LEAUCH: low-energy adaptive uneven clustering hierarchy for cognitive radio sensor network

Abstract

The integration of wireless sensor network (WSN) and cognitive radio (CR) technology enables a new paradigm of communication: cognitive radio sensor networks (CRSN). The existing WSN clustering algorithm cannot consider the advantage of channel resource brought by CR function in CRSN, and the CR network (CRN) clustering algorithm is designed based on the infinite energy nodes; thus both algorithms cannot operate with energy efficiency in CRSN. The paper proposes a low-energy adaptive uneven clustering hierarchy for CRSN, which can not only consider the advantage of the channel resource in reducing the energy consumption but also employ uneven clustering method for balancing the energy consumption among the cluster heads under multiple hops transmission means. Simulation results show that compared with the existing several typical clustering algorithms including WSN and CRSN clustering algorithms, low-energy adaptive clustering hierarchy (LEACH), HEED, energy-efficient unequal clustering (EEUC), cognitive LEACH (CogLEACH), and distributed spectrum-aware clustering (DSAC), the proposed algorithm can not only efficiently balance the energy consumption among cluster heads and network load in CRSN but also remarkably prolong the network lifetime.

TIME-DRIVEN opportunistic routing protocol for ultra-wideband indoor positioning

“…These algorithms with diverse emphasis of the cluster head (CH) election are applied in various environments, and the cluster structures are different. Because the link traffic lacks balance, the hot path 16 will reduce the network survival time.…”

“…Moreover, the algorithm employs the uneven clustering method, which can balance energy consumption among multi-hop CHs. However, most of those applications 16 have low bandwidth demands and are usually tolerant of delay. In literature, [17][18][19] multi-hop uneven clusterbased algorithms in competition all get the simulation result, but the MA selection has some disadvantages: (1) several nodes with less energy are activated to join in the competition without the possibility of winning, which leads to death faster, (2) random activation cannot ensure that the winner is the best, and (3) each competitor can send and receive a broadcast packet and calculate it, which increases the network overhead.…”

“…The uneven cluster-based routing protocol can solve the hot path problem. 16 The proposed routing algorithm takes the number of idle channels of each node as its weight and selects the nodes with more idle channels as the CHs. Moreover, the algorithm employs the uneven clustering method, which can balance energy consumption among multi-hop CHs.…”

Spectrum aware fuzzy clustering algorithm for cognative radio sensor networks

“…In [6], node degree and distance to BS are added to the channel availability parameter in the CH selection. One major observation in [2- 3,6] is the exclusion of energy parameter in the CH selection. This resulted to a possibility that the clustering algorithm may nominate a very low energy CH node causing an early energy hole.…”

“…The centralized architecture of CogLEACH-C has a high network overhead and energy consumption as compared to the distributed CogLEACH in the cluster formation process. LEAUCH [3] is a CR clustering algorithm that controlled the size of cluster of a CH to overcome the hotspots problem in the multi-hop transmission. In [6], node degree and distance to BS are added to the channel availability parameter in the CH selection.…”