Data structures for set manipulation- hash table, 1986

The most important issue addressed in this thesis is the efficient implementation of hash table methods. There are credential trade-offs in a desired implement ion. These are discussed in issues such as hash addressing, handling collision, hash table layout., and bucket overflow problems. The criteria of good hash function is providing even distribution. Collision is the major problem in hash table methods. Two major hashtable methods are discussed. Open Addressing Method places the synonymous items somewhere within the table. The Chaining Method, however, chains all synonymies and stores them somewhere outside the table called overflow area. Hash table is widely used by system software as an ideal data structure. Hash Table -applications canbe found in compiler's symbol table, database, directories of file organizations, as well as in problem-solving application programs

Accelerating Hash-Based Query Processing Operations on FPGAs by a Hash Table Caching Technique

Extracting valuable information from the rapidly growing field of Big Data faces serious performance constraints, especially in the software-based database management systems (DBMS). In a query processing system, hash-based computational primitives such as the hash join and the group-by are the most time-consuming operations, as they frequently need to access the hash table on the high-latency off-chip memories and also to traverse whole the table. Subsequently, the hash collision is an inherent issue related to the hash tables, which can adversely degrade the overall performance. In order to alleviate this problem, in this paper, we present a novel pure hardware-based hash engine, implemented on the FPGA. In order to mitigate the high memory access latencies and also to faster resolve the hash collisions, we follow a novel design point. It is based on caching the hash table entries in the fast on-chip Block-RAMs of FPGA. Faster accesses to the correspondent hash table entries from the cache can lead to an improved overall performance. We evaluate the proposed approach by running hash-based table join and group-by operations of 5 TPC-H benchmark queries. The results show 2.9×–4.4× speedups over the cache-less FPGA-based baseline.The research leading to these results has received funding from the European Union’s Seventh Framework Program (FP7/2007-2013), for Advanced Analytics for Extremely Large European Databases (AXLE) project under grant agreement number 318633, and from the Ministry of Economy and Competitiveness of Spain under contract number TIN2015-65316-p.Peer ReviewedPostprint (author's final draft

Backscatter from the Data Plane --- Threats to Stability and Security in Information-Centric Networking

Information-centric networking proposals attract much attention in the ongoing search for a future communication paradigm of the Internet. Replacing the host-to-host connectivity by a data-oriented publish/subscribe service eases content distribution and authentication by concept, while eliminating threats from unwanted traffic at an end host as are common in today's Internet. However, current approaches to content routing heavily rely on data-driven protocol events and thereby introduce a strong coupling of the control to the data plane in the underlying routing infrastructure. In this paper, threats to the stability and security of the content distribution system are analyzed in theory and practical experiments. We derive relations between state resources and the performance of routers and demonstrate how this coupling can be misused in practice. We discuss new attack vectors present in its current state of development, as well as possibilities and limitations to mitigate them.Comment: 15 page

Performance Evaluation of Quadratic Probing and Random Probing Algorithms in modeling Hashing Technique

In hashing technique, a hash table and hash map represent a data structure for a group of objects to map between key and value pairs, as the hash table is affected by collision and overflow. The hash table collision and overflow can be handled by searching the hash table in some systematic fashion for a bucket that is not full. In open addressing, quadratic and random probing are well-known probe sequence algorithms for collision and overflow resolution. Key density, loading density, loading factor, collisions, overflows, keys clustering, space complexity, and time complexity are the main factors that highly affect the two algorithms during hash table systematic probing. Therefore, this project is conducted to compare the quadratic probing and random probing challenge performance in terms of the key density, loading density, loading factor, overflows, collisions, keys clustering, space complexity, time complexity using step count, the order of magnitude, the worst case, the average case, and the best case. Comparing both algorithms was performed by collecting data from an online survey about the English language proficiency of 104 students. The compression result shows that the random probing algorithm has achieved similar performance compared to quadratic probing in terms of key density, loading density, loading factor, space complexity, order of magnitude, worst case, and average and best case. While the quadratic probing algorithm has recorded less time complexity using the step count method compared to the random probing algorithm. On the other hand, the random probing algorithm has recorded fewer overflows, collisions, and key clustering compared to quadratic probing. However, the study has recommended the quadratic probing algorithm for better time complexity performance and the random probing algorithm for better performance resolving overflows, collisions, and key clustering