As an ex military satellite communications engineer I certainly remember working with spread spectrum modulation and also frequency hopping technology in the 1980's. Wireless Local Area Networking technology today exploits a technology which was thitherto mostly hidden inside this shadowy domain of military communications and radar. This technology comprises a collection of ideas which are termed Spread Spectrum Techniques (SST). Spread Spectrum techniques have some powerful properties which make them an excellent candidate for networking applications. To better understand why, we will take a closer look at this fascinating area, and its implications for networking.

EIGRP (Enhanced Interior Gateway Routing Protocol) is a network protocol that lets routers exchange information more efficiently than was the case with older routing protocols. EIGRP which is a proprietary protocol evolved from IGRP (Interior Gateway Routing Protocol) and routers using either EIGRP and IGRP can interoperate because the metric (criteria used for selecting a route) used with one protocol can be translated into the metrics of the other protocol. It is this metric which we will examine in more detail.

Using EIGRP, a router keeps a copy of its neighbour’s routing tables. If it can’t find a route to a destination in one of these tables, it queries its neighbours for a route and they in turn query their neighbours until a route is found. When a routing table entry changes in one of the routers, it notifies its neighbours of the change. To keep all routers aware of the state of neighbours, each router sends out a periodic “hello” packet. A router from which no “hello” packet has been received in a certain period of time is assumed to be inoperative.

EIGRP uses the Diffusing-Update Algorithm (DUAL) to determine the most efficient (least cost) route to a destination. A DUAL finite state machine contains decision information used by the algorithm to determine the least-cost route (which considers distance and whether a destination path is loop-free).

The Diffusing Update Algorithm (DUAL) is a modification of the way distance-vector routing typically works that allows the router to identify loop free failover paths.  This concept is easier to grasp if you imagine it geographically. Consider the map of the UK midlands shown in Figure1. The numbers show approximate travel distance, in miles. Imagine that you live in Glasgow. From Glasgow, you need to determine the best path to Hull. Imagine that each of Glasgow’s neighbours advertises a path to Hull. Each neighbour advertises its cost (travel distance) to get to Hull. The cost from the neighbour to the destination is called the advertised distance. The cost from Glasgow itself is called the feasible distance.
In this example, Newcastle reports that if Glasgow routed to Hull through Newcastle, the total cost (feasible distance) is 302 miles, and that the remaining cost once the traffic gets to Newcastle is only 141 miles. Table1 shows distances reported from Glasgow to Hull going through each of Glasgow’s neighbours.

Glasgow will select the route with the lowest feasible distance which is the path through Newcastle.

If the Glasgow-Newcastle road were to be closed, Glasgow knows it may fail over to Carlisle without creating a loop. Notice that the distance from Carlisle to Hull (211 miles) is less than the distance from Glasgow to Hull (302 miles). Because Carlisle is closer to Hull, routing through Hull does not involve driving to Carlisle and then driving back to Glasgow (as it would for Ayr). Carlisle is a guaranteed loop free path.

The idea that a path through a neighbour is loop free if the neighbour is closer is called the feasibility requirement and can be restated as "using a path where the neighbour's advertised distance is less than our feasible distance will not result in a loop."

The neighbour with the best path is referred to as the successor. Neighbours that meet the feasibility requirement are called feasible successors. In emergencies, EIGRP understands that using feasible successors will not cause a routing loop and instantly switches to the backup paths.

Notice that Ayr is not a feasible successor. Ayr's AD (337) is higher than Newcastle's FD (302). For all we know, driving to Hull through Ayr involves driving from Glasgow to Ayr, then turning around and driving back to Glasgow before continuing on to Hull (in fact, it does). Ayr will still be queried if the best path is lost and no feasible successors are available because potentially there could be a path that way; however, paths that do not
meet the feasibility requirement will not be inserted into the routing table without careful consideration.

EIGRP uses a sophisticated metric that considers bandwidth, load, reliability and delay. That metric is:

[latex]256, *, left(K_1, *, bandwidth ,+, dfrac {K_2 ,*, bandwidth}{256 - load}, +, K_3 ,*, delayright), *,dfrac {K_5}{reliability ,+, K_4}[/latex]

Although this equation looks intimidating, a little work will help you understand the maths and the impact the metric has on route selection.

You first need to understand that EIGRP selects path based on the fastest path. To do that it uses K-values to balance bandwidth and delay. The K-values are constants that are used to adjust the relative contribution of the various parameters to the total metric. In other words, if you wanted delay to be much more relatively important than bandwidth, you might set K3 to a much larger number.

You next need to understand the variables:

• Bandwidth—Bandwidth is defined as (100 000 000 / slowest link in the path) kbps. Because routing protocols select the lowest metric, inverting the bandwidth (using it as the divisor) makes faster paths have lower costs.

 

• Load and reliability—Load and reliability are 8-bit calculated values based on the performance of the link. Both are multiplied by a zero K-value, so neither is used.

 

• Delay—Delay is a constant value on every interface type, and is stored in terms of microseconds. For example, serial links have a delay of 20,000 microseconds and Ethernet lines have a delay of 1000 microseconds. EIGRP uses the sum of all delays along the path, in tens of microseconds.

By default, K1=K3=1 and K2=K4=K5=0. Those who followed the maths will note that when K5=0 the metric is always zero. Because this is not useful, EIGRP simply ignores everything outside the parentheses. Therefore, given the default K-values the equation becomes:

[latex]256, *, left(1, *, bandwidth ,+, dfrac {0 ,*, bandwidth}{256 - load}, +, 1 ,*, delayright), *,dfrac {0}{reliability ,+, 0}[/latex]

Substituting the earlier description of variables, the equation becomes 100,000,000 divided by the chokepoint bandwidth plus the sum of the delays:

[latex]256, *, left(dfrac {10^7}{min(bandwidth)}, +,sum,dfrac {delays}{10}right)[/latex]

As a final note, it is important to remember that routers running EIGRP will not become neighbours unless they share K-values. That said however you really should not change the K-values from the default without a compelling reason.

Ask your average person what a Yagi antenna is and they will probably look at you with a puzzled expression. The fact is however that everybody in the UK has probably seen a Yagi antenna and in all likelihood used one at some point.

Example of a Yagi TV aerial.


The Yagi antenna was invented by two Japanese researchers in 1926, namely Hidetsugu Yagi and Shintaro Uda.
It is more correctly called the Yagi-Uda antenna however Mr Uda seems to have slipped off the credits somewhat.
It is an example of a subtype of antenna known as the "beam antenna" but having established that its on almost every roof in the UK, why does it interest us at Rustyice Solutions?

In recent years, telecommunications has gone through a revolution with mobile communications becoming the greatest driving force behind this. Whether you like it or not all mobile communication and by definition all radio communication requires an antenna for reception and transmission of the signal. This antenna has largely become hidden from the view of the consumer with form and function of equipments dictating that an antenna can not be visible from the outside in most equipments but they are still there and play a fundamental part in everything that we do in the mobile communications world. So what does the ugly old rooftop TV antenna have to do with todays sleek 21st century devices you may ask?

'Quite a lot' is the answer. First, lets look at the technicals of the Yagi antenna itself.




The Yagi antenna is usually made up of a single driven (dipole) elelment and a reflector along with a number of parasitic elements whose size and spacing is determined by the frequencies which one wishes to receive or transmit. The size of the dipole is usually half of the wavelength (?) of the centre frequency or, if a folded dipole is used, the total length of the conductor is equal to almost 1 x ?. It is directional along the axis perpendicular to the dipole in the plane of the elements, from the reflector toward the driven (dipole) element and the parasitic elements which are also known as directors. Typical spacings between elements vary from about 1/10 to 1/4 of a wavelength, depending on the specific design and performance requirements. The lengths of the directors are smaller than that of the driven element, which is smaller than that of the reflector(s) according to an elaborate design procedure. These elements are usually parallel in one plane, supported on a single crossbar known as a boom.




Many of the higher end wireless networking manufacturers use emulated yagi antennas in their products today however we are sure you will agree that the coolest gizmo to get yourself a wifi signal where everybody else just simply can and will not be able to connect is this example of antenna technology at its finest over there on the left. In all, we believe, a perfect example of how technology might surge ahead at great speed every day but there really is no escape from good old fashioned antenna theory when you want to get yourself connected on the move.

At Rustyice Solutions, we have many shared years of experience in the field of HF, VHF, UHF and even SHF radio communications. If you or your business needs help getting connected on the fringes of reasonable reception via off the shelf products why not give us a call. We are sure we will be able to bring our considerable experience to bear in getting you connected. Of course you could always go for the item below which, it is said can connect to a wifi network at a range of 10 miles but youre as likely to get the jail as get connected so maybe you should just leave it to us.

 

Having recently completed my latest M.Eng block on the subject of “Natural and Artificial Intelligence“, I became aware of advances made in the recent decade towards a new paradigm of network traffic engineering that was being researched. This new model turns its back on traditional destination based solutions, (OSPF, EIGRP, MPLS) to the combinatorial problem of decision making in network routing  favouring instead a constructive greedy heuristic which uses stochastic combinatorial optimisation. Put in more accessible terms, it leverages the emergent ability of sytems comprised of quite basic autonomous elements working together, to perform a variety of complicated tasks with great reliability and consistency.

In 1986, the computer scientist Craig Reynolds set out to investigate this phenomenon through computer simulation. The mystery and beauty of a flock or swarm is perhaps best described in the opening words of his classic 1986 paper on the subject:

The motion of a flock of birds is one of nature’s delights. Flocks and related synchronized group behaviors such as schools of fish or herds of land animals are both beautiful to watch and intriguing to contemplate. A flock … is made up of discrete birds yet overall motion seems fluid; it is simple in concept yet is so visually complex, it seems randomly arrayed and yet is magnificently synchronized. Perhaps most puzzling is the strong impression of intentional, centralized control. Yet all evidence dicates that flock motion must be merely the aggregate result of the actions of individual animals, each acting solely on the basis of its own local perception of the world.

An analogy with the way ant colonies function has suggested that the emergent behaviour of ant colonies to reliably and consistently optimise paths could be leveraged to enhance the way that the combinatorial optimisation problem of complex network path selection is solved.

The fundamental difference between the modelling of a complex telecommunications network and more commonplace problems of combinatorial optimisation such as the travelling salesman problem is that of the dynamic nature of the state at any given moment of a network such as the internet. For example, in the TSP the towns, the routes between them and the associated distances don’t change. However, network routing is a dynamic problem. It is dynamic in space, because the shape of the network – its topology – may change: switches and nodes may break down and new ones may come on line. But the problem is also dynamic in time, and quite unpredictably so. The amount of network traffic will vary constantly: some switches may become overloaded, there may be local bursts of activity that make parts of the network very slow, and so on. So network routing is a very difficult problem of dynamic optimisation. Finding fast, efficent and intelligent routing algorithms is a major headache for telcommunications engineers.

So how you may ask, could ants help here? Individual ants are behaviourally very unsophisticated insects. They have a very limited memory and exhibit individual behaviour that appears to have a large random component. Acting as a collective however, ants manage to perform a variety of complicated tasks with great reliability and consistency, for example, finding the shortest routes from their nest to a food source. 



These behaviours emerge from the interactions between large numbers of individual ants and their environment. In many cases, the principle of stigmergy is used. Stigmergy is a form of indirect communication through the environment. Like other insects, ants typically produce specific actions in response to specific local environmental stimuli, rather than as part of the execution of some central plan. If an ant’s action changes the local environment in a way that affects one of these specific stimuli, this will influence the subsequent actions of ants at that location. The environmental change may take either of two distinct forms. In the first, the physical characteristics may be changed as a result of carrying out some task-related action, such as digging a hole, or adding a ball of mud to a growing structure. The subsequent perception of the changed environment may cause the next ant to enlarge the hole, or deposit its ball of mud on top of the previous ball. In this type of stigmergy, the cumulative effects of these local task-related changes can guide the growth of a complex structure. This type of influence has been called sematectonic. In the second form, the environment is changed by depositing something which makes no direct contribution to the task, but is used solely to influence subsequent behaviour which is task related. This sign-based stigmergy has been highly developed by ants and other exclusively social insects, which use a variety of highly specific volatile hormones, or pheromones, to provide a sophisticated signalling system. It is primarily this second mechanism of sign based sigmergy that has been successfully simulated with computer models and applied as a model to a system of network traffic engineering.

In the traditional network model, packets move around the network completely deterministically. A packet arriving at a given node is routed by the device which simply consults the routing table and takes the optimum path based on its destination. There is no element of probability as the values in the routing table represent not probabilities, but the relative desirability of moving to other nodes.

In the ant colony optimisation model, virtual ants also move around the network, their task being to constantly adjust the routing tables according to the latest information about network conditions. For an ant, the values in the table are probabilities that their next move will be to a certain node.The progress of an ant around the network is governed by the following informal rules:

• Ants start at random nodes.

 

• They move around the network from node to node, using the routing table at each node as a guide to which link to cross next.

 

• As it explores, an ant ages, the age of each individual being related to the length of time elapsed since it set out from its source. However, an ant that finds itself at a congested node is delayed, and thus made to age faster than ants moving through less choked areas.

 

• As an ant crosses a link between two nodes, it deposits pheromone however, it leaves it not on the link itself, but on the entry for that link in the routing table of the node it left. Other ‘pheromone’ values in that column of the nodes routing table are decreased, in a process analogous to pheromone decay.

 

• When an ant reaches its final destination it is presumed to have died and is deleted from the system.R.I.P.

Testing the ant colony optimisation system, and measuring its performance against that of a number of other well-known routing techniques produced good results and the system outperformed all of the established mechanisms however there are potential problems of the kind that constantly plague all dynamic optimisation algorithms. The most significant problem is that, after a long period of stability and equilibrium, the ants will have become locked into their accustomed routes. They become unable to break out of these patterns to explore new routes capable of meeting new conditions which could exist if a sudden change to the networks conditions were to take place. This can be mitigated however in the same way that evolutionary computation introduces mutation to fully explore new possibilities by means of the introduction of an element of purely random behaviour to the ant.

‘Ant net’ routing has been tested on models of US and Japanese communications networks, using a variety of different possible traffic patterns. The algorithm worked at least as well as, and in some cases much better than, four of the best-performing conventional routing algorithms. Its results were even comparable to those of an idealised ‘daemon’ algorithm, with instantaneous and complete knowledge of the current state of the network.

It would seem we have not heard the last of these routing antics…. (sorry, couldnt resist).

The IEEE 802.1D Spanning Tree Protocol was designed to keep a switched or bridged network loop free, with adjustments made to the network topology dynamically. A topology change typically takes 30 seconds, with a port moving from the Blocking state to the Forwarding state after two intervals of the Forward Delay Timer. As technology has improved, 30 seconds has become an unbearable length of time to wait for a production network to fail over or "heal" itself during a problem.

The IEEE 802.1w standard was developed to used 802.1D's principal concepts and make the resulting convergence much faster. This is also known as the Rapid Spanning Tree Protocol (RSTP), which defines how switches must interact with each other to keep the network topology loop free, in a very efficient manner.

As with 802.1D, RSTP's basic functionality can be applied as a single instance or multiple instances. This can be done by using RSTP as the underlying mechanism for the Cisco-proprietary Per-VLAN Spanning Tree Protocol (PVST+). The resulting combination is called Rapid PVST+ (RPVST+). RSTP is also used as part of the IEEE 802.1s Multiple Spanning Tree (MST) operation. RSTP operates consistently in each, but replicating RSTP as multiple instances requires different approaches.

RSTP Port Behaviour
In 802.1D,each switch port is assigned a role and a state at any given time. Depending on the ports proximity to the Root Bridge, it takes on one of the following roles:

• Root Port

 

• Designated Port

 

• Blocking Port (neither root nor designated)

Tge Cisco proprietary UplinkFast feature also reserved a hidden alternate port role for ports that offered parallel paths to the root but were in the Blocking state.

Each switch port is also assigned one of five possible states:

• Disabled

 

• Blocking

 

• Listening

 

• Learning

 

• Forwarding

Only the forwarding state allows data to be sent and received. A ports state is somewhat tied to its role. For example, a blocking port cannot be a root port or a designated port.

RSTP achieves its rapid nature by letting each switch interact with its neighbours through each port. This interaction is performed based on a ports role, not strictly on the BPDU's that are relayed from the Root Bridge. After the role is determined, each port can be given a state that determines what it does with incoming data.

The Root Bridge in a network using RSTP is elected just as with 802.1D- by the lowest Bridge ID. After all switches agree on the identity of the root, the following port roles are determined.

• Root Port - The one switch port on each switch that has the best root path cost to the root. This is identical to 802.1D. (By definition the root bridge has no root ports.)

 

• Designated Port - The switch port on a network segment that has the best root path cost to the root.

 

• Alternate Port - A port that has an alternative path to the root, different than the path the root port takes. This path is less desirable than that of the root port. (An example of this is an access-layer switch with two uplink ports; one becomes the root port, and the other is an alternate port.)

 

• Backup port - A port that provides a redundant (but less desirable) connection to a segment where another switch port already connects. If that common segment is lost, the switch might or might not have a path back to the root.

RSTP defines port states only according to what the port does with incoming frames. (Naturally, if incoming frames are ignored or dropped, so are outgoing frames.) Any port role can have any of these port states:

• Discarding - Incoming frames are simply dropped; no MAC addresses are learned. (This state combines the 802.1D Disabled, Blocking and Listening states because all three did not effectively forward anything. The Listening state is not needed because RSTP can quickly negotiate a state change without listening for BPDUs first.

 

• Learning - Incoming frames are dropped but MAC addresses are learned.

 

• Forwarding - Incoming frames are forwarded according to MAC addresses that have been (and are being) learned.