Is there any method where we can get a minimum cost broadcast routing scheme without using the spanning tree algorithm?
Any references to guide me on this will be of great use to me.
Any algorithm for implementing a minimum cost broadcast (or multicast) routing scheme in the end boils down to constructing a least-cost spanning tree (rooted at the multicast source) of the full graph which represents the network.
There are various algorithms for computing the least-cost spanning tree.
IP multicast routing protocols such as PIM rely on least-cost spanning tree which is computed by the IGP (OSPF or ISIS) using the Dijkstra algorithm.
Older protocols, such as DVMRP, rely on a distance-vector protocol to compute the spanning tree.
One could theoretically use other algorithms to compute the least-cost spanning tree (e.g. Bellman-Ford) although I know of no implementation that does so in practice.
To add to Cayle, considering you mentioned spanning tree I assume you are not talking about layer 3 (pim, dvmrp, ospf, isis, rip, bgp, etc) and you are instead talking about layer 2. TRILL is a new standardized protocol that does nearly minimum cost broadcast routing (assuming your source is at a root of a distribution tree). IEEE 802.1aq is a protocol still be standardized that does a similar routing scheme.
Trill(Transparent Interconnection of Lots of links ) is the best option against STP.Because in stp there is a shortest dedicated path from source to destination.When Trill is used for multipathing.So using Trill we can use maximum bandwidth of the network.The research is also going on Trill.Trill usually use ISIS protocol for internal routing and Dijkstra algorithm for shortest path.
Trill basically work on L2 as well as on L3.If you are looking for implementation of trill you have to refer RFCs like 6325,6326,7177 and many more.
If you are looking for switches with Trill implemented.Cisco,juniperNetwork, Huawei and many other companies implemented it partially in the switches.
Thanks
Related
I have a bidirectional ring network topology with 9 routers. What would you suggest to reduce the size (number of rows) in a routing table, and a number of hops?
I suggest using a dynamic routing protol such as OSPF or RIP / EIGRP .
using HSRP for switches : https://en.wikipedia.org/wiki/Hot_Standby_Router_Protocol
I think what confusing you is that if every two of the nodes build a connection, the network may become comlpex.
Firstly, since the topology is small, a controller may be a good choice for you. If you don't want it, then you can use some algorithm like dijkstra, OSPF, RIP, or something others like ants colony algorithm, genetic algorithm which can work well in large network.
For P2P networks, I know that some networks have initial bootstrap nodes. However, one would assume that with all new nodes learning of peers from said bootstrap nodes, the network would have difficulty adding new peers and would end up with many cliques - unbalanced, for lack of a better word.
Are there any methods to prevent this from occuring? I'm aware that some DHTs structure their routing tables to be a bit less susceptible to this, but I would think the problem would still hold.
To clarify, I'm asking about what sort of peer mixing algorithms exist/are commonly used for peer to peer networks.
However, one would assume that with all new nodes learning of peers from said bootstrap nodes, the network would have difficulty adding new peers and would end up with many cliques - unbalanced, for lack of a better word.
If the bootstrap nodes were the only source of peers and no further mixing occured that might be an issue. But in practice bootstrap nodes only exist for bootstrapping (possibly only ever once) and then other peer discovery mechanisms take over.
Natural mixing caused by connection churn should be enough to randomize graphs over time, but proactive measures such as a globally agreed-on mixing algorithm to drop certain neighbors in favor of others can speed up that process.
I'm aware that some DHTs structure their routing tables to be a bit less susceptible to this, but I would think the problem would still hold.
The local buckets in kademlia should provide an exhaustive view of the neighborhood, medium-distance buckets will cover different parts of the keyspace for different nodes and the farthest buckets will preferentially contain long-lived nodes which should have a good view of the network.
This doesn't leave much room for clique-formation.
How can defined topology in Castalia-3.2 for WBAN ?
How can import topology in omnet++ to casalia ?
where the topology defined in default WBAN scenario in Castalia?
with regard
thanks
Topology of a network is an abstraction that shows the structure of the communication links in the network. It's an abstraction because the notion of a link is an abstraction itself. There are no "real" links in a wireless network. The communication is happening in a broadcast medium and there are many parameters that dictate if a packet is received or not, such as the power of transmission, the path loss between transmitter and receiver, noise and interference, and also just luck. Still, the notion of a link could be useful in some circumstances, and some simulators are using it to define simulation scenarios. You might be used to simulators that you can draw nodes and then simply draw lines between them to define their links. This is not how Castalia models a network.
Castalia does not model links between the nodes, it models the channel and radios to get a more realistic communication behaviour.
Topology is often confused with deployment (I confuse them myself sometimes). Deployment is just the placement of nodes on the field. There are multiple ways to define deployment in Castalia, if you wish, but it is not needed in all scenarios (more on this later). People can confuse deployment with topology, because under very simplistic assumptions certain deployments lead to certain topologies. Castalia does not make these assumptions. Study the manual (especially chapter 4) to get a better understanding of Castalia's modeling.
After you have understood the modeling in Castalia, and you still want a specific/custom topology for some reason then you could play with some parameters to achieve your topology at least in a statistical sense. Assuming all nodes use the same radios and the same transmission power, then the path loss between nodes becomes a defining factor of the "quality" of the link between the nodes. In Castalia, you can define the path losses for each and every pair of nodes, using a pathloss map file.
SN.wirelessChannel.pathLossMapFile = "../Parameters/WirelessChannel/BANmodels/pathLossMap.txt"
This tells Castalia to use the specific path losses found in the file instead of computing path losses based on a wireless channel model. The deployment does not matter in this case. At least it does not matter for communication purposes (it might matter for other aspects of the simulation, for example if we are sampling a physical process that depends on location).
In our own simulations with BAN, we have defined a pathloss map based on experimental data, because other available models are not very accurate for BAN. For example the, lognormal shadowing model, which is Castalia's default, is not a good fit for BAN simulations. We did not want to enforce a specific topology, we just wanted a realistic channel model, and defining a pathloss map based on experimental data was the best way.
I have the impression though that when you say topology, you are not only referring to which nodes could communicate with which nodes, but which nodes do communicate with which nodes. This is also a matter of the layers above the radio (MAC and routing). For example it's the MAC and Routing that allow for relay nodes or not.
Note that in Castalia's current implementations of 802.15.6MAC and 802.15.4MAC, relay nodes are not allowed. So you can not create a mesh topology with these default implementations. Only a star topology is supported. If you want something more you'll have to implemented yourself.
We have N cache-nodes with basic consistent-hashing in a ring.
Questions:
Is data-structure of this ring stored:
On each of these nodes?
Partly on each node with its ranges?
On a separate machine as a load balancer?
What happens to the ring when other nodes join it?
Thanks a lot.
I have found an answer to the question No 1.
Answer 1:
All the approaches are written in my blog:
http://ivoroshilin.com/2013/07/15/distributed-caching-under-consistent-hashing/
There are a few options on where to keep ring’s data structure:
Central point of coordination: A dedicated machine keeps a ring and works as a central load-balancer which routes request to appropriate nodes.
Pros: Very simple implementation. This would be a good fit for not a dynamic system having small number of nodes and/or data.
Cons: A big drawback of this approach is scalability and reliability. Stable distributed systems don’t have a single poing of failure.
No central point of coordination – full duplication: Each node keeps a full copy of the ring. Applicable for stable networks. This option is used e.g. in Amazon Dynamo.
Pros: Queries are routed in one hop directly to the appropriate cache-server.
Cons: Join/Leave of a server from the ring requires notification/amendment of all cache-servers in the ring.
No central point of coordination – partial duplication: Each node keeps a partial copy of the ring. This option is direct implementation of CHORD algorithm. In terms of DHT each cache-machine has its predessesor and successor and when receiving a query one checks if it has the key or not. If there’s no such a key on that machine, a mapping function is used to determine which of its neighbors (successor and predessesor) has the least distance to that key. Then it forwards the query to its neighbor thas has the least distance. The process continues until a current cache-machine finds the key and sends it back.
Pros: For highly dynamic changes the previous option is not a fit due to heavy overhead of gossiping among nodes. Thus this option is the choice in this case.
Cons: No direct routing of messages. The complexity of routing a message to the destination node in a ring is O(lg N).
What is the difference (if any) between a node and a vertex? I can't find the answer after looking at countless sites! Even my book doesn't specify it so I am kind of lost!
It is worth mentioning that I am looking for the difference besides the fact that it is called a 'vertex' when used in a graph and a 'node' when used in a tree.
There are no differences between the words Node and Vertex. Even in some books that explain graph theory and graph algorithms they name it as:
Vertex denoted by v, and sometimes it's called nodes also
There are no major nor minor differences between them.
This is mentioned in the book: Data structure and Algorithms with Object Oriented Design Patterns in C#, Bruno R, Preiss.
In "The Practitioner's Guide to Graph Data", the author avoid the term "node/nodes" and only use vertex/vertices and they explain it as below:
...because we are focusing on distributed graphs, and nodes has different meanings in distributed systems, graph theory and computer science.
In distributed systems, a node can be a client, server or peer, while in computer network it can be a computer or a modem. In computer science, as you already point out, it could be used either for graph theory or tree system.
So in the context of graph theory, node and vertex are used interchangeable. But if you would like to make it clear and avoid any misunderstanding, vertex/vertices is the way to go.
In think both terminologies come from the different perception of graphs and networks. Albert-László Barabási writes in his recent text book.
"In the scientific literature the terms network and graph are used interchangeably:
Network science
Graph theory
Network
Graph
Node
Vertex
Link
Edge
Yet, there is a subtle distinction between the two terminologies: the {network, node, link} combination often refers to real systems: The WWW is a network of web documents linked by URLs; society is a network of individuals linked by family, friendship or professional ties; the metabolic network is the sum of all chemical reactions that take place in a cell. In contrast, we use the terms {graph, vertex, edge} when we discuss the mathematical representation of these networks: We talk about the web graph, the social graph (a term made popular by Facebook), or the metabolic graph. Yet, this distinction is rarely made, so these two terminologies are often synonyms of each other."
<tl;dr> Same, same, but different.
There is no difference between a node and a vertex. Most books use V to represent the vertex of a graph. I've seen node mostly associated with a tree.
For instance, you may have come across O(V + E) being used to represent the time complexity for depth first search and breadth first search graph traversals.
Similarly, V is used as part of time complexity analysis for other graph algorithms like Prim's, Kruskal's, etc.