An energy-driven unequal clustering protocol for heterogeneous wireless sensor networks

SummaryIn wireless sensor network, a large number of sensor nodes are distributed to cover a certain area. Sensor node is little in size with restricted processing power, memory, and limited battery life. Because of restricted battery power, wireless sensor network needs to broaden the system lifetime by reducing the energy consumption. A clustering‐based protocols adapt the use of energy by giving a balance to all nodes to become a cluster head. In this paper, we concentrate on a recent hierarchical routing protocols, which are depending on LEACH protocol to enhance its performance and increase the lifetime of wireless sensor network. So our enhanced protocol called Node Ranked–LEACH is proposed. Our proposed protocol improves the total network lifetime based on node rank algorithm. Node rank algorithm depends on both path cost and number of links between nodes to select the cluster head of each cluster. This enhancement reflects the real weight of specific node to success and can be represented as a cluster head. The proposed algorithm overcomes the random process selection, which leads to unexpected fail for some cluster heads in other LEACH versions, and it gives a good performance in the network lifetime and energy consumption comparing with previous version of LEACH protocols.

One of the most important topics in the field of wireless sensor networks is the development of approaches to improve network lifetime. In this paper, an energy-efficient control and routing protocol for wireless sensor networks is presented. This algorithm is based on reinforcement learning for energy management in the network. This protocol seeks to optimize routing policies to maximize the long-term reward received by each node, using reinforcement learning, which is a machine learning approach. In order to improve the lifetime of wireless sensor network, three energy management approaches have been proposed. The first approach is to navigate correctly using reinforcement learning to reduce the length of the routes and to improve energy consumption. The second approach is to exploit a sleep scheduling technique to improve node energy consumption. The last approach is used to restrict data transmission of each node based on the received data change rate. Simulation results show that in terms of network lifespan, the proposed method significantly outperforms previous reported methods.

Wireless sensor networks(WSN) are a kind of communication networks with in-dependent sensor nodes which could construct multi-hop ad hoc network to trans-fer data. The transport protocols for Wireless Sensor Network play an important role to promote the performance of the whole systems. This paper proposes a modified transport layer protocol for heterogeneous Wireless Sensor Networks(HWSN). As TCP is not suitable to use in HWSN directly, we design a modified transport protocol(named mTCP) based on TCP by a six-state finite state machine. Experimental results illustrate that our design can improve the communication capability of the transmission layer in heterogeneous wireless sensor networks significantly.

Energy saving to prolong the network life is an important design issue while developing a new routing protocol for wireless sensor network. Clustering is a key technique for this and helps in maximizing the network lifetime and scalability. Most of the routing and data dissemination protocols of WSN assume a homogeneous network architecture, in which all sensors have the same capabilities in terms of battery power, communication, sensing, storage, and processing. Recently, there has been an interest in heterogeneous sensor networks, especially for real deployments. This research paper has proposed a new energy aware clustering protocol (EACP) for heterogeneous wireless sensor networks. Heterogeneity is introduced in EACP by using two types of nodes: normal and advanced. In EACP cluster heads for normal nodes are elected with the help of a probability scheme based on residual and average energy of the normal nodes. This will ensure that only the high residual normal nodes can become the cluster head in a round. Advanced nodes use a separate probability based scheme for cluster head election and they will further act as a gateway for normal cluster heads and transmit their data load to base station when they are not doing the duty of a cluster head. Finally a sleep state is suggested for some sensor nodes during cluster formation phase to save network energy. The performance of EACP is compared with SEP and simulation result shows the better result for stability period, network life and energy saving than SEP.

Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper we propose a enhance adaptive re-clustering protocol (EARP) for wireless sensor network. In EARP the cluster heads and next heads are elected based on residual energy of each node, transfer power, sleep and awake scheme and the average energy of each cluster. The simulation results show that EARP achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks.

Wireless sensor networks congestion occurs easily due to its centralized traffic pattern. Normally, mono-sync wireless sensor network experiences multiple traffic flow congestion in the dense environment of the network, which leads to excess energy consumption and severe packet loss. To overcome these issues, a congestion detection and alleviation mechanism using cluster based heuristic optimized hierarchical routing protocol is proposed in this paper. Here, congestion detection and alleviation utilize the features of sensor nodes. The congestion is categorized into two types: (i) node level congestion and (ii) link level congestion. The node level congestion is detected by assessing the buffer utilization and the interval amid the consecutive data packets. The link level congestion is considered with computing link usage utilizing back-off step of round robin carrier sense multi-access with collision avoidance. Congestion detection and alleviation reactively affected node/link through cuckoo hosted rider search multi-hop routing algorithm. It has two phases: the cluster head selection and multi-path routing. Cluster head selection is performed through Taylor multiple random forest kernel fuzzy C-means clustering algorithm and multi-path routing is performed through cuckoo hosted rider search multi-hop routing algorithm. The simulation of the proposed method is done in network simulator tool. Here, the performance metrics, like packet delivery ratio, delay, energy consumption, packet drop, overhead, network lifetime and throughput are calculated. The experimental outcomes of the proposed technique shows 11.6%, 18.4% and 28.1% lower delay, 78.2%, 65.4% and 52.6% higher packet delivery ratio, and 29.2%, 37.4% and 40.8% lower packet drop compared with the existing methods, like congestion detection and alleviation using multi-attribute decision-making in optimization-based hybrid congestion alleviation routing protocol in wireless sensor networks, congestion detection and alleviation using hybrid K-means with greedy best first search algorithms in packet rate reduction utilizing adaptive weight firefly algorithm ant colony optimization based routing protocol in wireless sensor networks and congestion detection and alleviation using multi-input time on task optimization algorithm for altered gravitational search algorithm routing protocol in wireless sensor networks.

FAMACROW: Fuzzy and ant colony optimization based combined mac, routing, and unequal clustering cross-layer protocol for wireless sensor networks

Nowadays Wireless Sensor Networks WSNs are playing a vital role in several application areas ranging health to battle field. Wireless sensor networks are easy to deploy due to its unique characteristics of size and self-organizing networks. Wireless sensor nodes contain small unchangeable and not chargeable batteries. It is a resource constraint type network. Routing in WSN is most expensive task as it utilizes more power resources. This paper is intended to introduce energy efficient routing protocol, known as Position Responsive Routing Protocol (PRRP) to enhance energy efficiency of WSN. Position responsive routing protocol differs in several ways than other existing routing techniques. Position response routing protocol approach allows fair distribution of gateway\cluster head selection, maximum possible distance minimization among nodes and gateways\cluster heads to utilize less energy. Position responsive routing protocol shows significant improvement of 45% in energy efficiency of wireless sensor network life time as a whole by increasing battery life of individual nodes. Furthermore PRRP shows drastic increases for data throughput and provide better solution to routing energy hole due to it fair distributed approach of gateway selection. This work is the extension of Energy efficient routing protocol for wireless sensor network published in IEEE ICACT 2014.

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.

Wireless sensor networks are mainly designed for environment monitoring. The lifetime of wireless sensor networks depends on the durability of the battery resource sensors, so it is crucial for sensors to efficiently use their limited battery resources. The energy expends by sensors in data communication makes up a significant quantum of their total amount of energy consumption. In the existing research, most of the power-saving medium access control protocols reduce energy consumption by putting periodically sensors to sleep mode. Such a regular active/sleep schedule fails to adjust individual sensor sleep duration according to per-sensor communication traffic-load, which causes unnecessary idle-listening problem and low power-efficiency. In this paper, we present a new power-saving medium access control protocol for saving power in a wireless sensor networks. This proposed protocol dynamically adjusts the active/sleep time duration of each sensor according to per-sensor communication traffic-load. Meanwhile, it can lead to much greater power-efficiency by prolonging the sensors sleeping duration, when in a sensor network at per-sensor communication traffic-load is low. The basic idea of this proposed protocol is an analytical model for estimating the accurate per-sensor communication traffic-load in a wireless sensor network and a grid-based quorum concept for regular active/sleep schedule.

Hybrid meta-heuristic optimization based energy efficient protocol for wireless sensor networks

—Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way, since their energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor networks. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with the highest residual energy send data to the base station. Furthermore, we can save the energy of head nodes by using the modes selection method. The simulation results show that CPMS achieves longer lifetime and more data message transmissions than current important clustering protocols in wireless sensor networks.

QoSNET: An integrated QoS network for routing protocols in large scale wireless sensor networks

The lifetime of Wireless Sensor Network (WSN) is based on the energy of each sensor. Therefore, numerous routing protocols have been introduced such as SEP (Stable Election Protocol), LEACH (Low energy adaptive clustering hierarchy) and EAMMH (Energy Aware Multi-hop Multi-path Hierarchical routing protocol) to stable the lifetime of WSN by efficient utilization of energy of the sensors. In WSN networks data is collected and forwarded wirelessly to the base stations. Routing protocols in WSN provide an efficient path for multi-hop communication because the transmission range and battery power storage of nodes is limited. As nodes are usually deployed in remote areas so, they face challenges of long lifetime, network architecture, security issues, and network coverage. Many routing protocols have been developed to increase the efficiency of networks. Out of these clustering algorithms are the best choice to increase the lifetime of the nodes. Each protocol has its limitations in different scenarios. In this paper, we discussed and compared the performance of LEACH, EAMMH and SEP. SEP is an efficient algorithm due to its weighted cluster head (CH) selection method. Simulation results are obtained using MATLAB. Design metrics of energy consumption and network lifetime are under consideration in this research work.

Classical clustering protocols in wireless sensor networks (WSNs) assume that all nodes are equipped with the same amount of energy. As a result, they cannot take full advantage of the presence of node heterogeneity. In this study, a stable and energy‐efficient clustering (SEEC) protocol for heterogeneous WSNs is proposed. In addition, the extension to multi‐level of SEEC is presented. It depends on the network structure that is divided into clusters. Each cluster has a powerful advanced node and some normal nodes deployed randomly in this cluster. In the multi‐level architectures, more powerful supper nodes are assigned to cover distant sensing areas. Each type of nodes has its role in the sensing, aggregation or transmission to the base station. At each level of heterogeneity, the optimum number of powerful nodes that achieves the minimum energy consumption of the network is obtained. The proposed protocol is a heterogeneous awareness to prolong the stability period, which is crucial for many applications. The performance of the proposed protocol is compared by existing homogeneous and heterogeneous protocols. Simulation results show that the proposed protocol provides a longer stability period, more energy efficiency and higher average throughput than the existing protocols.