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|Title:||Clustering-based scheduling: A new class of scheduling algorithms for single-hop lightwave networks|
|Authors:||Petridou, Sophia G.|
Sarigiannidis, Panagiotis G.
Papadimitriou, Georgios I.
Pomportsis, Andreas S.
|Subjects:||FRASCATI::Natural sciences::Computer and information sciences|
|Keywords:||WDM star networks|
|Source:||International Journal of Communication Systems|
|Abstract:||In wavelength division multiplexing (WDM) star networks, the construction of the transmission schedule is a key issue, which essentially affects the network performance. Up to now, classic scheduling techniques consider the nodes' requests in a sequential service order. However, these approaches are static and do not take into account the individual traffic pattern of each node. Owing to this major drawback, they suffer from low performance, especially when operating under asymmetric traffic. In this paper, a new class of scheduling algorithms for WDM star networks, which is based on the use of clustering techniques, is introduced. According to the proposed Clustering‐Based Scheduling Algorithm (CBSA), the network's nodes are organized into clusters, based on the number of their requests per channel. Then, their transmission priority is defined beginning from the nodes belonging to clusters with higher demands and ending to the nodes of clusters with fewer requests. The main objective of the proposed scheme is to minimize the length of the schedule by rearranging the nodes' service order. Furthermore, the proposed CBSA scheme adopts a prediction mechanism to minimize the computational complexity of the scheduling algorithm. Extensive simulation results are presented, which clearly indicate that the proposed approach leads to a significantly higher throughput‐delay performance when compared with conventional scheduling algorithms. We believe that the proposed clustering‐based approach can be the base of a new generation of high‐performance scheduling algorithms for WDM star networks.|
|Appears in Collections:||Department of Applied Informatics |
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