ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 7: SORTING
In this chapter we discuss the problem of sorting an array of elements. To simplify matters, we will
assume in our examples that the array contains only intege
Efcient Security Primitives Derived from a Secure
Aggregation Algorithm
Haowen Chan
Adrian Perrig
Carnegie Mellon University, USA
Carnegie Mellon University, USA
haowenchan@cmu.edu
perrig@cmu.edu
ABSTRACT
1.
By functionally decomposing a specic algorithm
ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 5: HASHING
In Chapter 4, we discussed the search tree ADT, which allowed various operations on a set of elements.
In this chapter, we discuss the hash table ADT, which su
ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 3: LISTS, STACKS, AND
QUEUES
This chapter discusses three of the most simple and basic data structures. Virtually every significant
program will use at least one of these
ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 6: PRIORITY QUEUES
(HEAPS)
Although jobs sent to a line printer are generally placed on a queue, this might not always be the best
thing to do. For instance, one job migh
ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 4: TREES
For large amounts of input, the linear access time of linked lists is prohibitive. In this chapter we look at a
simple data structure for which the running time
CYAN
MAGENTA
YELLOW
BLACK
Haine
IN THIS BOOK YOULL LEARN:
Also Available
M
arkup is the fabric that holds the web together. But
most people only scratch the surface of what can be
achieved using (X)HTML. Thats where this book comes
inits aimed at web desi
NOORUL ISLAM COLLEGE OF ENGINEERING, KUMARACOIL.
DEPARTMENT OF COMPUTER COMPUTER APPLICATION
MC1630 DATA WAREHOUSING AND DATA MINING
MODEL QUESTION BANK
DATA MINING AND DATA WAREHOUSING (CA 037)
1.
How Accuracy is an important factor in assessing the succ
UNIT 1
LINEAR DATASTRUCTURES
ABSTRACT DATA TYPES
1.1 INTRODUCTION
Abstract data type is defined as a set of operations. In general according to the
programming rule any program should not exceed a page. In such case the program
must be splitted into modul
Unit V
5.1 Greedy Algorithm
Greedy algorithms work in phases. In each phase, a decision is made that appears to be
good, without
regard for future consequences(cost). This means that some local optimum is chosen. This
"take what you
can get now" strategy
UNIT 2
TREE STRUCTURES
NEED FOR NON-LINEAR STRUCTURES
2.1 TREES ADT
The data structures like stack, queues are used to represent sequential collection
of elements. They are useful in representation of lists of elements, simulation of queues in
reservation
UNIT 4
GRAPHS
DEFINITION
A graph G = (V,E) consist of a set of vertices V and a set of edges E. Each edge is
a pair (V,W) where V,W E V. Edges are sometimes referred to as arcs.
A graph is defined as a set of nodes or vertices and a set of lines or edges
UNIT 3
BALANCED SEARCH TREES AND INDEXING
AVL Trees
An AVL tree is a self-balancing binary search tree, and it was the first such data structure
to be invented. In an AVL tree, the heights of the two child subtrees of any node differ by at most
one. Looku
S.No.
Date
Period
Topic(s)
DATASTRUCTURES AND ALGORITHMS LAB
1
2
3
4
5
6
Implementation of singly linked list
Implementation of doubly linked list
Represent a polynomial as a linked list and write functions for
polynomial addition.
Implement stack and use
ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 9: GRAPH ALGORITHMS
In this chapter we discuss several common problems in graph theory. Not only are these algorithms
useful in practice, they are interesting because in
ABC Amber CHM Converter Trial version, http:/www.processtext.com/abcchm.html
CHAPTER 10:
ALGORITHM DESIGN
TECHNIQUES
So far, we have been concerned with the efficient implementation of algorithms. We have seen that when
an algorithm is given, the actual d
Location Verication and Trust Management for Resilient
Geographic Routing
Ke Liu, Nael Abu-Ghazalehand Kyoung-Don Kang
CS. Department, Binghamton University
cfw_kliu,nael,kang@cs.binghamton.edu
July 31, 2006
Abstract
In this paper, we consider the securit
Roadmap
Brief introduction
ZigBee: current industry standard
Detecting malicious nodes
Detecting node replication attacks
Secure data aggregation
Software-based attestation
Secure Data Aggregation
Goal: detect malicious data aggregation
with probab
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING ,VOL. 8, NO. 2, MARCH-APRIL 2011
Adaptive Fault Tolerant QoS Control Algorithms for Maximizing System Lifetime
of Query-Based Wireless Sensor Networks
Ing-Ray Chen*, Anh Phan Speer* and Mohamed Eltoweis
A Middleware Approach
to Configure Security in WSN
Peter Langendrfer
Steffen Peter, Krzysztof Piotrowski, Renato Nunes, and Augusto Casaca
IHP
Im Technologiepark 25
15236 Frankfurt (Oder)
Germany
IHP Im Technologiepark 25 15236 Frankfurt (Oder) Germany
ww
Securing Geographic Routing in Wireless Sensor Networks
K.D. Kang, K. Liu, and N. Abu-Ghazaleh
Department of Computer Science
State University of New York at Binghamton
cfw_kang, kliu, nael @cs.binghamton.edu
Abstract
We consider the security of geographi
Surviving Attacks on DisruptionTolerant Networks without
Authentication
John Burgess, George Dean Bissias,
Mark Corner, Brian Neil Levine
University of Massachusetts, Amherst
Goal
Understand DTN vulnerability
Attack analysis
Experimental evaluation
Disru
Secure In-Network Aggregation for
Wireless Sensor Networks
Bo Sun
Department of Computer Science
Lamar University
Research Supported by Texas Advanced Research Program under Grant 0035810006-2006
1
Outline of Presentation
Introduction and Motivation
Ass
SafeQ: Secure and Efficient
Query Processing in Sensor Networks
Fei Chen and Alex X. Liu
Department of Computer Science and Engineering
Michigan State University
Two-tiered Sensor Network
A two-tiered sensor network [Ratnasamy et al. 2003]
Sensor
Sensor
Secure Hierarchical In-network
Data Aggregation for Sensor
Networks
Haowen Chan
Adrian Perrig and Dawn Song
Carnegie Mellon University
haowen chan cmu
Outline
The Secure Aggregation Problem
Algorithm Description
Algorithm Analysis
Proof (sketch) of co
Secure Hierarchical In-network
Data Aggregation for Sensor
Networks
Haowen Chan
Adrian Perrig and Dawn Song
Carnegie Mellon University
haowen chan cmu
Outline
The Secure Aggregation Problem
Algorithm Description
Algorithm Analysis
Proof (sketch) of co