Inductive Approaches Based on Trial/Error Paradigm for Communications Network

Today, providing a good quality of service (QoS) in irregular traffic networks is an important challenge. Besides, the impressive emergence and the important demand of the rising generation of real-time Multi-service (such as Data, Voice VoD, Video-Conference, etc.) over communication heterogeneous networks, require scalability while considering a continuous QoS. This emergence of rising generation Internet required intensive studies these last years which were based on QoS routing for heterogeneous networks on the one hand and on the backbone architecture level of communication networks characterized by a high and irregular traffic on the other hand (Mellouk et al., 2007b). The basic function of QoS routing is to find a network path which satisfies the given constraints and optimize the resource utilization. The integration of QoS parameters increases the complexity of the used routing algorithms. Thus, the problem of determining a QoS route that satisfies two or more path constraints (for example, delay and cost) is known to be NP-complete (Gravey & Jhonson, 1979). A difficulty is that the time required to solve the Multi-Constrained Optimal path problem exactly cannot be upper-bounded by a polynomial function. Hence the focus has been on the development of pseudo-polynomial time algorithms, heuristics and approximation algorithms for multi-constrained QoS paths (Kuipers & Mieghem, 2005). At present, several studies have been conducted on QoS routing algorithms which integrate the QoS requirements problematic for the routing algorithm. (Song & Sahni, 2006) introduce heuristics to find a source-to-destination path that satisfies two or more additive constraints on edge weights. (Jaffe, 1984) has proposed a polynomial time approximation algorithm for k multi-constrained path which uses a shortest path algorithm such as Dijkstra’s (Sahni, 2005). (Korkmaz & Krunz, 2001) propose a randomized heuristic that employs two phases. In the first one, a shortest path is computed for each of the k QoS constraints as well as for a linear combination of all k constraints. The second phase performs a randomized breadthfirst search for a solution of k multi-constrained problem. In (Kuipers & Mieghem, 2005), authors suggest that QoS routing in realistic networks could not be NP-complete regarding to a particular class of networks (topology and link weight structure). Due this complexity, QoS routing problems are divided on several classes according to some aspects. For example, we distinguish the single path routing problem and the multipath routing problem, where routers maintain multiple distinct paths of arbitrary costs between a