Proposed Architecture Clause Samples

Proposed Architecture. The proposed issue Fault tolerance is one of the most crucial issue which is faced by the cloud users and cloud service providers. If poorly handled, it can lead to increased waiting time, increased job turnaround time and in worst case increased job failures. Strict fault tolerance policies provide a static fault tolerance but induce additional overhead. Considering this we to have propose an adaptive fault tolerant job scheduling method which should vary the degree of Fault tolerance as per the user requirements. The cloud users have been classified into various classes based on the application requirements along with the job classification. [1] ▇. ▇▇▇▇▇, ▇. ▇▇▇, and A. K. ▇▇▇, “A novel high adaptive fault tolerance model in real time cloud computing,” in 2014 5th International Conference - Confluence The Next Generation Information Technology Summit (Confluence), 2014, pp. 138–143. [2] ▇. ▇▇▇▇▇ and ▇. ▇▇▇▇▇▇▇, “A Migration Approach for Fault Tolerance in Cloud Computing,” Int.

Proposed Architecture. The architecture for Smart Grid infrastructure is proposed to have bi-directional communication having 5 layers wherein the Field Devices - Energy Meter/ Sub-Stations shall communicate via suitable field communication devices like DCUs/ RTUs and chosen Publically Available Communication Mode to the AMI System/ SCADA System. For visualization, GIS shall be on top of the Layer where all data from AMI and SCADA system shall be visible. The Layout has been designed as per the flow of Communication from field devices to Visualisation engine which is the GIS System. SCADA system shall be supervised by the Data Management System (DMS) and Outage Management System (OMS) which will have all the logics of controlling the Distribution Network. Similarly, the AMI will be supervised by the Meter Data Management (MDM) which will have all the logics and control. The Consumer and the Network data for analysis and effective visualization will be available in the GIS System in the Control Centre. The Control Centre will have a remote disaster data back up at a remote location suitably in Bhubaneswar.

Proposed Architecture. This section briefly describes the architecture being proposed for the implementation of [***]*. a. Design Philosophy The [***]* will be implemented using the TTG OM2000 Product. It will be designed to allow the external interfaces to be modified easily as the needs of the customer change, and standardized interfaces are developed. The core functionality will be shielded from the external interfaces via strictly defined and maintained APIs, and interaction between functional sections of the system is also structured so that enhancements to one feature or function will have predictable and limited impact to all other areas of the system. The NE specific functions and databases will be isolated from the main system and be easy to test and configure to minimize maintenance over the product lifetime.

Proposed Architecture. We have proposed a mashup that will be base on ReST with web or data sources. Data may be transmitted in XML format. This mashup will use a combination of both server and client side logic for data aggregation. We have also designed the client web browser views on the basis of our information requirements analysis of quay allocation and planning process. Figure 6-2: Proposed Information Architecture Model of Information Exchange For Vestbase 6.3.1 API / Contents We are proposing that supply chain member should develop API’s to expose their contents to the partners. We are not very sure either the current information systems applications have capabilities to expose their contents though API’s or not. If not it should be done. Screen scraping is an alternative way to aggregate data in the absence of API’s. But we will not recommend this due to lack of sophisticated, re-usable screen-scraping toolkit software. By developing standard API’s for sharing contents it will easy to accommodate new members in the mashup. 6.3.2 ReST Representational State Transfer (ReST) technique will be use to communicate on web. It is platform independent protocol for communicating with remote services. It is very simple and using XML as a data format and communicates over HTTP. Every object has a unique URI. By using GET operation of ReST we can get contents of that object. Then we can modify that object by using POST, DELETE and PUT operations. It is very easy to build, no toolkit required. It produces human readable results. Design methodology of ReST is very simple. 1- Identify resources to be exposed as service (e.g. quay status, ship trips and planning data etc.) 2- Define ”Nice” URL’s to address them 3- Distinguish between read-only (GET) from modifiable resources (POST, PUT, DELETE) 4- Identify relationships between resources correspond to hyperlinks that can be followed to get more details 5- Implement and deploy to web server It emphasis on pieces of information called resources. ReST is useful while integrating resources. Because Vestbase is collecting information in bits and pieces from different sources, we think ReST is a good option for our enterprise mashup. SOAP is an alternative option for communicating with remote services. But as compared to ReST it is complex in design methodology. It’s a framework to deliver the necessary interoperability between message-based middleware tools across the entire industry. SOAP focus more on integrating design of distributed app...

Proposed Architecture. Based on requirements acquired from section 2 and in terms of multi-layered architecture, the PROPHESY – AR consists of a set of components placed in the application – presentation layer. In terms of PROPHESY architecture, the PROPHESY-AR is a crosscutting layer which crosses PROPHESY-CPS and PROPHESY PdM. Figure 3-1:PROPHESY – AR components 3.2.1 Components of PROPHESY-AR This component in CPS level is interfacing with the following components: • CPS Message bus: with this interface, data visualization retrieves data come from CPS assets (such as sensors, machinery) and local machine learning algorithms (PROPHESY-ML -HF/ML). All these data are presented as topics in the CPS message bus. In PdM level data visualization interfaces with the following components: • PdM message bus: with this interface, data visualization retrieves data come from connected CPS to PdM platform central machine learning algorithms (PROPHESY-▇▇ -▇▇/ML). All these data are presented as topics in the PdM message bus. • Platform repository: With this interface data visualization retrieves data come from legacy systems (Pdfs, csv, files etc.).