ArticleslgStudy

computer science

Heuristic routing

Heuristic routing is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Heuristic routing rather than just read about it. In short: Heuristic routing is a system used to describe how deliveries are made when problems in a network topology arise. Heuristic is an adjective used in relation to methods of learning, discovery, or problem solving.

Key takeaways

  • Heuristic routing belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Heuristic routing to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Heuristic routing from memory before moving on to harder problems.

Reference excerpt

Heuristic routing is a system used to describe how deliveries are made when problems in a network topology arise. Heuristic is an adjective used in relation to methods of learning, discovery, or problem solving. Routing is the process of selecting paths to specific destinations. Heuristic routing is used for traffic in the telecommunications networks and transport networks of the world. Heuristic routing is achieved using specific algorithms to determine a better, although not always optimal, path to a destination. When an interruption in a network topology occurs, the software running on the networking electronics can calculate another route to the desired destination via an alternate available path. According to Shuster & Schur (1974, p. 1):

The heuristic approach to problem solving consists of applying human intelligence, experience, common sense and certain rules of thumb (or heuristics) to develop an acceptable, but not necessarily an optimum, solution to a problem. Of course, determining what constitutes an acceptable solution is part of the task of deciding which approach to use; but broadly defined, an acceptable solution is one that is both reasonably good (close to optimum) and derived within reasonable effort, time, and cost constraints. Often the effort (manpower, computer, and other resources) required, the time limits on when the solution is needed, and the cost to compile, process, and analyze all the data required for deterministic or other complicated procedures preclude their usefulness or favor the faster, simpler heuristic approach. Thus, the heuristic approach is generally used when deterministic techniques or are not available, economical, or practical. Heuristic routing allows a measure of route optimization in telecommunications networks based on recent empirical knowledge of the state of the network. Data, such as time delay, may be extracted from incoming messages, during specified periods and over different routes, and used to determine the optimum routing for transmitting data back to the sources.

IP routing

The IP routing protocols in use today are based on one of two algorithms: distance vector or link state. Distance vector algorithms broadcast routing information to all neighboring routers. Link state routing protocols build a topographical map of the entire network based on updates from neighbor routers, and then use the Dijkstra algorithm to compute the shortest path to each destination. Metrics used are based on the number of hops, delay, throughput, traffic, and reliability.

Distance vector algorithms RIP uses number of hops, or gateways traversed, as its metric IGRP uses bandwidth, delay, hop count, link reliability, load, and MTU EIGRP uses the (DUAL) Diffusing Update Algorithm BGP uses the distance vector algorithm

Link state algorithms OSPF uses the Dijkstra algorithm.

See also Heuristic (computer science) Ford–Fulkerson algorithm Bellman–Ford algorithm Turn restriction routing

References Campbell, Ann Melissa; Savelsbergh, Martin (2004). "Efficient insertion heuristics for vehicle routing and scheduling problems". Transportation Science. 38 (3): 369–378. CiteSeerX 10.1.1.499.8006. doi:10.1287/trsc.1030.0046. JSTOR 25769207. {{cite journal}}: Cite uses deprecated parameter |citeseerx= (help) Malhotra, Ravi (2002). IP routing. Sebastopol, CA: O'Reilly. ISBN 0596002750. OCLC 49318657. Robertazzi, Thomas G. (2007). Networks and grids: technology and theory. Information technology: transmission, processing, and storage. New York: Springer. doi:10.1007/978-0-387-68235-8. ISBN 9780387367583. OCLC 76935739. Shuster, Kenneth A; Schur, Dennis A. (1974). Heuristic routing for solid waste collection vehicles. An environmental protection publication (SW-113) in the solid waste management series. Washington, DC: U.S. Environmental Protection Agency. hdl:2027/mdp.39015040701149. OCLC 3207134. This article incorporates public domain material from Federal Standard 1037C. General Services Administration. Archived from the original on 2022-01-22.

Worked examples

Example 1 — a first encounter with Heuristic routing

Start with the simplest possible case. Write down what Heuristic routing claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Heuristic routing before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Heuristic routing ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Heuristic routing

In research
Heuristic routing appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Heuristic routing in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Heuristic routing is common in secondary-school and first-year university syllabi. It links to neighbouring topics Heuristic algorithms, Routing, so understanding it makes those chapters shorter.
In everyday life
Look for Heuristic routing outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Heuristic routing in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Heuristic routing means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Heuristic routing out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Heuristic routing in simple terms?

Heuristic routing is a system used to describe how deliveries are made when problems in a network topology arise. Heuristic is an adjective used in relation to methods of learning, discovery, or problem solving.

Why does Heuristic routing matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Heuristic routing?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Heuristic routing.

Tags

  • Heuristic algorithms
  • Routing

Keep exploring