Reversible logic circuits are of interests to power minimization having applications in low power CMOS design, optical information processing, DNA computing, bioinformatics, quantum computing and nanotechnology. In this paper we propose a novel 4x4 bit reversible multiplier circuit. The proposed reversible multiplier is faster and has lower hardware complexity compared to the existing counterparts. It is also better than the existing counterparts in term of number of gates, garbage outputs and constant inputs. Haghparast and Navi recently proposed a 4x4 reversible gate called "HNG". The reversible HNG gate can work singly as a reversible full adder. In this paper we use HNG gates to construct the reversible multiplier circuit. The proposed reversible multiplier circuit using HNG gate can multiply two 4-bits binary numbers. The proposed reversible 4x4 multiplier circuit can be generalized for NxN bit multiplication. We can use it to construct more complex systems in nanotechnology.

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Design of a Novel Reversible Multiplier Circuit Using HNG Gate in Nanotechnology

Irreversible logic circuits dissipate heat for every bit of information that is lost. Information is lost when the input vector can not be uniquely recovered from the output vector. Theoretically reversible logic dissipates zero power since the input vector of reversible circuit can be uniquely recovered from the output vector. Reversible computation has applications in digital signal processing, low power CMOS design, DNA computing and quantum computing. This study presents an overview of the well-known reversible gates and discuss about their quantum implementation. A new PFAG gate and its quantum implementation are presented. Finally, this study proposes a novel low cost quantum realization of reversible multiplier circuit and compares its superiority with the existing counterparts

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Low Cost Quantum Realization of Reversible Multiplier Circuit

Due to the reasons such as the rapid growth and spread of network services, mobile devices, and online users on the Internet leading to a remarkable increase in the amount of data. Almost every industry is trying to cope with this huge data. Big data phenomenon has begun to gain importance. However, it is not only very difficult to store big data and analyse them with traditional applications, but also it has challenging privacy and security problems. For this reason, this paper discusses the big data, its ecosystem, concerns on big data and presents comparative view of big data privacy and security approaches in literature in terms of infrastructure, application, and data. By grouping these applications an overall perspective of security and privacy issues in big data is suggested.

A survey on security and privacy issues in big data

Reversible logic circuits have received significant attention in quantum computing, low power CMOS design, optical information processing, DNA computing, bioinformatics, and nanotechnology. This paper presents two new 4 × 4 bit reversible multiplier designs which have lower hardware complexity, less garbage bits, less quantum cost and less constant inputs than previous ones, and can be generalized to construct efficient reversible n × n bit multipliers. An implementation of reversible HNG is also presented. This implementation shows that the full adder design using HNG is one of the best designs in term of quantum cost. An implementation of MKG is also presented in order to have a fair comparison between our proposed reversible multiplier designs and the existing counterparts. The proposed reversible multipliers are optimized in terms of quantum cost, number of constant inputs, number of garbage outputs and hardware complexity. They can be used to construct more complex systems in nanotechnology.

Optimized reversible multiplier circuit

Cloud computing is a recently looming-evoked paradigm, the aim of which is to provide on-demand, pay-as-you-go, internet-based access to shared computing resources (hardware and software) in a metered, self-service, dynamically scalable fashion. A related hot topic at the moment is task scheduling, which is well known for delivering critical cloud service performance. However, the dilemmas of resources being underutilized (underloaded) and overutilized (overloaded) may arise as a result of improper scheduling, which in turn leads to either wastage of cloud resources or degradation in service performance, respectively. Thus, the idea of incorporating meta-heuristic algorithms into task scheduling emerged in order to efficiently distribute complex and diverse incoming tasks (cloudlets) across available limited resources, within a reasonable time. Meta-heuristic techniques have proven very capable of solving scheduling problems, which is fulfilled herein from a cloud perspective by first providing a brief on traditional and heuristic scheduling methods before diving deeply into the most popular meta-heuristics for cloud task scheduling followed by a detailed systematic review featuring a novel taxonomy of those techniques, along with their advantages and limitations. More specifically, in this study, the basic concepts of cloud task scheduling are addressed smoothly, as well as diverse swarm, evolutionary, physical, emerging, and hybrid meta-heuristic scheduling techniques are categorized as per the nature of the scheduling problem (i.e., single- or multi-objective), the primary objective of scheduling, task-resource mapping scheme, and scheduling constraint. Armed with these methods, some of the most recent relevant literature are surveyed, and insights into the identification of existing challenges are presented, along with a trail to potential solutions. Furthermore, guidelines to future research directions drawn from recently emerging trends are outlined, which should definitely contribute to assisting current researchers and practitioners as well as pave the way for newbies excited about cloud task scheduling to pursue their own glory in the field.

Task Scheduling in Cloud Computing based on Meta-heuristics: Review, Taxonomy, Open Challenges, and Future Trends

Losing information causes losing power. Information is lost when the input vector cannot be uniquely recovered from the output vector of a combinational circuit. The input vector of reversible circuit can be uniquely recovered from the output vector. In this study we have emphasized on the design of reversible adder circuits that is efficient in terms of gate count, garbage outputs and quantum cost and that can be technologically mapped. It has been analyzed and demonstrated that the results of our proposed adder circuits shows better performance compared to similar type of existing designs. Technology independent equations required to evaluate these circuits have also been given.

Minimization of reversible adder circuits

Object counting in an image is one of the major challenges in image processing. Image segmentation is used to segregate similar particles which help counting approximate total number of particles. Watershed segmentation technique is considered to be most efficient technique to solve problems of segregation contiguous objects. Thresholding technique is needed for counting objects in an image. Counting only with thresholding technique can give wrong impression. Using marker controlled watershed segmentation along with thresholding technique gives satisfactory result.

Counting objects in an image by marker controlled watershed segmentation and thresholding

Chemical reaction optimization for solving shortest common supersequence problem

Longest common subsequence (LCS) is a well-known NP-hard optimization problem that finds out the longest subsequence of each member of a given set of strings. In computational biology, sequence alignment is a fundamental technique to measure the similarity of biological sequences, such as DNA and genome sequences. A high sequence similarity often applied to molecular structural as well as functional similarities and can be used to determine whether (and how) sequences are related. Finding the longest common subsequence (LCS) is one way to measure the similarity of sequences. It has also applications in data compression, FPGA circuit minimization, and bioinformatics, etc. Exact algorithms are impractical since they fail to solve this problem for multiple instances of long lengths in polynomial time. There are some approximations, heuristic, and metaheuristic methods proposed to solve the problem. Chemical reaction optimization (CRO) is a new metaheuristic method that mimics the nature of chemical reaction into optimization problems. In this paper, we have proposed chemical reaction optimization technique to solve the longest common subsequence problem for multiple instances. Here, we have redesigned four elementary operators of CRO for LCS problem. Operators of CRO algorithm are used to explore the search space both locally and globally. A novel correction method has been designed to correct the solution. Correction method works after each search operator to ensure the validity of the changes made by operators. Both solution quality and execution time are considered while designing the operators and the correction method. Thus proposed system brings robustness, efficiency, and effectiveness while solving MLCS problem. Our approach is compared with hyper-heuristic, ant colony optimization, beam ant colony optimization, and memory-bound anytime algorithms. The experimental results in lengths of the returned common sequences show that our proposed algorithm gives either same or better results than all other algorithms in less execution time.

Chemical reaction optimization for solving longest common subsequence problem for multiple string

Cloud system framework must ensure appropriate security for data storages along with satisfied timing constrain and performance. Usually, data in cloud are very dynamic and different types of data demand different level of security. Hence, if different cloud data storages can be provided with different level of security, managing data will be more flexible and efficient; the performance of system will increase as well. Therefore, in order to ensure adequate security for different data storages in cloud, we have proposed a three tier security framework. We have analyzed the performance with respect to overhead for different security services such as confidentiality, integrity and authenticity and showed that data classification according to different level of security enhances the performance of the system that provides security services to the data in cloud.

Md. Rafiqul Islam

Papers

Minimization of reversible adder circuits

Counting objects in an image by marker controlled watershed segmentation and thresholding

Chemical reaction optimization for solving shortest common supersequence problem

Chemical reaction optimization for solving longest common subsequence problem for multiple string

Agent based framework for providing security to data storage in cloud