Tuesday, December 10, 2019

Distributed Information System for Software- myassignmenthelp

Question: Discuss about theDistributed Information System for Software and Effective. Answer: A distributed system can be defined as the network, which comprises of the autonomous systems connected by utilizing any distributed middleware [6]. This type of systems is utilized to share the various resources as well as capabilities for providing its users with an integrated and single network. The most important characteristics of this distributed system mainly involve allowing sharing of resources like software and systems, effective, efficient, cost effective and could be utilized from anywhere [3]. The main objective of this distributed system is to provide transparency, reliability and openness to the network and thus making it extremely popular for the users. The following essay outlines a brief discussion on the concept of distributed information system with relevant details. The essay will highlight the details of middleware and scalability in distributed system. Moreover, the various approaches and methods for building this distributed system will be mentioned here. The difficulties will also be provided here. Middleware and its Role in Distributed System Middleware can be defined as the computer software, which gives services to the software applications that are not available in the operating system. Middleware is responsible for making the implementation of communication as well as input output extremely easy by the developers of software [1]. This helps in focusing on the particular motive for their application. It lies between the applications and the operating system on both the sides of the distributed computing network. Middleware plays an important role in the distributed system. It is the particular type of infrastructure that helps to facilitate the creation of all applications of business and thus providing major services such as transactions, messaging, concurrency, threading and the framework for service component architecture for the SOA applications [5]. The distributed nature of any application within the distributed system is hidden by this middleware. Moreover, the interconnected parts are kept running as well as operational within the distributed locations thus making these extremely simpler and easier in managing. Scalability and its Three Major Types Scalability can be defined as the sole capability of any network, system and process for handling the increasing amount of work or with the potential for accommodating the growth [8]. Scalability is an extremely important requirement that makes any system effective and efficient. Any system becomes scalable if it has the capability for increasing the total output. There are three major types of scalability in distributed systems. The descriptions of each type with examples are given below: i) Load Scalability: A system has load scalability when it comprises of the capability in functioning gracefully. It occurs only when there is no delay in the functions and no consumption of unproductive resources [2]. The load scalability can eventually schedule the shared resources and helps in inadequate parallelism exploitation. The example of this type of scalability refers to the system that has self expanding performance measure. ii) Space Scalability: A system has space scalability when its memory requirement does not develop to the intolerable level since the number of items is increasing [7]. The example of space scalability is the sparse matrix method or compression. Structural Scalability: A system has structural scalability when the implementation or standard does not impede the increment of object numbers [3]. The example of structural scalability is any system with finite address space. Various Approaches to build Distributed System There are various approaches and methods for building any distributed system. They are as follows: i) Message Oriented Middleware: This type of approach helps to structure the communication and thus the distributed system is built. The main benefit of this particular approach is that it helps to support for the asynchronous communication [1]. Hence, the sender transmits data to the receiver without waiting for any response. ii) Publish or Subscribe Middleware: This type of approach is for the synchronous communication. They are responsible for producing events on various topics, which are propagated with the system [5]. The publishers require describing the kind of events generated priori. Difficulties faced by Management There are various difficulties and technical issues that are being faced by the management in any distributed system. The most significant issues faced by them are given below: i) Inherent Complexities: The inherent complexities mainly arise from the domain challenges like elements of distributed system residing in different address spaces and protocols utilized for communications [1]. The various networks, which connect the components with the distributed systems, involve several problems like overload, transient failures and latency that eventually affects the efficiency of the system. ii) Accidental Complexities: This type of problem mainly arises from the limitations with the software tools or techniques like poor distributed debuggers and non portable APIs [4]. These types of problems are often deliberate by the developers, who like lower level languages or platforms like C based operating system. Inadequate Methods or Techniques: The various methods of software analysis and techniques for design cannot produce the best quality service or QoS [7]. This is extremely dangerous and thus the developers face problems due to the inadequate techniques. iv) Continuous Re-discovery of Techniques: The re-invention of the techniques are continuous and thus the problems are increased for the developers [6]. The real time operating systems often become difficult to manage and control hardware resources. Therefore, from the above discussion, it can be concluded that, any distributed system is the specific model, where the components are located on the networked computers or systems for communicating and coordinating the activities by simply passing messages. These components eventually interact amongst each other for achieving the similar goal. There are three important features of this distributed system and they are the lacking of a global clock, components concurrency and sole failure of components. These types of systems work and act as one single computer. The performance of these systems is much higher than the other distributed models. The above essay has outlined a detailed description on the concept of distributed system and how this system could be utilized by the users. The middleware and its role in distributed system are also provided here. Moreover, the scalability and the various approaches for building the system are mentioned here. The essay has also given the diffic ulties faced by management due to distributed system. References [1] Abadi, Martn, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado et al. "Tensorflow: Large-scale machine learning on heterogeneous distributed systems."arXiv preprint arXiv:1603.04467(2016). [2] Chen, Tianqi, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, and Zheng Zhang. "Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems."arXiv preprint arXiv:1512.01274(2015). [3] Orgerie, Anne-Cecile, Marcos Dias de Assuncao, and Laurent Lefevre. "A survey on techniques for improving the energy efficiency of large-scale distributed systems."ACM Computing Surveys (CSUR)46, no. 4 (2014): 47. [4] Valls, Marisol Garca, Iago Rodrguez Lpez, and Laura Fernndez Villar. "iLAND: An enhanced middleware for real-time reconfiguration of service oriented distributed real-time systems."IEEE Transactions on Industrial Informatics9, no. 1 (2013): 228-236. [5] Ports, Dan RK, Jialin Li, Vincent Liu, Naveen Kr Sharma, and Arvind Krishnamurthy. "Designing Distributed Systems Using Approximate Synchrony in Data Center Networks." InNSDI, pp. 43-57. 2015. [6] Enokido, Tomoya, and Makoto Takizawa. "An integrated power consumption model for distributed systems."IEEE Transactions on Industrial Electronics60, no. 2 (2013): 824-836. [7] Stubbs, Joe, Walter Moreira, and Rion Dooley. "Distributed systems of microservices using docker and serfnode." InScience Gateways (IWSG), 2015 7th International Workshop on, pp. 34-39. IEEE, 2015. [8] Ahmed, Waseem, and Yong Wei Wu. "A survey on reliability in distributed systems."Journal of Computer and System Sciences79, no. 8 (2013): 1243-1255.

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