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Smart Grids and Energy Storage Systems

Smart Grids and Energy Storage Systems: Powering the Future of Energy In today’s rapidly evolving energy landscape, the push towards sustainability, efficiency, and reliability is stronger than ever. Traditional power grids, though robust in their time, are no longer sufficient to meet the demands of a modern, digital, and environmentally conscious society. This is where smart grids and energy storage systems (ESS) come into play — revolutionizing how electricity is generated, distributed, and consumed. What is a Smart Grid? A smart grid is an advanced electrical network that uses digital communication, automation, and real-time monitoring to optimize the production, delivery, and consumption of electricity. Unlike conventional grids, which operate in a one-way flow (from generation to end-user), smart grids enable a two-way flow of information and energy. Key Features of Smart Grids: Real-time monitoring of power usage and quality. Automated fault detection and rapid restoration. Int...

Disk scheduling

Disk Scheduling

* As mentioned earlier, disk moved speeds are limited primarily by seek times and rotational latency. When many requests are to be processed there is also some inherent delay in waiting for other requests to be processed.
* Bandwidth is calculated by the amount of data transferred divided by the total amount of time from the first request being made to the last transfer being completed, (for a series of disk requests.)
* Both bandwidth and access time can be increased by processing requests in a good order.
* Disk requests include the disk address, memory address, number of sectors to moved,and whether the request is for reading or writing.

FCFS Scheduling
First-Come First-Serve is easy and basically fair, but not very efficient. Consider in the following order the wild change from cylinder 122 to 14 and then back to 124:

SSTF Scheduling
* Shortest Seek Time First scheduling is more systematic, but may lead to starvation if a constant stream of requests arrives for the same general area of the disk.
* SSTF decreases the total head of 236 cylinders movements, down from 640 required for the same set of requests under FCFS. Note, however that the distance could be decreased still further to 208 by starting with 37 and then 14 first before processing the rest of the requests.

SCAN Scheduling
The SCAN algorithm, a.k.a. the elevator algorithm rotates back and front from one end of the disk to the other, similarly to an elevator processing requests in a tall building.
* Under the SCAN algorithm, if a request enters just ahead of the moving head then it will be processed right away, but if it arrives just after the head has passed, then it will have to delays for the head to pass going the other way on the return trip. This leads to a fairly wide difference in access times which can be improved upon.
* Consider, for example, when the head extends the high end of the disk: Requests with high cylinder numbers just missed the passing head, which means they are all fairly recent requests, whereas requests with low numbers may have been delaying for a much longer time. Making the return scan from high to low then ends up processing recent requests first and making older requests delays that much longer.

C-SCAN Scheduling
The Circular-SCAN algorithm improves upon SCAN by treating all requests in a circular queue fashion - Once the head extends the end of the disk, it backs to the other end without processing any requests, and then begins again from the beginning of the disk:

LOOK Scheduling
LOOK scheduling increases upon SCAN by looking ahead at the queue of pending requests, and not moving the heads any farther towards the end of the disk than is required. The following diagram demonstrates the circular form of LOOK:
Selection of a Disk-Scheduling Algorithm
* With very low charges all algorithms are same, since there will normally only be one request to process at a time.
* For moderately larger loads, SSTF offers good performance than FCFS, but may lead to starvation when loads become heavy enough.
* For busier systems, SCAN and LOOK algorithms delete starvation problems.
* The actual optimal algorithm may be something even more difficult than those discussed here, but the incremental enhancements are generally not worth the additional overhead.
* Some increment to overall file system access times can be made by intelligent 
placement of directory and/or inode information. If those structures are placed in the middle of the disk instead of at the starting of the disk, then the maximum distance from those structures to data blocks is decreased to only half of the disk size. If those structures can be further issues and furthermore have their data blocks stored as close as possible to the corresponding directory structures, then that decrease still further 
the overall time to find the disk block numbers and then process the corresponding data blocks.
* On modern disks the rotational latency can be almost as significant as they seek time, however it is not within the OSes manage to account for that, because modern disks do not reveal their interior sector mapping schemes, ( particularly when bad blocks have been remapped to additional sectors. )
• Some disk producers give for disk scheduling algorithms directly on their disk controllers, ( which do know the actual geometry of the disk as well as any 
remapping ), so that if a series of requests are sent from the computer to the controller then those requests can be served in an proper order.
• Unfortunately there are some considerations that the OS must take into account that are far away the abilities of the on-board disk-scheduling algorithms, such as importance of some requests over others, or the require to process certain requests in a particular order. For this reason OSes may elect to spoon-feed requests to the disk controller one at a time in various situations.

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Abbreviations

No :1 Q. ECOSOC (UN) Ans. Economic and Social Commission No: 2 Q. ECM Ans. European Comman Market No : 3 Q. ECLA (UN) Ans. Economic Commission for Latin America No: 4 Q. ECE (UN) Ans. Economic Commission of Europe No: 5 Q. ECAFE (UN)  Ans. Economic Commission for Asia and the Far East No: 6 Q. CITU Ans. Centre of Indian Trade Union No: 7 Q. CIA Ans. Central Intelligence Agency No: 8 Q. CENTO Ans. Central Treaty Organization No: 9 Q. CBI Ans. Central Bureau of Investigation No: 10 Q. ASEAN Ans. Association of South - East Asian Nations No: 11 Q. AITUC Ans. All India Trade Union Congress No: 12 Q. AICC Ans. All India Congress Committee No: 13 Q. ADB Ans. Asian Development Bank No: 14 Q. EDC Ans. European Defence Community No: 15 Q. EEC Ans. European Economic Community No: 16 Q. FAO Ans. Food and Agriculture Organization No: 17 Q. FBI Ans. Federal Bureau of Investigation No: 18 Q. GATT Ans. General Agreement on Tariff and Trade No: 19 Q. GNLF Ans. Gorkha National Liberation Front No: ...

Operations on data structures

OPERATIONS ON DATA STRUCTURES This section discusses the different operations that can be execute on the different data structures before mentioned. Traversing It means to process each data item exactly once so that it can be processed. For example, to print the names of all the employees in a office. Searching It is used to detect the location of one or more data items that satisfy the given constraint. Such a data item may or may not be present in the given group of data items. For example, to find the names of all the students who secured 100 marks in mathematics. Inserting It is used to add new data items to the given list of data items. For example, to add the details of a new student who has lately joined the course. Deleting It means to delete a particular data item from the given collection of data items. For example, to delete the name of a employee who has left the office. Sorting Data items can be ordered in some order like ascending order or descending order depending ...

Points to Remember

• A data structure is a particular way of storing and organizing data either in computer’s memory or on the disk storage so that it can be used efficiently. • There are two types of data structures: primitive and non-primitive data structures. Primitive data structures are the fundamental data types which  are supported by a programming language. Non-primitive data structures are those data structures which are created using primitive data structures. • Non-primitive data structures can further be classified into two categories: linear and non-linear data structures.  • If the elements of a data structure are stored in a linear or sequential order, then it is a linear data structure. However, if the elements of a data structure are not stored in sequential order, then it is a non-linear data structure.  • An array is a collection of similar data elements which are stored in consecutive memory locations. • A linked list is a linear data structure consisting of a grou...