An energy-efficient unequal clustering routing protocol for wireless sensor networks

Abstract

Wireless sensor networks have drawn tremendous attentions from all fields because of their wide application. Maximizing network lifetime is one of the main problems in wireless sensor networks. This article proposes an energy-efficient routing protocol which adopts unequal clustering technology to solve the hot spots problem and proposes double cluster head strategy to reduce the energy consumption of head nodes in the clusters. In addition, to balance the energy consumption between cluster heads and cluster members, a hybrid cluster head rotation strategy based on time-driven and energy-driven is proposed, which can make the timing of rotation more reasonable and the energy consumption more efficient. Finally, we compare the proposed protocol with LEACH, DEBUC, and UCNPD by simulation experiments. The simulation results prove that our proposed protocol can effectively improve the performance in terms of network lifetime, energy consumption, energy balance, stability, and throughput.

Energy-Efficient and Load-Balanced Clustering Routing Protocol for Wireless Sensor Networks Using a Chaotic Genetic Algorithm

“…Clustering usually consists of CHs selection and clusters formation. Many approaches have been provided for CHs selection, which can be categorized into probability based [4][5][6][11][12][13][14], weight based [7,[15][16][17] and heuristics based [9,10,[18][19][20] approaches. The nodes are selected as CHs when their threshold values are less than a random assigned real number between 0 and 1 in probability based approaches.…”

“…Consequently, fuzzy logic inference [9,18,22], particle swarm optimization algorithm [23], bat algorithm [19], genetic algorithm [10,20], differential evolution and harmony search [21] have been used to find the optimal CHs. Once the CHs are selected, each of them broadcasts an advertisement message announcing its CH identity, and the normal nodes decide to join the clusters based on the received signal strength, residual energy of the CHs and so on in order to form uniform and energy efficient clusters [5,11,12,15,[21][22][23]. Moreover, a TDMA schedule like in LEACH is used for intra-cluster communication to further reduce energy consumption .…”

“…Routing is used to find the optimal routing path for each CH because the CMs only can communicate with their corresponding CHs. When a CH receives all the data from its CMs, it fuses and forwards the data to the BS directly in single-hop mode [3][4][5][6]19,22,23] or indirectly in multi-hop mode [7][8][9][10][11][12][13][14][15][16][17][18]24]. Usually, communication between CHs and BS in single hop mode may expend excessive energy when the CH appears far away from the BS and undoubtedly reduce the scalability of the network.…”

“…Hence, fuzzy logic [9], particle swarm optimization [8], ant colony optimization [20,26], genetic algorithm [10,13,17,20] are utilized to find the optimal routing paths for each CH so as to achieve balanced energy consumption of CHs and increased network lifetime. Moreover, they can also alleviate hot spot problem caused by hop-by-hop routing to some extend as other unequal clustering routing methods by adjusting cluster size, selecting vice CHs, and controlling hop counts and so on [12,15,24,27].…”

“…Usually, round is adopted to reconstruct clusters in the network like in LEACH, but it is difficult to determine the most appropriate round time. Moreover, fixed round time inevitably leads to premature death of CHs with low residual energy, resulting in interruption of communication [5,9,11,12,15,16,24]. Especially in the later period of network operation, this situation is even worse.…”