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Computers And Intractability A Guide To The Theory Of Np Completeness

Cloud computing simulators: A comprehensive review

Finding the best compromise between exploration and exploitation phases of a search algorithm is a hard task. The Gravitational Search Algorithm (GSA) is an evolutionary algorithm based on the Newton’s universal law of gravitation. Many studies show that GSA suffers from slow exploitation which generates premature convergence. This paper proposes a Hyperbolic Gravitational Search Algorithm (HGSA) able to find an optimal balance between exploration and exploitation. The main contributions of this work are: the definition of suitable hyperbolic acceleration coefficients, the dynamic regulation of the gravitational constant coefficient through hyperbolic function and the definition of a decreasing hyperbolic function for the best agents which attract the other agents. The proposed algorithm is compared with well-known search algorithms on classical benchmark functions, C E C -06 2019 benchmark functions and three-bar truss design problem. The results show that HGSA is better than other algorithms in terms of optimization and convergence performances.

Improving exploration and exploitation via a Hyperbolic Gravitational Search Algorithm

Workflow is composed of some interdependent tasks and workflow scheduling in the cloud environment that refers to sorting the workflow tasks on virtual machines on the cloud platform. We will encounter many sorting modes with an increase in virtual machines and the variety in task size. Reaching an order with the least makespan is an NP-hard problem. The hardness of this problem increases even more with several contradictory goals. Hence, a meta-heuristic algorithm is what required in reaching the optimal response. Thus, the algorithm is a hybridization of the ant lion optimizer (ALO) algorithm with a Sine Cosine Algorithm (SCA) algorithm and used it multi-objectively to solve the problem of scheduling scientific workflows. The novelty of the proposed algorithm was to enhance search performance by making algorithms greedy and using random numbers according to Chaos Theory on the green cloud computing environment. The purpose was to minimize the makespan and cost of performing tasks, to reduce energy consumption to have a green cloud environment, and to increase throughput. WorkflowSim simulator was used for implementation, and the results were compared with the SPEA2 workflow scheduling algorithm. The results show a decrease in the energy consumed and makespan.

A hybrid multi-objective metaheuristic optimization algorithm for scientific workflow scheduling

Arithmetic plays a major role in a computer?s performance and efficiency. Building new computing platforms supported by the traditional binary arithmetic and silicon-based technologies to meet the requirements of today?s applications is becoming increasingly more challenging, regardless whether we consider embedded devices or high-performance computers. As a result, a significant amount of research effort has been devoted to the study of nonconventional number systems to investigate more efficient arithmetic circuits and improved computer technologies to facilitate the development of computational units that can meet the requirements of applications in emergent domains. This paper presents an overview of the state of the art in nonconventional computer arithmetic. Several different alternative computing models and emerging technologies are analyzed, such as nanotechnologies, superconductor devices, and biological- and quantum-based computing, and their applications to multiple domains are discussed. A comprehensive approach is followed in a survey of the logarithmic and residue number systems, the hyperdimensional and stochastic computation models, and the arithmetic for quantum- and DNA-based computing systems and techniques for approximate computing. Technologies, processors and systems addressing these nonconventional computer arithmetic systems are also reviewed, taking into consideration some of the most prominent applications, such as deep learning or postquantum cryptography. In the end, some conclusions are drawn, and directions for future research on nonconventional computer arithmetic are discussed.

Nonconventional Computer Arithmetic Circuits, Systems and Applications

Gravitational search algorithm based novel workflow scheduling for heterogeneous computing systems

With the tremendous growth in VLSI technology in recent years, the Integration density of the transistors has reached billions causing the scaling of transistors to touch the subatomic dimension in deep submicron regime where laws of classical physics can not survive. Due to inherent information loss and other factors associated with irreversible computing, reversible circuits are becoming more and more important in terms of computing for present and future days. However, due to several factors, known synthesis approaches of classical Boolean logic like Karnaugh Map and Quine-McCluskey method cannot be applied directly to synthesize a reversible logic. In this paper, we propose a stochastic procedure to synthesize a reversible circuit. This procedure is based on a modified version of classical Quine-McCluskey method and is being used under the wrapper of two intelligent stochastic search techniques, Simulated Annealing and Ant Colony Optimization. The experimental results are quite encouraging.

Reversible circuit synthesis using ACO and SA based Quine-McCluskey method

DNA computing has attracted the attention of many a researcher in recent years for its applicability to solve computationally hard problems. It can over-perform conventional computers with its inherent massively parallelism nature. On the other hand, proper synthesis of reversible circuit is a well researched computing problem in recent days for its extremely low power consumption (ideally zero) and inherent reversible nature of reversible logic. Minimum synthesis of a reversible truth table means finding the reversible circuit made up of reversible gates satisfying given truth table with minimum cost. But none of the approaches running on conventional computers can perform minimum synthesis till date without using brute-force DFS tree search. On the other hand, DFS tree-search approach can not be reasonably implemented for larger circuits as searching a DFS tree is extremely costly on a conventional computer. In this paper, first, a procedure to search a DFS tree in constant time has been proposed to run on a DNA computer. Second, another procedure has also been proposed to apply a reversible gate on a reversible truth table in linear time that can be used to generate a DFS tree library. Finally, the generated library can then be searched in constant time to get minimum reversible circuit given a reversible truth table. An analytical feasibility study has been done and a novel methodology has been developed that can extend enormous scope of future research in this area. To the best of authors’ knowledge this is a pioneering approach to bridge reversible computing and DNA computing.

Minimal reversible circuit synthesis on a DNA computer

Since its inception, DNA computing has advanced to offer an extremely powerful, energy-efficient emerging technology for solving hard computational problems with its inherent massive parallelism and extremely high data density. This would be much more powerful and general purpose when combined with other existing well-known algorithmic solutions that exist for conventional computing architectures using a suitable ALU. Thus, a specifically designed DNA Arithmetic and Logic Unit (ALU) that can address operations suitable for both domains can mitigate the gap between these two. An ALU must be able to perform all possible logic operations, including NOT, OR, AND, XOR, NOR, NAND, and XNOR; compare, shift etc., integer and floating point arithmetic operations (addition, subtraction, multiplication, and division). In this paper, design of an ALU has been proposed using sticker-based DNA model with experimental feasibility analysis. Novelties of this paper may be in manifold. First, the integer arithmetic operations performed here are 2s complement arithmetic, and the floating point operations follow the IEEE 754 floating point format, resembling closely to a conventional ALU. Also, the output of each operation can be reused for any next operation. So any algorithm or program logic that users can think of can be implemented directly on the DNA computer without any modification. Second, once the basic operations of sticker model can be automated, the implementations proposed in this paper become highly suitable to design a fully automated ALU. Third, proposed approaches are easy to implement. Finally, these approaches can work on sufficiently large binary numbers.

Exploring the Feasibility of a DNA Computer: Design of an ALU Using Sticker-Based DNA Model

Continuous increase in bottlenecks with silicon-based conventional computers inspired researchers around the world to search for a non-conventional computing alternative that led to the development of DNA Computing, Quantum Computing etc. Each computing technologies came with their own advantages and disadvantages. Biology has inspired the computing through the pathway of DNA Computing. Since its inception it has been proven to be a powerful approach to solve computationally hard problems. But to solve otherwise general problems it needs mathematical ability. It lacks this ability in the sense that several manual interventions are required here. Moreover, the biomolecular operations in the DNA Labs are also slow to perform. To overcome this another molecule residing in the cell viz. ribosome can be used. Its automated procedure of translation can be used to perform the required operation. Recent development of artificial ribosome and the possibility of mutations in rRNAs residing in the ribosome has enabled the pathway of computation without any manual interventions. It can operate automatically at the speed of natural operations getting performed inside a living cell. This work has proposed a pathway to perform logic operations using the ribosomes.

Mayukh Sarkar

Papers

Gravitational search algorithm based novel workflow scheduling for heterogeneous computing systems

Reversible circuit synthesis using ACO and SA based Quine-McCluskey method

Minimal reversible circuit synthesis on a DNA computer

Exploring the Feasibility of a DNA Computer: Design of an ALU Using Sticker-Based DNA Model

Computing in Ribosomes: Performing Boolean Logic Using mRNA-Ribosome System