Capacity Planning

Capacity Planning IACT 918 July 2004 Gene Awyzio SITACS University of Wollongong

The Importance of Planning • Network capacity planning lies at the heart of all network management functions • The design of networks to route data from one location to another with the least cost is of great concern to network designers

The Importance of Planning • The objective of network designers is to minimise the cost of installing and maintaining the network • These problems are complicated by the need to consider many factors such as • Cable capacity • End-to-end blocking probabilities • Delay and reliability requirements

The Importance of Planning • The process of designing a network requires that many variables are determined simultaneously • In designing and upgrading a network, it is necessary to simultaneously select • Node location • Links connecting backbone nodes • Links between end users

The Importance of Planning • Mathematically we can say that • The objective of designing and maintaining a network is to: • Minimise the cost of installation and maintenance • Whilst meeting some given performance criteria

Given Node locations Edge locations Traffic requirementsbetween node pairs Cost of transmission capacity Cost of node installation Minimise Total network costs Determine Network topology Edge capacities Routing policy Subject to Performance constraints Capacity constraints Reliability constraints The Importance of Planning…or more specifically:

Working It Out • These models generally end up being combinatorially explosive or NP complete • NP = Non-deterministic Polynomial-time • To simplify the problem of solving these models several assumptions are used • Packet (data) arrival is independent of other traffic (Poissonian arrival) • Packet size is independent of other traffic (exponential packet size)

Working It Out • Modern network based applications don’t follow these assumptions • Most applications have a real time component • These types of applications tend to create a traffic stream that creates packets: • At fixed time intervals (deterministic) • Have a fixed size (deterministic)

Working It Out • This means that all the simplifying assumptions are no longer valid • Also, • potential savings can be achieved by installing excess capacity to meet future requirements

Developing the Network Capacity Plan • We start with a knowledge of the present network and its traffic loads etc, and our prediction of the future demands of the organisation • We will develop the network capacity plan in three steps, • facilities, • equipment and • evaluation

1. Facilities • “A facility is a transmission path between two or more locations, not including terminating or signalling equipment. The addition of terminating equipment would produce either a channel, a central office line, or a trunk.” (Terplan P 556)

1. Facilities • A facility has a theoretical maximum capacity which is given by the bandwidth • In practice it is found to be impossible to use all the bandwidth because of: • Overheads • Downtime • Utilisation ceiling (depends on burstiness)

Facilities • Capacity of facilities: • The utilization level beyond which the facility is unable to perform work in a timely manner within service-level limits • The facility has reached its capacity when when its utilization has attained a level at which targeted service levels cannot be met.

1. Facilities • Utilization ceiling: • The theoretical capacity of the facilities • Identified by the speed of the resource • How many bits can be transmitted per second • Bits per second on average • Bits per second at peak loading times • There must be no compromise on service-levels for the average load • Some violations at peak load may be tolerated • Depends on the patterns of usage and the culture of the organisation

1. Facilities • Terplan shows a graph as follows: • We will run out of capacity when we reach the usable limit. Then we are in trouble on this facility Reserve

1. Facilities • Utilization • = arrival rate / service time This yields a ratio (sometimes expressed as a percentage) >1 = unstable, queue will just grow bigger <1 = stable

1. Facilities • As utilization increases in a stable system ( <1), if the system were purely deterministic, then time would increase linearly • But as this assumption does not hold, there is a ‘knee’ point beyond which delays increase idealized Time There is a ‘knee’ often at around 60~70% Utilization 

1. Facilities • Congestion collapse perfect Maximum carrying capacity of subnet desirable Packets delivered congested Packets sent

1. Facilities • Response time = service time + waiting time • Service time = transmission time + poll transmit time + select transmit time + poll/select wait times • Waiting time = (service time x utilization) / [2 x (1 – utilization)] • If response time < response time objective, then the utilization ceiling is acceptableotherwise, the utilization ceiling must be reduced, by installing larger capacity lines, or more lines.

1. Facilities • For practical purposes, we can estimate the effective capacity as about 60-70% of the bandwidth • As the traffic approaches this maximum, the performance drops. Response time and packet loss increase • This effective capacity is the upper limit available to the network, and we can use our estimates of future traffic to predict when we will run out of capacity

2. Equipment • Equipment is everything not included in the facility • Equipment capacity can be computed in the same way as facility capacity, using overhead, downtime and utilisation ceiling.

3. Evaluation • When major upgrades are considered, there is always a choice among several alternatives • The different possibilities must be developed and evaluated • Development requires thinking of the alternatives, discussion among those involved and may include brainstorming

3. Evaluation • Evaluation requires computer modelling or simulation • It can be done on a spreadsheet or a simulation package designed for the purpose(eg Arena, nm) • The value of any of these exercises depends on the accuracy of the original information on present and future loads

Capacity Planning