With the development of the Internet of Things, smart objects are used ubiquitously for supporting intelligent and cost-efficient applications. Techniques that collect and aggregate data from sensing devices are essential, and spatial index trees are usually constructed for facilitating the queries. Current spatial index trees are mostly not efficient for query data collection and aggregation. To address this challenge, we propose in this paper an Energy efficiency index tree (EGF-tree) for efficient data collection and aggregation, especially for the situation when sensor nodes are distributed unevenly. Generally, the region of the sensor network is divided evenly into grid cells. An EGF-tree is constructed through merging grid cells nearby. A multi-region query aggregation method is proposed for facilitating the collection and aggregation of simultaneous queries. Theoretical analysis and experiments show that our query aggregation technique is energy efficient.

Wireless sensor networks consist of hundreds or thousands of nodes and are broadly used for collecting data from the environment. In this type of network nodes communicate with each other and send their data to the base station. Since sensor nodes are battery limited, it is crucial to minimize the amount of energy they dissipate for communication. The LEACH protocol is an elegant clustering algorithm for sending information to base station. It uses clustering, therefore each node only communicates with their cluster head nodes and then those cluster heads communicate with base station. In this paper we improved the LEACH algorithm and proposed a weighted energy efficient clustering algorithm (WEEC) algorithm for wireless sensor networks. We take into consideration the location of each node while clusters are forming. The simulation result proves that our proposed scheme noticeably increases the life time of the network.

Wireless sensor networks are widely used for gathering data in an autonomous fashion. Since sensors are power constrained devices, it is quite important for them to minimize the energy consumption. In this paper we propose a novel tree-based clustering (TBC) approach for energy efficient wireless sensor networks. Here the nodes in a cluster form a tree with the root as the cluster-head, while the height of the tree is decided based on the distance of the member nodes to the cluster-head. Computer simulation shows that the proposed scheme effectively reduces and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes such as LEACH, PEGASIS, and TREEPSI.

Wireless sensor networks are an important new technology for remote monitoring. How to organize the nodes in a network remains a core practical problem. Node clustering is the most popular technique to increase the energy efficiency of a wireless sensor network, but the number of clusters greatly influences two performance metrics - data reliability and energy efficiency. Present methods treat these two metrics separately. To address this gap, we here introduce a joint optimal clustering technique (JOC), which optimizes both the number of clusters and the clustering process by considering intra and inter-cluster communication cost, link quality and traffic congestion so that both reliability and energy efficiency are maximized. We used simulation to compare JOC with HEED, the most popular of current clustering techniques. The results show that JOC improves network lifetime and reliability significantly.

Wireless sensor networks (WSNs) open a new domain which has great potentials in application of gathering data in a variety of environments. It is necessary to design energy efficient routing to maximize lifetime of WSNs, because WSNs consist of a large number of sensor nodes with limited battery. In this paper, we analyze the well-known clustering routing protocol LEACH and put forward feasible measures to improve the performance. We propose an energy and distance based clustering (EDBC) protocol which optimizes the random selection of cluster heads in LEACH. Regarding residual energy of sensor nodes, we select nodes with relatively more energy as clusters. Distances between cluster heads are greater than a proper threshold D to form a well-proportioned distribution. Simulation results show that EDBC outperforms LEACH in terms of network lifetime, load balance and energy utilization.

Wireless sensor networks (WSNs) have recently gained the attention of researchers in many challenging aspects. The most important challenge in these networks is energy conservation. One of the most popular solutions in making WSNs energy-efficient is to cluster the networks. In clustering, the nodes are divided into some clusters and then some nodes, called cluster-heads, are selected to be the head of each cluster. In a typical clustered WSN, the regular nodes sense the field and send their data to the cluster-head, then, after gathering and aggregating the data, the cluster-head transmits them to the base station. Clustering the nodes in WSNs has many benefits, including scalability, energy-efficiency, and reducing routing delay. In this paper we present a state-of-the-art and comprehensive survey on clustering approaches. We first begin with the objectives of clustering, clustering characteristics, and then present a classification on the clustering algorithms in WSNs. Some of the clustering objectives considered in this paper include scalability, fault-tolerance, data aggregation/fusion, increased connectivity, load balancing, and collision avoidance. Then, we survey the proposed approaches in the past few years in a classified manner and compare them based on different metrics such as mobility, cluster count, cluster size, and algorithm complexity.

Wireless sensor networks (WSN) is widely used for gathering data in the distributed fashion. In WSN, each node has limited energy resource, and thus the lifetime of the network is one of the most critical issues. In this paper we propose an energy efficient and optimal randomized clustering protocol for self-organizing WSNs. The proposed scheme decides optimal number of clusters by employing a new approach for setting threshold value, including the probability of optimum number of cluster-heads and residual energy of the nodes. We also introduce a new approach maximize the network lifetime by tree construction in each cluster. Computer simulation shows that the proposed scheme effectively reduces and balances the energy consumption among the nodes, and thus significantly extends the network lifetime compared to the existing schemes.

Wireless sensor networks (WSN) consisting of a largenumber of sensors aims to gather data in a variety of environments and is beingused and applied in many different fields. The sensor nodes composing a sensornetwork operate on battery of limited power and as a result, high energyefficiency and long network lifetime are major goals of research in the WSN. Inthis paper we propose a novel cluster-based local multi-hop routing protocolthat enhances the overall energy efficiency and guarantees reliability in thesystem. The proposed protocol minimizes energy consumption for datatransmission among sensor nodes by forming a multi-hop in the cluster.Moreover, through local cluster head rotation scheme, it efficiently manageswaste of energy caused by frequent formation of clusters which was an issue inthe existing methods. Simulation results show that our scheme enhances energyefficiency and ensure longer network time in the sensor network as comparedwith existing schemes such as LEACH, LEACH-C and PEACH.

Wireless sensor network consists of hundreds to thousands of sensor nodes gathering various data including temperature, sound, location, etc. They have been applied to numerous fields such as healthcare, monitoring system, military, and so forth. It is usually difficult to recharge or replace the sensor nodes which have limited battery capacity. Energy efficiency is thus a primary issue in maintaining the network. In this paper we propose an efficient cluster head selection method using K-means algorithm to maximize the energy efficiency of wireless sensor network. It is based on the concept of finding the cluster head minimizing the sum of Euclidean distances between the head and member nodes. Computer simulation shows that the proposed approach allows better performance than the existing hierarchical routing protocols such as LEACH and HEED in terms of network lifetime.

Wireless sensor network consists of hundreds or thousands of tiny sensor nodes, which can monitor remote environment and it's useful in military and civilian applications. The limitation of the batteries of sensor nodes necessitates that the energy efficiency is a key issue in WSN. We proposed a novel protocol LEACH-L based on the geographical location of nodes, which improves the LEACH on its clustering method, cluster-head selecting and the relay transmitting. It takes care of both residual energy and position of sensor nodes in cluster when chooses a cluster-head. Mathematic analysis and simulation show that the LEACH-L has better performance in the network lifetime, node energy consumption and network throughput.

Wireless sensor network consisting of a large number of small sensors of low-power transceiver is effective for gathering data in a variety of environments. Since the network is built with low-cost sensor nodes of limited battery power, it is a challenging task to design an efficient routing scheme maximizing the network lifetime. In this paper, we propose a new clustering protocol reducing the energy taken for routing, and thus extending the network lifetime. The proposed scheme is based on a newly developed model of optimal number of clusters in the network with which the energy consumption can be minimized. It also includes a method of cluster-head rotation inside each cluster, which avoids the clustering operation during normal operation and evenly distributes the load among the nodes. The performance of the proposed scheme is compared with the clustering-based routing protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH), LEACH-Centralized (LEACH-C), and Adaptive and Energy Efficient Clustering (AEEC) algorithm. Simulation results show that it significantly reduces energy consumption and improves network lifetime. It is thus expected to be effective for large-scale semantic sensor web.

Wireless sensor network consisting of a large number of small sensors is effective for gathering various data in a variety of environments. Since each sensor operates on battery, energy efficient data transfer is indispensable to maximize the lifetime of the network. In this paper we propose a new data transfer protocol employed in large-scale wireless sensor network. Here only one designated cluster-head sends the data received from other cluster-heads to the base station during one round of communication. Also, we adopt a method that replaces weak cluster-head using a proxy node. Comparison with the existing schemes such as LEACH and PEACH through computer simulation reveals that the proposed scheme significantly improves the network lifetime for practical operational conditions.

Wireless sensor network consisting of a large number of sensors is effective for gathering data in a variety of environments. Since the sensors operate on battery of limited power, it is a challenging task to design an efficient routing scheme which can minimize the delay while offering high energy efficiency and long network lifetime. In this paper we propose a new routing protocol and data gathering scheme in which the sensor nodes form chains in each cluster. The cluster and chain construction occur only once, and the cluster-head rotates locally inside the cluster without re-clustering. Simulation results show that the proposed routing scheme significantly reduces energy consumption and increases the lifetime of sensor network compared to other hierarchical routing schemes such as Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information System (PEGASIS).

Wireless sensor network comprises of numerous tiny sensor nodes to form an ad hoc distributed sensing and data propagation network to collect the context information on the physical environment. Wireless sensor networks are used for remotely monitoring tasks and effective for data gathering in a variety of environments. Minimizing energy dissipation and maximizing network lifetime are one of the central concerns to design applications and protocols for wireless sensor networks. Cluster based architectures are one of the most practical solutions in order to cope with the requirements of large scale of sensor networks. Clustering results in a reduced number of messages that propagate through the network in order to accomplish a sensing task. In this paper, we have presented a brief review of the state of the art scenario of various routing protocols and propose a weighted energy efficient cluster based routing for wireless sensor networks. Conducted simulation experiments on different scenarios shown its ability to obtain effective & efficient communications among different clusters and achieves scalability in large scale of wireless sensor networks.

Wireless sensor network (WSN) technologies are increasingly employed in recent years for monitoring purposes in various fields ranging from the engineering industry to our immediate home environments due to their ability to intelligently monitor remote locations at low cost. While WSNs are continuously tasked to handle more complex functions, such as, data aggregation, frequent transmissions etc., in-network processing and intelligent computation still necessitate the available energy resources to be judiciously consumed in order to prolong their lifetime, since the nodes are often powered by batteries. In this thesis, our original contribution to knowledge is by developing three key strategies that can efficiently optimize transmission protocols in relation to offer an improved network lifetime for WSN deployments. Our first strategy involves a design of a cluster-based network layer routing protocol. We propose a purely deterministic model that utilizes clustering to organize the WSN. Our design is referred to as DEC: a deterministic energy-efficient clustering protocol. It is dynamic, distributive, self-organizing and it offers better energy efficiency compared with the existing protocols in the same domain. In addition, it utilizes a simplified approach that minimizes computational overhead to self-organize the sensor network. Our simulation result shows a better performance with respect to the energy consumption, which is reflected in the network lifetime of up to 2× improvement in both homogeneous and heterogeneous settings when compared with the existing protocols. It is worth mentioning that our approach approximates an ideal solution to offer a balanced energy consumption in hierarchical wireless sensor networks.

Wireless sensor network (WSN) systems are typically composed of thousands of sensors that are powered by limited energy resources. To extend the networks longevity, clustering techniques have been introduced to enhance energy efficiency. This paper presents a survey on clustering over the last two decades. Existing protocols are analyzed from a quality of service (QoS) perspective including three common objectives, those of energy efficiency, reliable communication and latency awareness. This review reveals that QoS aware clustering demands more attention. Furthermore, there is a need to clarify how to improve quality of user experience (QoE) through clustering. Understanding the users’ requirements is critical in intelligent systems for the purpose of enabling the ability of supporting diverse scenarios. User awareness or user oriented design is one remaining challenging problem in clustering. In additional, this paper discusses the potential challenges of implementing clustering schemes to Internet of Things (IoT) systems in 5G networks. We indicate that clustering techniques enhanced with smart network selection solutions could highly benefit the QoS and QoE in IoT. As the current studies for WSNs are conducted either in homogeneous or low level heterogeneous networks, they are not ideal or even not able to function in highly dynamic IoT systems with a large range of user scenarios. Moreover, when 5G is finally realized, the problem will become more complex than that in traditional simplified WSNs. Several challenges related to applying clustering techniques to IoT in 5G environment are presented and discussed.

Wireless Sensor Nodes are deployed in the hostile region to help the user by providing data to the user for the review purpose. These nodes are having limited power as they are battery operated. Hence, routing protocol used to deliver data to end users must be energy efficient to provide prolonged network lifetime. In this paper, we have proposed a decentralized clustering scheme based on sequential selection (S-LEACH) that maintains desired number of cluster heads during each round until the death of first node. Extensive simulations are carried out to compare our proposed protocol with three well known protocols - LEACH (Low Energy Adaptive Clustering Hierarchy), LDCHS (Low Energy Clustering Hierarchy with Deterministic Cluster Head Selection) and ALEACH (Advanced LEACH). Simulation results show that S-LEACH outperforms to the LEACH, LDCHS and ALEACH protocols.

Wireless Sensor Networks require robust wireless communication that are energy efficient and provide low latency. Various routing schemes have been presented in order to improve the life time of these wireless sensor networks and to overcome the energy constraint of sensor nodes. One of the effective schemes is based on clustering of sensor nodes and as well as to improve the network life time, decreases the communication latency and to reduce the energy consumption of whole Wireless Sensor Networks as much as possible. In this paper we include a brief survey of the state-of-the-art of various existing cluster based routing algorithms for sensor networks and present a new clustering algorithm named HCBQRP: Hierarchical Cluster Based Query-Driven Routing Protocol for Wireless Sensor Networks. The main goal of this routing protocol is to evenly distribute the energy load among the entire sensor nodes in the network so that there are no overly utilized sensor nodes that will run out of energy before the others.

Wireless Sensor Networks (WSNs) is a promising structure used to assist the stipulation of many militaryand industrial services. They have many different constraints, such as computational power, storage capacity, energy supply and etc are the important issue is their energy constraint. Many issues hold back the effectiveness of WSNs to support different applications, such as the resource confines of sensor devices and the finite battery power. To overcome this problem and to improve the performance need not only to minimize total energy consumption but also to balance WSN load. In this research, a novel tree based routing protocol is proposed which builds a routing tree using a process where, for each round, BS assigns a root node and broadcasts this selection to all sensor nodes. Subsequently, each node selects its parent by considering only itself and its neighbors’ information, thus making a dynamic protocol. The simulation results shows that the proposed approach performs better that other existing approaches. Generalized self-organized tree based energy balancing routing protocol (GSTEB) with shortest path algorithm and SWARM based GSTEB.

Wireless Sensor Networks (WSN) consist in a set of nodes that collect information from the environment and send it to a Base Station that processes the final data. Some challenges in order to minimize the power consumption and maximize the network lifetime in this kind of networks can be found. This paper presents MH-LEACH, an algorithm that permits to establish a multi-hop communication between sensor nodes, which aims to save energy. Using MH-LEACH, a sensor will have options to transmit their data to closer nodes, always sending the collected data to the base station. This proposal was incorporated into the LEACH protocol being evaluated through simulations. The results show improvements in the approach when compared to the original version of LEACH. Keywords-Sensor networks; Multi-Hop communication; energy consumption;