Christopher J. Martinez

On designing fast nonuniformly distributed IP address lookup hashing algorithms

Computer networks have continued to make substantial advances in the past couple of decades through better technologies and methodologies employed. As the usage of the networks continues to increase exponentially, high throughput of the networks has to be maintained with various performance-efficient network algorithms. IP address lookup is one of the processes, the performance of which dearly affects the overall network performance. Hashing has been widely used for fast IP address lookup due to its simplicity, but mostly assuming on hashing from an address set with uniformly distributed key values. Performance from these known hashing techniques is far from optimal due to the high nonuniformity in actual IP address distribution. In this paper, we propose a preprocessing method for the IP address databases to extract certain regularity to allow for design of more efficient hashing algorithms based on XOR operations. Simulation results show an improvement in performance ranging from 35% to 72% on randomly generated addresses and several sample IP address databases. The paper also shows that the proposed algorithms deliver comparable performance to other well-known hashing algorithms such as the CRC and RS hashing while requiring much less hardware to implement and a much shorter time to perform.

Adaptive Hashing for IP Address Lookup in Computer Networks

For applications that rely on large databases as the core data structure, the need for a fast search process is essential. Hashing algorithms have widely been adopted as the search algorithm of choice for fast lookups. Hashing algorithms involve the creation of hash values from the target database entries. A hashing algorithm that transforms the database to hash values with a distribution as uniform as possible would lead to a better search performance. When a database is already value-wise uniformly distributed, any regular hashing algorithm, such as bit-extraction, group-XOR, etc., will lead to a statistically perfect hashing result. In almost all known practical applications, the target database rarely demonstrates uniformly distributed characteristic. The use of any known regular hashing algorithm can lead to a performance far less than desirable. This paper aims at designing a hashing algorithm that can deliver a better performance for all practical databases. An analytical preprocess is performed on the original database to extract critical information that would significantly benefit the design of a better hashing algorithm. The process includes sorting database hash bits to provide a priority that would facilitate the decision-making on which bits and how these bits should be combined to generate better hash values. The algorithm follows an ad hoc design that is critical to adapting to real-time situation when there exists a changing database with an irregular non-uniform distribution. The proposed technique clearly outperforms all known regular hashing algorithms by a significant margin

Optimal XOR hashing for a linearly distributed address lookup in computer networks

Hashing algorithms have been widely adopted to provide a fast address look-up process which involves a search through a large database to find a record associated with a given key. Modern examples include address-lookup in network routers for a forwarding outgoing link, rule-matching in intrusion detection systems comparing incoming packets with a large database, etc. Hashing algorithms involve transforming a key inside each target data to a hash value hoping that the hashing would render the database a uniform distribution with respect to this new hash value. When the database are already key-wise uniformly distributed, any regular hashing algorithm would easily lead to perfectly uniform distribution after the hashing. On the other hand, if records in the database are instead not uniformly distributed, then different hashing functions would lead to different performance. This paper addresses the case when such distribution follows a natural negative linear distribution, which is found to approximate distributions in many various applications. For this distribution, we derive a general formula for calculating the distribution variance produced by any given non-overlapped bit-grouping XOR hashing function. Such a distribution variance from the hashing directly translates to performance variations in searching. In this paper, the best XOR hashing function is determined for any given key size and any given hashing target size.

Advanced Hash Algorithms with Key Bits Duplication for IP Address Lookup

Hashing technique have been widely adopted for various computer network applications such as IP address lookup and intrusion detection, among which XOR-hashing is one of most popular techniques due to its relatively small hash process delay. In all the current commonly used XOR-hashing algorithms, each of the hash key bits is usually explicitly XORed only at most once in the hash process, which may limit the amount of potential randomness that can be introduced by the hash process. This paper looks into the possibility in duplicating/reusing key bits to inject additional randomness into the hash process thus enhancing the overall performance further. However, when a key bit is reused, newly induced correlation arises among resulted hash bits where key bits are shared which may easily offset the intended benefit from bit duplication. The novel hash technique introduced in this paper shows how to intelligently apply bit duplication while minimizing the amount of correlation induced in the duplication process.

Performance of commercial multimedia workloads on the Intel Pentium 4: A case study

In this paper, we present a case study of the execution time characteristics of several popular commercial audio and video applications on a state of the art microprocessor, the Intel Pentium 4. The on-chip performance counters on the Pentium 4 processor are used to perform this study using actual real-world workloads. While the Pentium 4 is capable of executing 3-4 instructions in one cycle, it was observed that commercial audio and video applications take between 1.4 and 3.5 cycles (per instruction) to execute. Despite using large caches and sophisticated out of ordering techniques, the average cycles per instruction is higher than a predecessor like Pentium II. This indicates that while clock frequency has improved, real speedups are not scaling. The performance of multimedia programs is compared with execution characteristics of SPEC CPU 2000 programs. Performance impact of branch predictors, caches and trace caches on the Pentium 4 are analyzed for multimedia and SPEC CPU applications.

A Dynamic Frequency Controlling Technique for Power Management in Existing Commercial Microcontrollers

Power continues to be a driving force in central processing units (CPU) design. Most of the advanced breakthroughs in power have been in a realm that is applicable to workstation CPUs. Advanced power management systems will manage temperature, dynamic voltage scaling and dynamic frequency scaling in a CPU. The use of power management systems for microcontrollers and embedded CPUs has been modest, and mostly focuses on very large scale integration (VLSI) level optimizations compared to system level optimizations. In this paper, a dynamic frequency controlling (DFC) technique is introduced, to lay the foundation of a system level power management system for commercial microcontrollers. The DFC technique allows a commercial microcontroller to have minor modifications on both the hardware and software side, to allow the clock frequency to change to save power; results in this study show a 10% savings. By adding an additional layer of software abstraction at the interrupt level, the microcontroller can operate without having knowledge of the current clock frequency, and this can be accomplished without having to use an embedded operating system.

Optimal XOR hashing for non-uniformly distributed address lookup in computer networks

Hashing algorithms have been widely adopted to provide a fast address lookup process which involves a search through a large database to find a record associated with a given key. Modern examples include address lookup in network routers for a forwarding outgoing link, rule-matching in intrusion detection systems comparing incoming packets with a large database, etc. Hashing algorithms involve transforming a key inside each target data to a hash value hoping that the hashing would render the database a uniform distribution with respect to this new hash value. When the database are already key-wise uniformly distributed, any regular hashing algorithm would easily lead to perfectly uniform distribution after the hashing. On the other hand, if records in the database are instead not uniformly distributed, then different hashing functions would lead to different performance. This paper addresses the cases when such distribution follows a natural negative linear distribution, a partial negative linear distribution, or an exponential distribution which are found to closely approximate many real-life database distributions. For each of these distributions, we derive a general formula for calculating the distribution variance produced by any given non-overlapping bit-grouping XOR hashing function. Such a distribution variance from the hashing directly translates to performance variations in searching. Through this, the best XOR hashing function can be easily determined for any given key size and any given hashing target size.

CLIP 4 Robotics: A Click-Based Programming Language.

CLIP 4 Robotics is an icon-based Visual Programming Language (VPL) that is designed for the novice programmer. The VPL program is written as a series of icons that represent program instruction syntax. The images allow for a wide age range to use the VPL from children to adults. Icons allow for users to feel less intimated with programming than with text-based languages. CLIP 4 Robotics has a user-defined syntax that helps the novice comprehend the language especially children. Icons allow children that have let master reading to program. Example programs are shown that demonstrate the CLIP 4 Robotics language in two different scenarios.

Observing Hand Placement and Measurement on a Tabletop Using a Depth Camera

Tabletop computing is a new emerging interface that can be realized with low cost using depth sensor cameras such as the Microsoft Kinect. The optimization of the touch interface using depth measurements must take into account the size variations of a diverse population. In this study, we examine a sample population to understand the differences in hand measurements a depth camera would detect on a large tabletop computer. We have broken down the hand into three measurements (the three joints in the hand) that may be of interest to research working in the field. The hand measurements have been taken at different locations on the table to account for changes in the hand position caused by the user stretching their arm.

Human Avatar Robotic Puppeteering (HARP)

The Human Avatar Robotic Puppeteering (HARP) project is focused on studying whether homologous puppeteering (controlling via mimicry) is an effective control principle for robots, given minimal user training. This project aims to develop a practical implementation at low-cost. The HARP project is a three-joint robotic crane that is capable of grasping objects. In order to control via puppeteering, the system tracks the user’s hand moving in free space in real time as an avatar. This implementation relies on a Microsoft Kinect (