Uniquely represented data structures for computational geometry
... Most computer applications store a significant amount of information that is hidden from the application interface—sometimes intentionally but more often not. This information might consist of data left behind in memory or disk, but can also consist of much more subtle variations in the state of a s ...
... Most computer applications store a significant amount of information that is hidden from the application interface—sometimes intentionally but more often not. This information might consist of data left behind in memory or disk, but can also consist of much more subtle variations in the state of a s ...
Network Applications of Bloom Filters: A Survey
... from which symmetry reveals that the minimum value for g occurs when p = 1=2, or equivalently k = ln 2(m=n). In this case the false positive rate f is (1=2)k = (0:6185)m=n : In practice, of course, k must be an integer, and smaller k might be preferred since they reduce the amount of computation ne ...
... from which symmetry reveals that the minimum value for g occurs when p = 1=2, or equivalently k = ln 2(m=n). In this case the false positive rate f is (1=2)k = (0:6185)m=n : In practice, of course, k must be an integer, and smaller k might be preferred since they reduce the amount of computation ne ...
Computational Bounds on Hierarchical Data Processing with
... hash-based authenticated dictionaries of size n incur Θ(log n) complexity. We also present a new hash-based dictionary ADS based on our skip-list structure from Section 3 and show that it has better authentication cost parameters than previous hash-based ADS constructions. Multicast Key Distributio ...
... hash-based authenticated dictionaries of size n incur Θ(log n) complexity. We also present a new hash-based dictionary ADS based on our skip-list structure from Section 3 and show that it has better authentication cost parameters than previous hash-based ADS constructions. Multicast Key Distributio ...
Concise Notes on Data Structures and Algorithms
... Concise Notes on Data Structures and Algorithms Ruby Edition Christopher Fox ...
... Concise Notes on Data Structures and Algorithms Ruby Edition Christopher Fox ...
Programming Embedded Computing Systems using Static Embedded SQL
... commercial SQL engines have a large footprint that cannot be stored on an embedded device, and (3) most SQL operations can be executed in satisfactory time only when potentially large amounts of additional storage is available for auxiliary structures, such as indices and materialized views. The pap ...
... commercial SQL engines have a large footprint that cannot be stored on an embedded device, and (3) most SQL operations can be executed in satisfactory time only when potentially large amounts of additional storage is available for auxiliary structures, such as indices and materialized views. The pap ...
A Practical Introduction to Data Structures and Algorithm Analysis
... (the domain) and outputs (the range). • An input to a function may be single number, or a collection of information. • The values making up an input are called the parameters of the function. • A particular input must always result in the same output every time the function is ...
... (the domain) and outputs (the range). • An input to a function may be single number, or a collection of information. • The values making up an input are called the parameters of the function. • A particular input must always result in the same output every time the function is ...
Proof of Freshness: How to efficiently use an online single secure
... In our system, we place a small TCB at a server for maintaining certificates of global counters for timestamping to allow clients to immediately detect misbehavior, including replay attacks. This allows us to prevent forking attacks and guarantee the freshness, integrity, and consistency of data. Ou ...
... In our system, we place a small TCB at a server for maintaining certificates of global counters for timestamping to allow clients to immediately detect misbehavior, including replay attacks. This allows us to prevent forking attacks and guarantee the freshness, integrity, and consistency of data. Ou ...
Theory and Practice of Monotone Minimal Perfect Hashing 1
... better ones. To this purpose, we provide precise, big-Oh-free estimates of the number of bits occupied by each structure, which turn out to match very closely the number of bits required in the actual implementations; such estimates are valuable in two ways: they make it possible to tune optimally t ...
... better ones. To this purpose, we provide precise, big-Oh-free estimates of the number of bits occupied by each structure, which turn out to match very closely the number of bits required in the actual implementations; such estimates are valuable in two ways: they make it possible to tune optimally t ...
W-7 OMT-II
... The new records are added at the end of the table. We can insert one row or various rows at the same time, normally getting the data from another table, and so an append query has a source (the table or tables where it gets the data from) and a destiny (the table where we will insert the data). The ...
... The new records are added at the end of the table. We can insert one row or various rows at the same time, normally getting the data from another table, and so an append query has a source (the table or tables where it gets the data from) and a destiny (the table where we will insert the data). The ...
Performance Problems in ABAP Programs: How to Fix Them Werner Schwarz
... BELNR, and GJAHR) that specifies a value for the field BELNR (0000000001) and returns one record from the database. An ideal index for such a database selection would start with fields MANDT and BELNR. Suppose there is no such index, however. In this case, the table’s key index must be used,2 which ...
... BELNR, and GJAHR) that specifies a value for the field BELNR (0000000001) and returns one record from the database. An ideal index for such a database selection would start with fields MANDT and BELNR. Suppose there is no such index, however. In this case, the table’s key index must be used,2 which ...
Average-Case Analysis of Algorithms and Data Structures
... of generating functions to recover information about their coefficients. The methods are often applicable to functions known only indirectly via functional equations, a situation that presents itself naturally when counting recursively defined structures. In Sections 3–6, we apply general methods fo ...
... of generating functions to recover information about their coefficients. The methods are often applicable to functions known only indirectly via functional equations, a situation that presents itself naturally when counting recursively defined structures. In Sections 3–6, we apply general methods fo ...
Average-Case Analysis of Algorithms and Data Structures
... where In = jIn j and Jnk is the number of inputs of size n with complexity k for algorithm A. Average-case analysis then reduces to combinatorial enumeration. The next step in the analysis is to express the complexity of the algorithm in terms of standard functions like n (log n) (log log n) , wh ...
... where In = jIn j and Jnk is the number of inputs of size n with complexity k for algorithm A. Average-case analysis then reduces to combinatorial enumeration. The next step in the analysis is to express the complexity of the algorithm in terms of standard functions like n (log n) (log log n) , wh ...
Offset Addressing Approach to Memory
... producing the longest matching prefix 01*. C. Offset Encoding of Multi-bit Tries A multi-bit trie with a stride of s is generally used to boost the lookup throughput of a binary trie by a factor of s . However, the node size grows exponentially with the stride size, which leads to the rapidly increa ...
... producing the longest matching prefix 01*. C. Offset Encoding of Multi-bit Tries A multi-bit trie with a stride of s is generally used to boost the lookup throughput of a binary trie by a factor of s . However, the node size grows exponentially with the stride size, which leads to the rapidly increa ...
Authenticated Data Structures for Graph and Geometric Searching
... of possible answers is much larger than the data size itself. For example, there are O(n2 ) different paths in a tree of n nodes, and each of these paths can have O(n) edges. Requiring an authenticator to digitally sign every possible response is therefore prohibative, especially when the data is ch ...
... of possible answers is much larger than the data size itself. For example, there are O(n2 ) different paths in a tree of n nodes, and each of these paths can have O(n) edges. Requiring an authenticator to digitally sign every possible response is therefore prohibative, especially when the data is ch ...
KorthDB6_ch11
... performance degrades as file grows, since many overflow blocks get created. Periodic reorganization of entire file is required. Advantage of B+-tree index files: automatically reorganizes itself with small local changes, in the face of insertions and deletions. Reorganization of entire file ...
... performance degrades as file grows, since many overflow blocks get created. Periodic reorganization of entire file is required. Advantage of B+-tree index files: automatically reorganizes itself with small local changes, in the face of insertions and deletions. Reorganization of entire file ...
Creating Common Information Structures Using Lists Stored in SAS® DATA Step HASH Objects
... table structure. The data associated with a key will be simply called “node data”. Since we are going to be storing our data in hash tables we have to make our keys, in an individual list, either numeric or character type. All the examples we will cover in this paper will have numeric typed keys. Th ...
... table structure. The data associated with a key will be simply called “node data”. Since we are going to be storing our data in hash tables we have to make our keys, in an individual list, either numeric or character type. All the examples we will cover in this paper will have numeric typed keys. Th ...
Text Processing in Linux A Tutorial for CSE 562/662 (NLP)
... Now I'd like to see that same list, but only see each word once (unique). hint: you can tell 'sort' which fields to sort on e.g., sort +3 –4 will skip the first 3 fields and stop the sort at the end of field 4; this will then sort on the 4th field. sort –k 4,4 will do the same thing for f in out*; d ...
... Now I'd like to see that same list, but only see each word once (unique). hint: you can tell 'sort' which fields to sort on e.g., sort +3 –4 will skip the first 3 fields and stop the sort at the end of field 4; this will then sort on the 4th field. sort –k 4,4 will do the same thing for f in out*; d ...
Creating common information structures using list's stored in data step hash objects
... table structure. The data associated with a key will be simply called “node data”. Since we are going to be storing our data in hash tables we have to make our keys, in an individual list, either numeric or character type. All the examples we will cover in this paper will have numeric typed keys. Th ...
... table structure. The data associated with a key will be simply called “node data”. Since we are going to be storing our data in hash tables we have to make our keys, in an individual list, either numeric or character type. All the examples we will cover in this paper will have numeric typed keys. Th ...
Structural Signatures for Tree Data Structures
... are in T but not in S; (2) the structural relationship between a node x in S and some node y which is in T but not in S; and (3) the relative (structural) order between a node x which is in S and y, which is in T but not in S. One approach to avoid such information leakage is to pre-compute and stor ...
... are in T but not in S; (2) the structural relationship between a node x in S and some node y which is in T but not in S; and (3) the relative (structural) order between a node x which is in S and y, which is in T but not in S. One approach to avoid such information leakage is to pre-compute and stor ...
Metadata Repository Design Concepts
... Stewardship provides another metadata area which may be associated to any of a number of other metadata items. An Operational Steward may be associated to a Business Process or a Data Definition. A Technical Steward may be associated to a Data Feed, or a Data System. Tables holding information abou ...
... Stewardship provides another metadata area which may be associated to any of a number of other metadata items. An Operational Steward may be associated to a Business Process or a Data Definition. A Technical Steward may be associated to a Data Feed, or a Data System. Tables holding information abou ...
Title: First Slide in a Presentation
... • Uses a weak encryption algorithm that can be easily cracked © 2005 Cisco Systems, Inc. All rights reserved. ...
... • Uses a weak encryption algorithm that can be easily cracked © 2005 Cisco Systems, Inc. All rights reserved. ...
Chapter 7: Relational Database Design
... Multilevel insertion (as well as deletion) algorithms are simple ...
... Multilevel insertion (as well as deletion) algorithms are simple ...
CISC220-final
... Efficiency of Algorithms • An operation for an Absract Data Type can be thought of as a “problem” ...
... Efficiency of Algorithms • An operation for an Absract Data Type can be thought of as a “problem” ...
Rainbow table
A rainbow table is a precomputed table for reversing cryptographic hash functions, usually for cracking password hashes. Tables are usually used in recovering a plaintext password up to a certain length consisting of a limited set of characters. It is a practical example of a space/time trade-off, using less computer processing time and more storage than a brute-force attack which calculates a hash on every attempt, but more processing time and less storage than a simple lookup table with one entry per hash. Use of a key derivation function that employs a salt makes this attack infeasible.Rainbow tables are an application of an earlier, simpler algorithm by Martin Hellman.