chain transactions). Estimating the cardinality of set expressions de_ned ....etc

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