Top 10 Research Topics in Parallel and Distributed Computing

Top 10 Research Topics in Parallel and Distributed Computing

The specific pressure in locations of the internet with concurrent enhancement in the availability of big data with several users has to accurate the computing tasks in parallel. Parallel and distributed computing will take place in several research areas such as networks, software engineering, computer science, computer architecture, operating systems, algorithms, etc. At present, our research experts are providing complete research support and research guidance for all the research topics in parallel and distributed computing. The ideas based on an essential system of parallel and distributed computing are highlighted below shared memory models, mutual exclusion, concurrency, message passing, memory manipulation, etc.

  Parallel computing is deployed for the provision of high-speed power of processing where it is required and supercomputers are the best example for parallel computing. In this process, distributed computing is accustomed when the geographical locations are differing for the computers.

Top 10 Research Topics in Parallel and Distributed Computing

  • Software-defined fog node in blockchain architecture & cloud computing
  • Multi clustering approach in mobile edge computing
  • Distributed computing & smart city services
  • Geo distributed fog computing
  • Service attacks in software-defined network with cloud computing
  • Distributed trust protocol for IaaS cloud computing
  • Large scale convolutional neural networks
  • Parallel vertex-centric algorithms
  • Partitioning algorithms in mobile environments
  • Configuration tuning for hierarchical cloud schedulers
  • Distributed computing with delay tolerant network

We provide the research work with the implementation of research algorithms, methodologies that shape the research projects with the proper execution and appropriate code implementation. 

Top 5 Research Topics in Parallel and Distributed Computing

Parallel Computing

           Parallel computing delivers the simultaneous process and it is used to save both money and time. In general, the memory in a parallel system might be two-dimensional such as disseminated and collective. The processors in parallel computing have to perform numerous tasks which are assigned to the processors concurrently.

Distributed Computing

           Distributed computing is entirely different from the parallel computing process because here in distributed computing a task is separated between several computers. In addition, the computers can pass the messages among them and the shared memory is not used. Several autonomous computers appear as one computer for the users. 

What are the Characteristics of Parallel and Distributed Computing?

  • Transparency
    • It is based on the process of communication and location of what the node have to access to other nodes
  • Fault Tolerance
    • It is the process of detecting failures and how the system is recovered as soon as possible
  • Scalability
    • The process of computing and processing has some accumulation in several machines
  • Concurrency
    • The process similar task happing in several machines at a particular time
  • Openness
    • The frankness of software structure and its enhancement
  • Resource Sharing
    • Distribution of hardware and software data

Parallel Computing Versus Distributed Computing

  • Definition
    • Parallel and distributed computing are different from each other. In distributed computing, several computers are seemed together as a single system for the users to perform a single task by messages among them. In parallel computing, a single task is split into several tasks and allocated to various system
  • Usage
    • In distributed computing, the high scalability place is required for usage. In parallel computing, the place which has high speed is preferred for the performance
  • Synchronization
    • A similar master clock is used for the synchronization in parallel computing and the synchronization algorithms are used in distributed computing
  • Resources sharing
    • Distributed computing is used to have their memory and processers. In parallel computing, one memory is shared for all the processors
  • Scalability
    • The limited scalability is used in parallel computing and without any limitations the systems are working in addition to networks in distributed computing
  • Dependency among processes
    • There is no dependency in distributed computing and parallel, it is fully dependent on each other because the output of one process is the input of the next task
  • Number of computer systems involved
    • A single system is involved in parallel computing as multiple hosts. In distributed computing, many systems are available in the computer system 

Distributed Parallel Computing

           The process of distributed parallel computing system is deployed for the functions of several computers in a single network with their allocated task. In general, we are using many applications based on the distributed and parallel computing system such as

  • Grid Computing
  • Cloud computing
  • Distributed supercomputers
  • Travel reservation
  • Electronic banking
  • Cloud storage system
  • Internet, intranet & email system
  • Peer to peer network

Below, our research experts have mentioned the pioneering research topics in parallel and distributed computing, it is a significant research system and it is used to locate the various geographical locations through computers. As per the data, the research fields in parallel and distributed computing are as follows

Recent Research Areas of Parallel and Distributed Computing

  • Heterogeneous computing
  • Biological & molecular computing
  • Supercomputing
  • Computational intelligence
  • Quality development using HPC
  • Distributed data storage & cloud architecture
  • Federated ML & shared memory
  • Fault tolerance software system
  • Peer to peer network
  • MI & AL
  • Distributed grid computing
  • Web technologies
  • Distribution & management system in multimedia
  • Mobile crowdsensing
  • IoT & multi-tier computing

           At present, we can see the issues from different sources in parallel and distributed computing. Thus, our research experts provide better research solutions for all such research challenges mentioned below. At this moment, let us discuss the significant research challenges in parallel and distributed computing.

Latest Research Issues of Parallel and Distributed Computing

  • Management overhead
    • There are some additional functions in this process such as logging, intelligence, load balancing, monitoring, etc. All the above-mentioned functions are used for the visibility
  • Network & communication failure
    • There is no appropriate message communication (messages are delivered wrongly to other nodes) that seems to breakdown the communication
  • Data integration & consistency
    • It is used to coordinate the sequence of changes in data and it is a complex issue in the distributed computing process and it leads the nodes to fall, stop and start
  • Pipeline performance
    • It is the outline of multi-purpose stream processing
  • Fault Tolerance
    • It leads to let down the functions of nodes
  • Scalability
    • Functions of structural designs used in the linear process with rational quantity
  • Data consistency
    •  It functions as a warehouse of data in significant corporations

Thus, by solving all such research challenges in parallel and distributed computing our technical experts have shared some significant requirements of parallel and distributed computing. And, that helps the research scholars to be familiar with the most substantial real-time requirements in current research topics in parallel and distributed computing research.

Future Research Directions of Parallel and Distributed Computing Projects

  • Distributed memory parallel computing
  • Distinctive purpose & hybrid structural design
  • Accelerators & multicore functions
  • Cloud Computing
  • High performance & shared memory computing
  • Developing domain applications
  • Structure of supercomputing & applications

The research scholars can get the best guidance for handling parallel and distributed computing tools from our research and development experts. In this regard let us see about some of the important and best-distributed computing tools below

Development Tools for Parallel and Distributed Computing Projects

  • Open MPI
  • Zabbix & Nimrod
  • SPRNG & Apache Hadoop
  • Paralib & simGrid
  • Alchemi & distributed folding GUI

To this end, we believe that you get the top to bottom way out to select the research topics in parallel and distributed computing. The above information will make you a better research scholar to precede your research in parallel and distributed computing. Yet, if you want to become an expert, then you must need a better tutor. In addition, we have several research experts for the scholar’s research assistance. We are ready to provide help and clear up all your difficulties at any stage. So, you can enrich your skills through our keen help.

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