Presentation on theme: "Capacity Planning IACT 918 July 2004 Gene Awyzio SITACS University of Wollongong."— Presentation transcript:
Capacity Planning IACT 918 July 2004 Gene Awyzio SITACS University of Wollongong
2 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
3 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
4 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
5 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
6 The Importance of Planning …or more specifically: Given –Node locations –Edge locations –Traffic requirements between 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
7 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)
8 Working It Out Modern network based applications dont 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)
9 Working It Out This means that all the simplifying assumptions are no longer valid Also, –potential savings can be achieved by installing excess capacity to meet future requirements
10 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, 1.facilities, 2.equipment and 3.evaluation
11 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)
12 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)
13 1.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.
14 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
15 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
16 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
17 1. Facilities Utilization Time There is a knee often at around 60~70% 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
18 Congestion collapse 1. Facilities Packets sent Packets delivered Maximum carrying capacity of subnet perfect desirable congested
19 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 acceptable otherwise, the utilization ceiling must be reduced, by installing larger capacity lines, or more lines.
20 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
21 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.
22 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
23 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