What is a data center? List and explain the features of GIDC, Nepal.

-

 

 DATA CENTER

  • A data center is a storage facility that holds computer facilities such as servers, routers, switches, and firewalls, as well as supporting components such as backup equipment, fire suppression systems, and conditioning. A data center can be complicated (dedicated building) or simple (dedicated building) (2 area or room that houses only a few servers). A data center can also be private or shared.
  • Datacenter components are frequently at the heart of an organization's information system (IS). As result, these important data center facilities often need a substantial investment in supporting technologies such as air conditioning/climate control systems, fire suppression/smoke detection, secure entrance am identification, and elevated floors for easier cabling and water damage avoidance.
  • When data centers are shared, allowing virtual data center access to numerous organizations and individuals frequently makes more sense than allowing entire physical access to multiple companies or persons. Shared data centers are often owned and managed by a single organization that rents out cent partitions (virtual or physical) to other client businesses. Client/leasing organizations are frequently time businesses that lack the financial and technical capabilities necessary for dedicated data center upkeep The leasing option enables smaller enterprises to benefit from professional data center capabilities without incurring large capital expenditures.
  • A data center is a location where an organization's IT operations and equipment are centralized, as well as where data is stored, managed, and disseminated. Data centers hold a network's most crucial systems a are important to the day-to-day functioning of the network. As a result, corporations prioritize the security and dependability of data centers and associated information.
  • Although each data center is unique, it may typically be divided into two types: internet-facing data centers and business (or "internal") data centers. Internet-facing data centers often handle a small num of apps, are browser-based, and have a large number of unknown users. Enterprise data centers, on other hand, serve fewer users but host more applications ranging from off-the-shelf to bespoke applications.
  • Datacenter designs and needs can vary greatly. A data center designed for a cloud service provider, such as Amazon EC2, has facility, infrastructure, and security needs that differ dramatically from a wholly private data center, such as one designed for the Pentagon to secure sensitive data. 

GOVERNMENT INTEGRATED DATA CENTER

  • A data center is a centralized location for the storage, management, processing, and exchange of data that exists within a specific enterprise or a specialized facility. In general, data centers can be broken down into three types - Internet Datacenter (IDC), Storage area network (SAN), and Enterprise data center (EDC).
  • An Internet data center (IDC) is a facility that provides data and Internet services for other companies. GIDC falls in this phase.
  • A Storage Area Network (SAN) is a network of interconnected storage devices and data servers usually located within an enterprise data center or as an off-site facility offering leased storage space.
  •  An Enterprise data center (EDC) is the central processing facility for an enterprise's computer network

Features of GIDC

  • High-End Computing Infrastructure
  • Storage Area Network (SAN) High-Speed Local Area Network
  • Multi-Tier Security
  • High-Speed Internet Connectivity
  • 24*7*365 Help Desk
  • Multi-level redundant power back-up
  • Air Conditioning Management
  • Infrastructure System
  • Fire Detection & Control System

Infrastructure System

  • Air-Circulation System: HVAC (Heating, Ventilating, and Air Conditioning) 
  • Security: Biometric Access Control System, Card Reader Access Control System, CCTV
  • Facility Management System: Water Leakage Sensing
  • Disaster Prevention System: Firefighting

Electrical System

  • 200 KVA transformers (3 nos.) 
  • Main Power Switchboard
  • Emergency Generator: 400 KW
  •  UPS-Redundant 100 KVA, 120 KVA; Batteries: 620.

Facilities of GIDC

  • Information Technology System
  • Routers, Backbone Switches, etc. System
  • Integrated Network Management
  • Integrated Server Management System
  • Integrated Storage - 158 TB IPS, Web Application Firewall

Comments

Post a Comment

Popular posts from this blog

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

-
Image
a) A Snowflake Shema is shown in figure below: b) The specific OLAP operations to be performed: 1. Roll-up on course from course_id to department. 2. Roll-up on a student from student_id to university. 3. Dice on course, student with department ="CS" and university = "biguniversity" 4. Drill-down on a student from the university to student_name. c) N = 4 dimensions The cube will contain 54 = 625 cuboids.
Read more

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

-
Image
  b) The specific OLAP operations to be performed are: 1. Roll-up on date from date id to year. 2. Roll-up on spectator from spectator id to status. 3. Roll-up on location from location id to location name. 4. Roll-up on the game from game id to all. 5. Dice with status= “students”, location name= “GM Place”, and year=2004
Read more

Explain Parallel Efficiency of MapReduce.

-
Image
 PARALLEL EFFICIENCY OF MAP-REDUCE It is worth trying to figure out what is the parallel efficiency of MapReduce. Now let us assume that the data produced after the map phase is σ times the original data size D (σD), further, we assume that there are P processors which in turn perform map and reduce operations depending on which phase they are used in, so we do not have any wastage of processors. Also, the algorithm itself is assumed to do wD useful work, w is not necessarily a constant it could be D^2 or something like that, but the point is that there is some amount of useful work being done even if you have a single processor and that's wD. Now let us look at the overheads of doing the computation wD using MapReduce. After the map operation, instead of D data items, we have σD data items in P pieces, so each mapper writes data to their local disk. So, P there is some overhead associated with writing this data. Next, this data has to be read by each reducer before it can begin ...
Read more