UNIT 1
Telecommunication Switching & Traffic
In message switching there is not a dedicated path between the sender and receiver. In message switching, each message is treated as an independent unit and have its own source and destination addresses.
(i) It is different from circuit switching as it has no dedicated path.
(ii) It is also different from packet switching as complete message is send without divided into packets.
(iii) Complete message is transmitted from sending device to the receiving device through the communication link.
(iv) Message switching technique is also called as store and forward technique because each intermediate device receive the message from previous device and store it, and forward it to the rent device when next device is ready to accept it.
Fig.: Message Switching Technique
Advantages
- Priorities can be assigned to messages to be switched, that provide the efficient traffic management.
- Store and forward mechanism reduce the traffic congestion in network, because the stored message is not forwarded till than the channel became available.
- Message switching provides the synchronous communication occurs the time zones.
Disadvantages
- Store and forward also has the disadvantage of delay, because of delay it cannot be the best option for real time applications such as voice and video.
- Requirement of large storing capacity for the intermediate device as device has to store the message before forwarding to the next device on free path.
- Circuit switching has been used so long for both voice and data communications.
- It can handle the digital data also, but it provide as inefficient.
- Circuit Switching provides the communication via a dedicated path between two stations.
- The network connection allows the signals to flow between the two users. The end to end connection is maintained for the whole duration of the call.
- The most common example of circuit switching is the telephone network.
- In telephone network setting up of a connection is required before transfer of the information from one place to another or sender to receiver.
- The circuit switching takes place at the physical layer where before starting communication in first phase the resource are reserved for further communication such as the channels, switch, buffers input / output parts.
- In circuit switching data gets transferred continuously. The switches routes the data on the basis of their occupied frequency band (FDM) or time slot (TDM)
- Three phases are involves in the communication via circuit switching :
1) Circuit Establishment (Set-up Phase)
2) Data Transfer Phase
3) Circuit Disconnect (Tear-down Phase)
Fig: Circuit Switch Network
In Fig. 1.12.1 - 1, 2, 3 are called as switching nodes, they are used to connect one another and pass the information.
1) Circuit Establishment
- Before transmitting the signals, end-to-end connection is established.
- As given in the example if the communication is in between A to F then first A establish the connection from A to node 1 then to node 2, then to node 3 and at last communication is established with D.
- FDM and TDM techniques are used for node to node links.
- To complete and check the connection, a test is conducted to determine if F is busy or is ready to accept the connection to A.
2) Data Transfer
- Now the information can be transferred from A to F through the network.
- The transmitted data can be analog voice, digitized voice; binary data depends on the nature of the used network.
- Generally full duplex connections are used.
3) Circuit Disconnect (tear down phase)
- After some time of the data transfer, the connection between sender and receiver is terminated. In this usually one of the two stations is involved.
- The dedicated resources are deallocated after the tear down phase.
Advantages
- Circuit Switching is connection oriented so that provides a guaranteed data rate.
- In circuit switching, once the connection is established, the network is effectively transparent to the users.
- As data is transmitted at a fixed data rate, so no delay problem, only propagation delay is there through the transmission links.
Disadvantages
- Reservation of the resource before transmission, delays the transmission of any other data even the channel is free.
- Bandwidth Requirement is more due to dedicated channel.
- To establish the connection, it takes long time.
- Example : Public telephone network
The switching systems in the early stages were operated manually. The connections were made by the operators at the telephone exchanges in order to establish a connection. To minimize the disadvantages of manual operation, automatic switching systems were introduced.
The Electronic Switching systems are operated with the help of a processor or a computer which control the switching timings. The instructions are programmed and stored on a processor or computer that control the operations. This method of storing the programs on a processor or computer is called the Stored Program Control (SPC) technology. New facilities can be added to a SPC system by changing the control program.
The switching scheme used by the electronic switching systems may be either Space Division Switching or Time Division Switching. In space division switching, a dedicated path is established between the calling and the called subscribers for the entire duration of the call. In time division switching, sampled values of speech signals are transferred at fixed intervals.
The time division switching may be analog or digital. In analog switching, the sampled voltage levels are transmitted as they are. However, in binary switching, they are binary coded and transmitted. If the coded values are transferred during the same time interval from input to output, the technique is called Space Switching. If the values are stored and transferred to the output at a time interval, the technique is called Time Switching. A time division digital switch may also be designed by using a combination of space and time switching techniques.
- The most common switching function involves direct connections between subscriber loops at an end office or between station loops at a PBX.
- These connections inherently require setting up a path through the switch from the originating loop to a specific terminating loop.
- Each loop must be accessible to every other loop. This level of switching is sometimes referred to as line switching.
- Transit connections require setting up a path from a specific incoming (originating) line to an outgoing line or trunk group. Normally, more than one outgoing circuit is acceptable.
SPACE DIVISION SWITCHING
This switching matrix can be used to connect any one of Ninlets to any one of M outlets. If the inlets and outlets are connected to two-wire circuits, only one crosspoint per connection is required.1 Rectangular crosspoint arrays are designed to provide intergroup (transit) connections only, that is, from an inlet group to an outlet group. Applications for this type of an operation occur in the following: 1. Remote concentrators 2. Call distributors 3. Portion of a PBX or end office switch that provides transit switching 4. Single stages in multiple-stage switches
TIME DIVISION SWITCHING
Time division switching is equally applicable to either analog or digital signals. At one time, analog time division switching was attractive when interfacing to analog transmission facilities, since the signals are only sampled and not digitally encoded. However, large analog time division switches had the same limitations as do analog time division transmission links: the PAM samples are particularly vulnerable to noise, distortion, and crosstalk. Thus, large electronic switching matrices have always incorporated the cost of digitizing PAM samples to maintain end-to-end signal quality. The low cost of codecs and the prevalence of digital trunk interconnections imply that analog switching is now used in only the smallest of switching systems (e.g., electronic key systems).
The product of the calling rate and the average holding time is defined as the Traffic Intensity. The continuous sixty-minute period during which the traffic intensity is high is the Busy Hour. When the traffic exceeds the limit to which the switching system is designed, a subscriber experiences blocking.
The traffic in a telecommunication network is measured by an internationally accepted unit of traffic intensity known as Erlang (E). A switching resource is said to carry one Erlang of traffic if it is continuously occupied through a given period of observation.
- The traffic in a telecommunication network is measured by an internationally accepted unit of traffic intensity known as Erlang (E).
- A switching resource is said to carry one Erlang of traffic if it is continuously occupied through a given period of observation.
a) In a medium of transmission that is a bandwidth of 1 G bps internet traffic flowing at 0.6 G bps, the traffic intensity in the transmission medium is = 0.6 G bps / 1 G bps = 0.6 Erlang.
b) On a web server that can serve 1000 hits per hour, there were 400 hits per hour, the traffic intensity on this web server is = 400 hits per hour / 1000 hits per hour = 0.4 Erlang.
c) On a call center that is able to serve customers as many as 500 calls per minute there are 230 calls per minute, then the traffic intensity in the call center is a call per minute = 230 calls per minute / 500 calls per minute = 0.46 Erlang.
Numerical:
Calculate the intensity of traffic (using Erlang unit) on the 3 problems below:
a) A radio-link with a capacity of 6 channels, with measurements for 30 minutes, every channel average holded for 15 minutes.
b) A measurement of the digital switch over for 25 minutes, processed about 25,000 calls, which have a mean holding time = 3 minutes ( = 3 minutes/call)
c) A web server has a service rate = 1 M bit per seconds, if in a 10-minute measurements received 600 requests, each request requires an average of 100 packet data @ 1,000 bits per packet.
Solution :
Final calculation should be dimensionless, because the requested unit is erlang !!
a) Traffic Intensity = A = 6 channel x (15 minutes per channel / 30 minutes) = 3 erlang.
b) Traffic Intensity = A = 25,000 calls x 3 minutes per call / 25 minutes = 3,000 erlang.
c) Traffic Intensity = A = (600 requests x 100 packets per request x 1,000 bits per packet) / (1 M bits per second x (10 minutes x 60 seconds per minute) = 0.1 erlang
The service of incoming calls depends on the number of lines. If number of lines equal to the number of subscribers, there is no question of traffic analysis. But it is not only uneconomical but not possible also. So, if the incoming calls finds all available lines busy, the call is said to be blocked. The blocked calls can be handled in two ways.
The type of system by which a blocked call is simply refused and is lost is called loss system. Most notably, traditional analog telephone systems simply block calls from entering the system, if no line available. Modern telephone networks can statistically multiplex calls or even packetize for lower blocking at the cost of delay. In the case of data networks, if dedicated buffer and lines are not available, they block calls from entering the system.
In the second type of system, a blocked call remains in the system and waits for a free line. This type of system is known as delay system.
Spectral efficiency as the traffic capacity unit divided by the product of bandwidth and surface area element, and is dependent on the number of radio channels per cell and the cluster size (number of cells in a group of cells):
Where Nc is the number of channels per cell, BW is the system bandwidth, and Ac is Area of cell.
The type of system by which a blocked call is simply refused and is lost is called loss system. Most notably, traditional analog telephone systems simply block calls from entering the system, if no line available. Modern telephone networks can statistically multiplex calls or even packetize for lower blocking at the cost of delay. In the case of data networks, if dedicated buffer and lines are not available, they block calls from entering the system.
The Erlang loss system may be defined by the following specifications.
1. The arrival process of calls is assumed to be Poisson with a rate of X calls per hour.
2. The holding times are assumed to be mutually independent and identically distributed random variables following an exponential distribution with 1/|u seconds.
3. Calls are served in the order of arrival.
There are three models of loss systems.
They are :
1. Lost calls cleared (LCC)
2. Lost calls returned (LCR)
3. Lost calls held (LCH)
The basic queueing model is shown in figure. It can be used to model, e.g., machines or operators processing orders or communication equipment processing information.
• The arrival process of customers. Usually we assume that the interarrival times are independent and have a common distribution. In many practical situations customers arrive according to a Poisson stream (i.e. exponential interarrival times). Customers may arrive one by one, or in batches. An example of batch arrivals is the customs office at the border where travel documents of bus passengers have to be checked.
The behaviour of customers. Customers may be patient and willing to wait (for a long time). Or customers may be impatient and leave after a while. For example, in call centers, customers will hang up when they have to wait too long before an operator is available, and they possibly try again after a while.
• The service times. Usually we assume that the service times are independent and identically distributed, and that they are independent of the interarrival times. For example, the service times can be deterministic or exponentially distributed. It can also occur that service times are dependent of the queue length. For example, the processing rates of the machines in a production system can be increased once the number of jobs waiting to be processed becomes too large.
• The service discipline. Customers can be served one by one or in batches. We have many possibilities for the order in which they enter service. We mention: – first come first served, i.e. in order of arrival; – random order; – last come first served (e.g. In a computer stack or a shunt buffer in a production line); – priorities (e.g. Rush orders first, shortest processing time first); – processor sharing (in computers that equally divide their processing power over all jobs in the system).
• The service capacity. There may be a single server or a group of servers helping the customers.
• The waiting room. There can be limitations with respect to the number of customers in the system. For example, in a data communication network, only finitely many cells can be buffered in a switch. The determination of good buffer sizes is an important issue in the design of these networks.
Kendall introduced a shorthand notation to characterize a range of these queueing models. It is a three-part code a/b/c. The first letter specifies the interarrival time distribution and the second one the service time distribution. For example, for a general distribution the letter G is used, M for the exponential distribution (M stands for Memoryless) and D for deterministic times. The third and last letter specifies the number of servers. Some examples are M/M/1, M/M/c, M/G/1, G/M/1 and M/D/1. The notation can be extended with an extra letter to cover other queueing models. For example, a system with exponential interarrival and service times, one server and having waiting room only for N customers (including the one in service) is abbreviated by the four letter code M/M/1/N.
The Erlang distribution (sometimes called the Erlang-k distribution) was developed by A.K. Erlang to find the number of phone calls which can be made simultaneously to switching station operators. Erlang was a telecommunications engineer for the Copehagen Telephone Company; his formulas for loss and waiting time were used by many telephone companies, including the British Post Office. Erlang’s distribution has since been expanded for use in queuing theory, the mathematical study of waiting in lines. It is also used in stochastic processes and in mathematical biology.
The Erlang distribution is a specific case of the Gamma distribution. It is defined by two parameters, k and &u;, where:
- k is the shape parameter. This must be a positive integer (an integer is a whole number without a fractional part). In the Gamma distribution, k can be any real number, including fractions.
- μ is the scale parameter. Must be a positive real number (a real number is any number found on the number line, including fractions).
The probability distribution function of the Erlang distribution is:
The factorial(!) in the denominator is the reason why the distribution is only defined for positive numbers. An equivalent form of the pdf for this distribution includes λ, a measure of rate, which is related to μ in the following way:
μ = 1/λ.
λ represents the number of items or calls expected in a given amount of time.
- The queuing delay defined as the time taken by a data packet to reach it sink node after it is generated.
- It is the expectation of the queuing delay over all packets and all possible sensor network topologies.
- In these analysis takes into account, the queuing delay at the source and intermediate sensor nodes. The packets are assumed to have a fixed size and random arrival process. And characterized how the average queuing delay and maximum achievable throughput vary with the degree of locality of congested area.
- Evaluating the mean and the moment of service time over a single hop by taking into account the back-off and collision avoidance mechanisms of IEEE 802.11 MAC. And using the diffusion approximation method for solving open queuing networks to evaluate the closed form equations for the average queuing packet delay.
- Using the average service time of the nodes, to obtain an expression for the maximum achievable throughput.
- The analytical results obtained from the queuing network, analysis have discussed about is concerning similarities and difference from the queuing network, analysis are discussed well established information-theoretic result on throughput and delay scaling laws in sensor networks.
- And perform extensive simulations and verifying the analytical results, nearly matching the results obtained from simulations.
- The analytical equations for the performance measures such as average queuing delay, packet 76 loss probability, throughput, the average number of hops and expansion method for models with finite-buffer nodes derived using the queuing network analyzer.
In some queueing process, there is limited waiting space, So that when the queue reaches a certain length, further customers are not allowed to join the queue, until the space becomes available after service completion. Thus there is a finite limit to the maximum system size.
If any number of customers are allowed to join the queue, we may say that the capacity is infinite.
Customers Behaviour:
A customer generally behaves in four ways.
(i) Balking – A customer may leave the queue, if there is no waiting space.
(ii) Reneging – This occurs when the waiting customers leave the queue due to inpatients.
(iii) Priorities – In certain applications some customers are served before others, regardless of their order of arrival.
(iv) Jockeying – The customer may jump one waiting line to another.
Kendall’s Notation:
The assumptions made for the simples queueing model is
(a|b|c): (d|e)
Where a = Probability distribution of the inter-arrival time.
b = Probability distribution of the service time.
c = Number of services in the system.
d = Maximum number of customers allowed in the system.
e = Queue discipline.
Notations and Symbols:
The following notations and symbols will be used in connection with the queueing systems.
n = Total number of customers in the system, both waiting and in service.
= Average number of customers arriving per unit time.
= Average number of customers being served per unit time.
C = Number of parallel service channels (servers).
L s (or) E(n) = Expected or average number of customers in the system, both waiting and in service [L s= E (Ns) ]
Lq (or) E(M) = Average or expected number of customer in the queue (excluding those who are receiving service) Lq = E(Nq)
Ws (Or) E ( Ws ) = Average or expected waiting time of a customer in the system both waiting and in service (Including the service time).
Wq (Or) E ( Wq ) = Average or expected waiting time of a customer in the queue. (Excluding service time)
P n (t) = Probability that there are n customers in the system at any time t (both waiting and in service) assuming that the system has started its operation at time zero.
= Traffic intensity or utilization factor, which represents the proportion of time the servers are busy = /
P(n) = Steady state probability of having n customers in the system.
An M/M/1 queue is a stochastic process whose state space is the set {0,1,2,3,...} where the value corresponds to the number of customers in the system, including any currently in service.
- Arrivals occur at rate λ according to a Poisson process and move the process from state i to i + 1.
- Service times have an exponential distribution with rate parameter μ in the M/M/1 queue, where 1/μ is the mean service time.
- A single server serves customers one at a time from the front of the queue, according to a first-come, first-served discipline. When the service is complete the customer leaves the queue and the number of customers in the system reduces by one.
- The buffer is of infinite size, so there is no limit on the number of customers it can contain.
The model can be described as a continuous time Markov chain with transition rate matrix
On the state space {0,1,2,3,...}. This is the same continuous time Markov chain as in a birth–death process. The state space diagram for this chain is as below.
- To evaluate the local queuing delay at the final stage of the concentration tree, we may replace the tree by an "equivalent tandem queue" carrying the same traffic streams with the same service times, provided we add a jitter delay generated by the mutual independence of the various branches of the concentration tree.
- This jitter delay takes into account the impact of the variations in the local arrival order, since the equivalent tandem queue corresponds to a local arrival order identical to the overall arrival order at the network input.
- In the case of branches with unequal lengths, we will define later the parameter no to represent the number of stages of the equivalent tandem queue.
- In general, this equivalence property is not true when successive service times (of the same customer) are different and varying, or are mutually independent.
- However, in the case of heavily loaded networks, the property does remain true if it may avoid breaking up the busy periods, since there is just one busy period of the second stage server during the interval (Xn,, Xn2).
- The size and the length of this busy period is therefore unchanged due to %he extended delays at the second stage, which tends to cause busy periods to accumulate.
References
1. Theodore S Rappaport, “Wireless Communications Principles and Practice” Second Edition, Pearson Education
2. John C. Bellamy, “Digital Telephony”, Third Edition; Wiley Publications
3. ThiagarajanVishwanathan, “Telecommunication Switching Systems and Networks”; PHI Publications
4. Wayne Tomasi, “Electronic Communications Systems”; 5th Edition; Pearson Education
5. Vijay K Garg, Joseph E Wilkes, “Principles and Applications of GSM” Pearson Education
6. Vijay K Garg, Joseph E Wilkes, “IS-95CDMA and CDMA 2000 Cellular/PCS Systems Implementation” Pearson Education
7. Mischa Schwartz, “Mobile Wireless Communications”, Cambridge University Press
