As Internet connectivity is reaching the global community, information systems are becoming more and more distributed. Inevitably, this overnight exponential growth has also caused traffic overload at various places in the network. Until recently, it was believed that scaling the Internet was simply an issue of adding more resources, . bandwidth and processing power could be brought to where they were needed. | Telecommunications Optimization Heuristic and Adaptive Techniques. Edited by David W. Corne Martin J. Oates George D. Smith Copyright 2000 John Wiley Sons Ltd ISBNs 0-471-98855-3 Hardback 0-470-84163X Electronic 13 Adaptive Demand-based Heuristics for Traffic Reduction in Distributed Information Systems George Bilchev and Sverrir Olafsson Introduction As Internet connectivity is reaching the global community information systems are becoming more and more distributed. Inevitably this overnight exponential growth has also caused traffic overload at various places in the network. Until recently it was believed that scaling the Internet was simply an issue of adding more resources . bandwidth and processing power could be brought to where they were needed. The Internet s exponential growth however exposed this impression as a myth. Information access has not been and will not be evenly distributed. As it has been observed user requests create hot-spots of network load with the same data transmitted over the same network links again and again. These hotspots are not static but also move around making it impossible to accurately predict the right network capacity to be installed. All these justify the requirement to develop new infrastructure for data dissemination on an ever-increasing scale and the design of adaptive heuristics for traffic reduction. In this chapter we develop a distributed file system model and use it as an experimental simulation tool to design implement and test network adaptation algorithms. Section describes in detail the distributed file system model and explains the implemented simulation environment. Two adaptation algorithms are developed in section . One is Telecommunications Optimization Heuristic and Adaptive Techniques edited by . Corne . Oates and . Smith 2000 John Wiley Sons Ltd 224 Telecommunications Optimization Heuristic and Adaptive Techniques based on the greedy heuristic principle and the other is a .
