An efficient routing protocol for the QoS support of large‐scale MANETs

SummaryThe hierarchical routing algorithm is categorized as a kind of routing method using node clustering to create a hierarchical structure in large‐scale mobile ad hoc network (LMANET). In this paper, we proposed a new hierarchical clustering algorithm (HCAL) and a corresponded protocol for hierarchical routing in LMANET. The HCAL is designed based on a cost metric in the form of the link expiration time and node's relative degree. Correspondingly, the routing protocol for HCAL adopts a reactive protocol to control the existing cluster head (CH) nodes and handle proactive nodes to be considered as a cluster in LMANET. Hierarchical clustering algorithm jointly utilizes table‐driven and on‐demand routing by using a combined weight metric to search dominant set of nodes. This set is composed by link expiration time and node's relative degree to establish the intra/intercommunication paths in LMANET. The performance of the proposed algorithm and protocol is numerically evaluated in average end‐to‐end delay, number of CH per round, iteration count between the CHs, average CH keeping time, normalized routing overhead, and packet delivery ratio over a number of randomly generated benchmark scenarios. Furthermore, to corroborate the actual effectiveness of the HCAL algorithm, extensive performance comparisons are carried out with some state‐of‐the‐art routing algorithms, namely, Dynamic Doppler Velocity Clustering, Signal Characteristic‐Based Clustering, Dynamic Link Duration Clustering, and mobility‐based clustering algorithms.In this paper, we proposed a hybrid hierarchical clustering algorithm (HCAL) for large‐scale ad hoc networks (LMANET) and a protocol for hierarchical routing related to it (HCAL‐R) based on the cost metric in the forms of the link expiration time and node's relative degree. Remarkable features of the HCAL algorithm are that (1) its implementation is distributed over the available mobile nodes and (2) it is capable to adapt to the (possibly, complex) network size with the high‐speed nodes over the LMANET. Both these features are attained by equipping each routing path by a cost metric function in cluster head (CH) election that acquires context information by the environment (eg, current state of the CHs and the keeping time of the CHs)