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49-455: IRC clients can connect to Undernet via the global round robin irc.undernet.org , the region-specific round robins us.undernet.org and eu.undernet.org , IPv6 client servers irc6.undernet.org or a specific server from the server list. Undernet was established in October 1992 by Danny Mitchell, Donald Lambert, and Laurent Demally as an experimental network running a modified version of

98-561: A server farm . Commonly load-balanced systems include popular web sites , large Internet Relay Chat networks, high-bandwidth File Transfer Protocol (FTP) sites, Network News Transfer Protocol (NNTP) servers, Domain Name System (DNS) servers, and databases. Round-robin DNS is an alternate method of load balancing that does not require a dedicated software or hardware node. In this technique, multiple IP addresses are associated with

147-612: A DNS query, so that on different connection attempts, clients would receive service from different providers, thus distributing the overall load among servers. Some resolvers attempt to re-order the list to give priority to numerically "closer" networks. This behaviour was standardized in RFC 3484 during the definition of IPv6, when applied to IPv4 the bug in Windows Vista and caused issues and defeated round-robin load-balancing. Some desktop clients do try alternate addresses after

196-429: A connection timeout of up to 30 seconds. Round-robin DNS is often used to load balance requests among a number of Web servers . For example, a company has one domain name and three identical copies of the same web site residing on three servers with three IP addresses. The DNS server will be set up so that domain name has multiple A records, one for each IP address. When one user accesses the home page it will be sent to

245-489: A known set of tasks with the available processors in order to minimize a certain performance function. The trick lies in the concept of this performance function. Static load balancing techniques are commonly centralized around a router, or Master , which distributes the loads and optimizes the performance function. This minimization can take into account information related to the tasks to be distributed, and derive an expected execution time. The advantage of static algorithms

294-427: A means to curb abuse. Undernet uses GNUworld to provide X , its channel service bot . X operates on a user name basis; a username is independent from a nickname, which cannot be registered on Undernet. As Undernet limits channel registration to "established channels" or channels with an active userbase, Undernet introduced a version of ChanFix (under the nickname C ) designed to work like EFNet's CHANFIX. Its use

343-415: A number of drawbacks, such as those arising from record caching in the DNS hierarchy itself, as well as client-side address caching and reuse, the combination of which can be difficult to manage. Round-robin DNS should not solely be relied upon for service availability. If a service at one of the addresses in the list fails, the DNS will continue to hand out that address and clients will still attempt to reach

392-460: A period in 1994, Undernet was wracked by an ongoing series of flame wars . Again in 2001, it was threatened by automated heavy spamming of its users for potential commercial gain. Undernet survived these periods relatively intact and its popularity continues to the present day. It is notable as being the first network to utilize timestamping , originally made by Carlo Wood, in the IRC server protocol as

441-534: A server does not reply as required, the server can be temporarily removed from the DNS pool, until it reports that it is once again operating within specs. Load balancing (computing) In computing , load balancing is the process of distributing a set of tasks over a set of resources (computing units), with the aim of making their overall processing more efficient. Load balancing can optimize response time and avoid unevenly overloading some compute nodes while other compute nodes are left idle. Load balancing

490-471: A single domain name ; clients are given IP in a round-robin fashion. IP is assigned to clients with a short expiration so the client is more likely to use a different IP the next time they access the Internet service being requested. Another more effective technique for load-balancing using DNS is to delegate www.example.org as a sub-domain whose zone is served by each of the same servers that are serving

539-413: A single common memory on which they read and write in parallel ( PRAM model), and those where each computing unit has its own memory ( distributed memory model), and where information is exchanged by messages. For shared-memory computers, managing write conflicts greatly slows down the speed of individual execution of each computing unit. However, they can work perfectly well in parallel. Conversely, in

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588-459: A single potential IP address , but with a list of potential IP addresses corresponding to several servers that host identical services. The order in which IP addresses from the list are returned is the basis for the term round robin . With each DNS response, the IP address sequence in the list is permuted . Traditionally, IP clients initially attempt connections with the first address returned from

637-443: A specific node dedicated to the distribution of work. When tasks are uniquely assigned to a processor according to their state at a given moment, it is a unique assignment. If, on the other hand, the tasks can be permanently redistributed according to the state of the system and its evolution, this is called dynamic assignment. Obviously, a load balancing algorithm that requires too much communication in order to reach its decisions runs

686-407: A specific problem. Among other things, the nature of the tasks, the algorithmic complexity , the hardware architecture on which the algorithms will run as well as required error tolerance , must be taken into account. Therefore compromise must be found to best meet application-specific requirements. The efficiency of load balancing algorithms critically depends on the nature of the tasks. Therefore,

735-404: A very efficient algorithm "Tree-Shaped computation", where the parent task is distributed in a work tree. Initially, many processors have an empty task, except one that works sequentially on it. Idle processors issue requests randomly to other processors (not necessarily active). If the latter is able to subdivide the task it is working on, it does so by sending part of its work to the node making

784-419: Is work stealing . The approach consists of assigning to each processor a certain number of tasks in a random or predefined manner, then allowing inactive processors to "steal" work from active or overloaded processors. Several implementations of this concept exist, defined by a task division model and by the rules determining the exchange between processors. While this technique can be particularly effective, it

833-510: Is "static" when it does not take into account the state of the system for the distribution of tasks. Thereby, the system state includes measures such as the load level (and sometimes even overload) of certain processors. Instead, assumptions about the overall system are made beforehand, such as the arrival times and resource requirements of incoming tasks. In addition, the number of processors, their respective power and communication speeds are known. Therefore, static load balancing aims to associate

882-473: Is an NP-hard problem and therefore can be difficult to be solved exactly. There are algorithms, like job scheduler , that calculate optimal task distributions using metaheuristic methods. Another feature of the tasks critical for the design of a load balancing algorithm is their ability to be broken down into subtasks during execution. The "Tree-Shaped Computation" algorithm presented later takes great advantage of this specificity. A load balancing algorithm

931-457: Is difficult to implement because it is necessary to ensure that communication does not become the primary occupation of the processors instead of solving the problem. In the case of atomic tasks, two main strategies can be distinguished, those where the processors with low load offer their computing capacity to those with the highest load, and those were the most loaded units wish to lighten the workload assigned to them. It has been shown that when

980-460: Is not known in advance at all, static load distribution is always possible. In a round-robin algorithm, the first request is sent to the first server, then the next to the second, and so on down to the last. Then it is started again, assigning the next request to the first server, and so on. This algorithm can be weighted such that the most powerful units receive the largest number of requests and receive them first. Randomized static load balancing

1029-408: Is not tolerable to execute a parallel algorithm that cannot withstand the failure of one single component. Therefore, fault tolerant algorithms are being developed which can detect outages of processors and recover the computation. If the tasks are independent of each other, and if their respective execution time and the tasks can be subdivided, there is a simple and optimal algorithm. By dividing

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1078-431: Is possible to make inferences for a future task based on statistics. In some cases, tasks depend on each other. These interdependencies can be illustrated by a directed acyclic graph . Intuitively, some tasks cannot begin until others are completed. Assuming that the required time for each of the tasks is known in advance, an optimal execution order must lead to the minimization of the total execution time. Although this

1127-599: Is shared. The last category assumes a dynamic load balancing algorithm. Since the design of each load balancing algorithm is unique, the previous distinction must be qualified. Thus, it is also possible to have an intermediate strategy, with, for example, "master" nodes for each sub-cluster, which are themselves subject to a global "master". There are also multi-level organizations, with an alternation between master-slave and distributed control strategies. The latter strategies quickly become complex and are rarely encountered. Designers prefer algorithms that are easier to control. In

1176-410: Is simply a matter of randomly assigning tasks to the different servers. This method works quite well. If, on the other hand, the number of tasks is known in advance, it is even more efficient to calculate a random permutation in advance. This avoids communication costs for each assignment. There is no longer a need for a distribution master because every processor knows what task is assigned to it. Even if

1225-406: Is still possible to approximate a relatively fair distribution of tasks, provided that the size of each of them is much smaller than the total computation performed by each of the nodes. Most of the time, the execution time of a task is unknown and only rough approximations are available. This algorithm, although particularly efficient, is not viable for these scenarios. Even if the execution time

1274-434: Is that they are easy to set up and extremely efficient in the case of fairly regular tasks (such as processing HTTP requests from a website). However, there is still some statistical variance in the assignment of tasks which can lead to the overloading of some computing units. Unlike static load distribution algorithms, dynamic algorithms take into account the current load of each of the computing units (also called nodes) in

1323-417: Is the subject of research in the field of parallel computers . Two main approaches exist: static algorithms, which do not take into account the state of the different machines, and dynamic algorithms, which are usually more general and more efficient but require exchanges of information between the different computing units, at the risk of a loss of efficiency. A load-balancing algorithm always tries to answer

1372-767: Is to protect unregistered channels. ChanFix tracks channel op usage by username basis and restores ops if channels become opless or are taken over . Round robin DNS Round-robin DNS is a technique of load distribution , load balancing , or fault-tolerance provisioning multiple, redundant Internet Protocol service hosts, e.g., Web server , FTP servers , by managing the Domain Name System 's (DNS) responses to address requests from client computers according to an appropriate statistical model. In its simplest implementation, round-robin DNS works by responding to DNS requests not only with

1421-510: The EFnet irc2.7 IRCd software, created in an attempt to make it less bandwidth-consumptive and less chaotic, as netsplits and takeovers were starting to plague EFnet. The Undernet IRC daemon became known as "ircu". Undernet was formed at a time when many small IRC networks were being started and subsequently disappearing; however, it managed to grow into one of the largest and oldest IRC networks despite some initial in-fighting and setbacks. For

1470-571: The case of message exchange, each of the processors can work at full speed. On the other hand, when it comes to collective message exchange, all processors are forced to wait for the slowest processors to start the communication phase. In reality, few systems fall into exactly one of the categories. In general, the processors each have an internal memory to store the data needed for the next calculations and are organized in successive clusters . Often, these processing elements are then coordinated through distributed memory and message passing . Therefore,

1519-494: The context of algorithms that run over the very long term (servers, cloud...), the computer architecture evolves over time. However, it is preferable not to have to design a new algorithm each time. An extremely important parameter of a load balancing algorithm is therefore its ability to adapt to scalable hardware architecture. This is called the scalability of the algorithm. An algorithm is called scalable for an input parameter when its performance remains relatively independent of

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1568-443: The different execution times. First of all, in the fortunate scenario of having tasks of relatively homogeneous size, it is possible to consider that each of them will require approximately the average execution time. If, on the other hand, the execution time is very irregular, more sophisticated techniques must be used. One technique is to add some metadata to each task. Depending on the previous execution time for similar metadata, it

1617-490: The first IP address. The second user who accesses the home page will be sent to the next IP address, and the third user will be sent to the third IP address. In each case, once the IP address is given out, it goes to the end of the list. The fourth user, therefore, will be sent to the first IP address, and so forth. A round-robin DNS name is, on rare occasions, referred to as a "rotor" due to the rotation among alternative A records. Although easy to implement, round-robin DNS has

1666-633: The inoperable service. Round-robin DNS may not be the best choice for load balancing on its own, since it merely alternates the order of the address records each time a name server is queried. Because it does not take transaction time, server load, and network congestion into consideration, it works best for services with a large number of uniformly distributed connections to servers of equivalent capacity. Otherwise, it just does load distribution . Methods exist to overcome such limitations. For example, modified DNS servers (such as lbnamed ) can routinely poll mirrored servers for availability and load factor. If

1715-413: The load balancing algorithm should be uniquely adapted to a parallel architecture. Otherwise, there is a risk that the efficiency of parallel problem solving will be greatly reduced. Adapting to the hardware structures seen above, there are two main categories of load balancing algorithms. On the one hand, the one where tasks are assigned by “master” and executed by “workers” who keep the master informed of

1764-460: The master processor. In addition to efficient problem solving through parallel computations, load balancing algorithms are widely used in HTTP request management where a site with a large audience must be able to handle a large number of requests per second. One of the most commonly used applications of load balancing is to provide a single Internet service from multiple servers , sometimes known as

1813-465: The more information about the tasks is available at the time of decision making, the greater the potential for optimization. Perfect knowledge of the execution time of each of the tasks allows to reach an optimal load distribution (see algorithm of prefix sum ). Unfortunately, this is in fact an idealized case. Knowing the exact execution time of each task is an extremely rare situation. For this reason, there are several techniques to get an idea of

1862-400: The network is heavily loaded, it is more efficient for the least loaded units to offer their availability and when the network is lightly loaded, it is the overloaded processors that require support from the most inactive ones. This rule of thumb limits the number of exchanged messages. In the case where one starts from a single large task that cannot be divided beyond an atomic level, there is

1911-456: The number of tasks is unknown, it is still possible to avoid communication with a pseudo-random assignment generation known to all processors. The performance of this strategy (measured in total execution time for a given fixed set of tasks) decreases with the maximum size of the tasks. Of course, there are other methods of assignment as well: Master-Worker schemes are among the simplest dynamic load balancing algorithms. A master distributes

1960-442: The progress of their work, and the master can then take charge of assigning or reassigning the workload in case of the dynamic algorithm. The literature refers to this as "Master-Worker" architecture. On the other hand, the control can be distributed between the different nodes. The load balancing algorithm is then executed on each of them and the responsibility for assigning tasks (as well as re-assigning and splitting as appropriate)

2009-404: The quality of the algorithm can be greatly improved by replacing the master with a task list that can be used by different processors. Although this algorithm is a little more difficult to implement, it promises much better scalability, although still insufficient for very large computing centers. Another technique to overcome scalability problems when the time needed for task completion is unknown

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2058-420: The request. Otherwise, it returns an empty task. This induces a tree structure . It is then necessary to send a termination signal to the parent processor when the subtask is completed so that it, in turn, sends the message to its parent until it reaches the root of the tree. When the first processor, i.e. the root, has finished, a global termination message can be broadcast. In the end, it is necessary to assemble

2107-399: The results by going back up the tree. The efficiency of such an algorithm is close to the prefix sum when the job cutting and communication time is not too high compared to the work to be done. To avoid too high communication costs, it is possible to imagine a list of jobs on shared memory . Therefore, a request is simply reading from a certain position on this shared memory at the request of

2156-524: The risk of slowing down the resolution of the overall problem. Parallel computing infrastructures are often composed of units of different computing power , which should be taken into account for the load distribution. For example, lower-powered units may receive requests that require a smaller amount of computation, or, in the case of homogeneous or unknown request sizes, receive fewer requests than larger units. Parallel computers are often divided into two broad categories: those where all processors share

2205-468: The size of that parameter. When the algorithm is capable of adapting to a varying number of computing units, but the number of computing units must be fixed before execution, it is called moldable. If, on the other hand, the algorithm is capable of dealing with a fluctuating amount of processors during its execution, the algorithm is said to be malleable. Most load balancing algorithms are at least moldable. Especially in large-scale computing clusters , it

2254-416: The system. In this approach, tasks can be moved dynamically from an overloaded node to an underloaded node in order to receive faster processing. While these algorithms are much more complicated to design, they can produce excellent results, in particular, when the execution time varies greatly from one task to another. Dynamic load balancing architecture can be more modular since it is not mandatory to have

2303-411: The tasks in such a way as to give the same amount of computation to each processor, all that remains to be done is to group the results together. Using a prefix sum algorithm, this division can be calculated in logarithmic time with respect to the number of processors. If, however, the tasks cannot be subdivided (i.e., they are atomic ), although optimizing task assignment is a difficult problem, it

2352-418: The time needed for the assignment, the execution time would be comparable to the prefix sum seen above. The problem with this algorithm is that it has difficulty adapting to a large number of processors because of the high amount of necessary communications. This lack of scalability makes it quickly inoperable in very large servers or very large parallel computers. The master acts as a bottleneck . However,

2401-417: The workload to all workers (also sometimes referred to as "slaves"). Initially, all workers are idle and report this to the master. The master answers worker requests and distributes the tasks to them. When he has no more tasks to give, he informs the workers so that they stop asking for tasks. The advantage of this system is that it distributes the burden very fairly. In fact, if one does not take into account

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