Shirish Koirala

Queuing system is described by its calling population, queue, server, entity (customers), nature of arrival, service mechanism, system capacity and queuing discipline. Entity comes from calling population and join the queue. If any of the server is idle, entity on the queue moves to the server. Otherwise, if all servers are busy, entity waits on the queue, and as soon as server state changes to ideal, entity moves to the server. After the entity is served, the entity goes back to the calling population. The time between the arrivals of each entity is known as inter arrival time. The time taken by the server to serve an entity is known as service time.

Queuing behavior: It refers to action of customers while in a queue waiting for a service to begin. In some situations, there is possibility that incoming customers will Back (leave when they see that the line is too long), Renege (leave after being in line when they see that line is moving too slowly) or Jockey (move from one line to another if they think have chosen a slow line). Queuing Discipline : It is the logical ordering of the customers in a queue and determines which customers will be chosen for service when the server become free. Common queuing discipline include:  First In First Out (FIFO)  Last In First Out (LIFO)  Service In Random Order (SIRO)  Shortest Processing Time First (SPTF)  Service According To Priority (SATP). In some jobs, queue discipline are based on due date and on expected processing time for the job.

Common Name IEEE Standard Physical Standard Max. Speed Medium Used Max. Span/Area Ethernet 802.3 10-Base-5 10Mbps Coaxial-Thick-net 200m Ethernet 802.3a 10-Base-2 10Mbps Coaxial-Thick-net 185mm Ethernet 802.3i 10-Base-T 10Mbps Twisted Pair cable 100m Ethernet 802.3j 10-Base-F 10Mbps Fiber optic cable 500m Fast Ethernet 802.3u 100-Base-Tx 100Mbps Twisted Pair 100m Fast Ethernet 802.3u 100-Base-Fx 100Mbps Fiber (Multimode) 2km Fast Ethernet 802.3u 100-Base-Sx 100Mbps Fiber (Multimode) 500m Gigabit Ethernet 802.3ab 1000-Base-T 1000Mbps Twisted Pai

Best case complexity gives the lower bound on the running time of the algorithm for any instance of inputs. This indicates that the algorithm can never have lower running time that best case for particular class problems. Worst case complexity gives the upper bound in the running time of the algorithm for all the instances of inputs this insures that no input can overcome the running time limit processed by worst case complexity. Average case complexity gives average number of steps required on any instance of inputs. For example: the best case for a simple sorting algorithm would be providing data that is already sorted, worst case for the same algorithm would be providing input that is sorted in reverse order and average case would be  input that is half sorted. This varies according the algorithm as this would not be the case for all sorting algorithms

An algorithm is a finite set of computational instructions, each instruction are can be  executed in finite time, to perform computational or problem solving by giving some value or set of values as input to produce some values or set of values as output. Algorithms are not dependent on a particular machine, programming language or compilers i.e. algorithms run in same manner everywhere. So the algorithm is a mathematical object where the algorithms are assumed to be run under machine with unlimited capacity.

Physical models are of two types, static and dynamic. Static physical model is scaled down model of a system which does not change with time. An architect before constructing a building, makes a scaled down model of the building, which reflects all its rooms, outer design and other important features. This is an example of static physical model. Similarly for conducting trials in water, we make small water tanks, which are the replica of sea, and fire small scaled down shells in them. This tank can be treated as a static model of sea. Dynamic physical model are ones which changes with time or which are function of time. In wind tunnel, small aircraft models (static models) are kept and the air is blown over them with different velocities and pressure profiles are measured with the help of transductions embedded in the model. Here wind changes with time and is the example of dynamic physical model.