Load balancing (computing)

In computing, load balancing improves the distribution of workloads across multiple computing resources, such as computers, a computer cluster, network links, central processing units, or disk drives. Load balancing aims to optimize resource use, maximize throughput, minimize response time, and avoid overload of any single resource. Using multiple components with load balancing instead of a single component may increase reliability and availability through redundancy. Load balancing usually involves dedicated software or hardware, such as a multilayer switch or a Domain Name System server process. In computing, load balancing improves the distribution of workloads across multiple computing resources, such as computers, a computer cluster, network links, central processing units, or disk drives. Load balancing aims to optimize resource use, maximize throughput, minimize response time, and avoid overload of any single resource. Using multiple components with load balancing instead of a single component may increase reliability and availability through redundancy. Load balancing usually involves dedicated software or hardware, such as a multilayer switch or a Domain Name System server process. Load balancing differs from channel bonding in that load balancing divides traffic between network interfaces on a network socket (OSI model layer 4) basis, while channel bonding implies a division of traffic between physical interfaces at a lower level, either per packet (OSI model Layer 3) or on a data link (OSI model Layer 2) basis with a protocol like shortest path bridging. One of the most commonly used applications of load balancing is to provide a single Internet service from multiple servers, sometimes known as a server farm. Commonly load-balanced systems include popular web sites, large Internet Relay Chat networks, high-bandwidth File Transfer Protocol sites, Network News Transfer Protocol (NNTP) servers, Domain Name System (DNS) servers, and databases. An alternate method of load balancing, which does not require a dedicated software or hardware node, is called round robin DNS. In this technique, multiple IP addresses are associated with a single domain name; clients are given IP in 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 the web site. This technique works particularly well where individual servers are spread geographically on the Internet. For example: However, the zone file for www.example.org on each server is different such that each server resolves its own IP Address as the A-record. On server one the zone file for www.example.org reports: On server two the same zone file contains: This way, when a server is down, its DNS will not respond and the web service does not receive any traffic. If the line to one server is congested, the unreliability of DNS ensures less HTTP traffic reaches that server. Furthermore, the quickest DNS response to the resolver is nearly always the one from the network's closest server, ensuring geo-sensitive load-balancing. A short TTL on the A-record helps to ensure traffic is quickly diverted when a server goes down. Consideration must be given the possibility that this technique may cause individual clients to switch between individual servers in mid-session. Another approach to load balancing is to deliver a list of server IPs to the client, and then to have client randomly select the IP from the list on each connection. This essentially relies on all clients generating similar loads, and the Law of Large Numbers to achieve a reasonably flat load distribution across servers. It has been claimed that client-side random load balancing tends to provide better load distribution than round-robin DNS; this has been attributed to caching issues with round-robin DNS, that in case of large DNS caching servers, tend to skew the distribution for round-robin DNS, while client-side random selection remains unaffected regardless of DNS caching.