we study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they cannot take full advantage of the presence of node heterogeneity. We propose An Amend LEACH, a heterogeneous aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. A-LEACH is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node

since the energy supply of a sensor node is limited, energy optimization should be considered as the key objective when studying the wireless sensor networks (WSNs). Our contribution is in integrated control optimization and genetic algorithms to ensure proper function of WSNs in extremely limited bandwidth, power and storage. A set of simulation results are performed to demonstrate the effectiveness of the proposed algorithm. The simulation results show that the proposed algorithm has higher efficiency and can achieve better network lifetime at the base station.

real life applications deal with such Heterogeneity rather than Homogeneity. In this paper, a protocol is proposed, which is heterogeneous in energy. We analyze the basic distributed clustering routing protocol LEACH (Low Energy Adaptive Clustering Hierarchy), which is a homogeneous system, and then we study the impact of heterogeneity in energy of nodes to prolong the life time of WSN. Simulation results using MATLAB shows that the proposed Leach-heterogeneous system significantly reduces energy consumption and increase the total lifetime of the wireless sensor network.

With the rapid increase in applications utilizing the current advancements of wireless sensor networks, a number of problems related to self-organization, energy-awareness and network organizations have attracted many researchers in the field. Various groups have proposed grouping the sensors into clusters and design communication routes in two levels as a way to improve communication cost and better organize networks of large sensors. In this paper, we propose a new approach to cluster wireless sensors and identify cluster heads using multi-stage graph algorithms. The approach takes advantage of the optimally associated with finding matching solutions in multi-stage graph networks. The proposed solution is designed to accommodate networks with different sizes and levels of density. We tested the algorithm using different types of networks and measure the quality of the key parameters as compared to those obtained by traditional greedy heuristics. Obtained results show that the multi-stage graph approach produces better network organization and better cluster head selection which leads to be more efficient self-organized networks.

With the growth of different design goals and application requirements, wireless sensor networks (WSNs) have been increasingly popular for a wide variety of purposes, e.g., image formation of a target field, intrusion detection, surveillance and environmental monitoring. In this paper, a multi-hop heterogeneous cluster-based optimization algorithm (MHCOA) for WSNs is proposed. The motivation to MHCOA for WSNs is that several higher energy sensor nodes act as cluster heads, which are deployed artificially, while some low energy sensor nodes act as cluster members, which are deployed randomly. In order to realize monitoring task, we complete three major works in this paper. First, MHCOA calculates the number of cluster heads and communication radius of low energy sensor nodes; Second, it finishes monitoring task through data packets transmission with higher energy nodes acting as cluster heads in the form of multi-hop heterogeneous WSNs; Finally, simulation results show that compared to its peers in heterogeneous WSNs, MHCOA reduces the number of cluster heads, which saves the network average energy by up to 16.7 % and extends the network life by up to 38 %, while with less end-to-end delay.

Wireless sensor system includes hundreds to thousands of sensor nodes that helps in collecting different information including temperature, sound, area, etc. It’s generally difficult to recharge or change the sensor nodes which may have confined battery capacity. Energy efficiency is therefore a key problem in sustaining the network. Certainly one of the most used alternatives to make WSNs energy-efficient is to cluster the networks. Various clustering techniques are accustomed to effectively optimize or enhance the energy of sensor nodes. In this paper we have examined the various methods of clustering which are centralized, distributed and hybrid utilized in Sensor Networks. This paper also presents a comparative study of various clustering algorithms and the issues of clustering in WSNs.

Wireless sensor networks, an interconnection of energy restrained devices used for sensing environmental variables and then transmitting these to sink by manipulating routes over communication medium between sensors and sink node. Major constraints in routing of sensed data are latency of network from source to destination and the other one is limited residual energy of nodes required for effective communication. Both of these are prime factors in designing of routing algorithms. In this paper we have selected geo-locations of nodes as principal variable for energy-efficient routing between nodes. Sensor nodes are equipped with differentiable technical specification over other nodes. Some of nodes have higher initial energies compared to other nodes and higher number of frequency channels than other nodes. Simulation and scenario has been generated in network simulator 2. Transmission power is calculated based on geo-location of nodes and tuned using software radio presets. Likeliness of forwarding packet is based on rationalizing residual energy of transmitting node and distance between nodes.

Wireless sensor networks require energy-efficient data transmission because the sensor nodes have limited power. A cluster-based routing method is more energy-efficient than a flat routing method as it can only send specific data for user requirements and aggregate similar data by dividing a network into a local cluster. However, previous clustering algorithms have some problems in that the transmission radius of sensor nodes is not realistic and multi-hop based communication is not used both inside and outside local clusters. As energy consumption based on clustering is dependent on the number of clusters, we need to know how many clusters are best. Thus, we propose an optimal number of cluster-heads based on multi-hop routing in wireless sensor networks. We observe that a local cluster made by a cluster-head influences the energy consumption of sensor nodes. We determined an equation for the number of packets to send and relay, and calculated the energy consumption of sensor networks using it. Through the process of calculating the energy consumption, we can obtain the optimal number of cluster-heads in wireless sensor networks.

Wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. The way these data are manipulated by the sensor...

Wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. The way these data are manipulated by the sensor nodes is a fundamental issue. Information fusion arises as a response to process data gathered by sensor nodes and benefits from their processing capability. By exploiting the synergy among the available data, information fusion techniques can reduce the amount of data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. In this work, we survey the current state-of-the-art of information fusion by presenting the known methods, algorithms, architectures, and models of information fusion, and discuss their applicability in the context of wireless sensor networks.

Wireless sensor networks have strict constrains in size, weight and energy. The conflict of long lifetime and strict energy constrain brings a natural integration of energy harvesting into wireless sensor networks. A modified low energy adaptive clustering hierarchy (LEACH) protocol has been proposed to increase the network life time. Modified LEACH is divided into two main phases at the first setup phase and at the second steady state phase. Setup phase has been modified such that cluster head (CH) selection will be selected only from advanced nodes. Results showed significant improvement in WSN overall lifetime. Simulations show number of dead nodes vs rounds. Comparison between pure LEACH and modified one showed significant improvement in lifetime, also comparison between modified LEACH and energy aware multi-hop multi-path (EAMMH) protocol shows significant improvement in performance.

Wireless sensor networks have received excessive attention in now a days. Research in all field in wireless sensor network (WSN) till now has assumed that sensors in network is homogeneous, means that all the nodes are same, especially for routing protocols that has used clustering like LEACH, LEACHC, and PEGASIS etc. But in the clustering algorithm where some nodes have to work as cluster heads, if they are same as the other nodes, this would lead the lifetime constraint in WSN. Because of this most we shall be considering here the heterogeneous WSN, where the nodes which will work as cluster head will contain more energy, computational and communication power than normal nodes. In this paper we introduce a routing protocol that is based on clustering and uses heterogeneity in nodes to increase the network lifetime.

Wireless sensor networks have grown from homogeneous network architecture to heterogeneous networks for the improvement of network efficiency and lifetime. This paper exhibits a mobile cluster-head data collection (MCHDC) model for heterogeneous wireless networks. The MCHDC model illustrates the mobility pattern of mobile cluster-head nodes in a controlled environment with uniform and nonuniform deployment of mobile elements in the area of observation. It focuses on the threshold velocity for movement of mobile elements in the network area. In this paper the effects of data sending rate, network area, sensor node density, and cluster-head node density on energy efficiency of the network with the MCHDC model have been studied through simulations.

Wireless sensor networks have gained abundant interest due to their potential wide range of applications. Reliability of deployed wireless sensor network is defined by covered area of alive nodes and redundancy of data. Redundancy in data occurs because of overlapped sensed area. An initial reliable wireless sensor network switches to unreliable state because nodes perish in the field randomly. Consequently, the quality of data starts diminishing. It is imperative to know when the network will switch to unreliable state from reliable state so that proper action can be conducted in the field. Work of this paper analyzes and compares analytical and simulation modeling for reliability state of wireless sensor network. Multi-objective genetic algorithm based method is operated for analytical modeling which determines minimum number of nodes (randomly) that covers almost complete area while having required minimum overlapped area. Clustering algorithm, LEACH, is implemented in NS-2 for simulation modeling. Comparative results of analytical and simulation modeling are different because of their different nature but both highlights that reliability of wireless sensor network is salient.

Wireless sensor networks have found many applications in different areas, including environmental surveillance, intelligent building, health monitoring, intelligent transportations, etc. Recent development in electronics and wireless communications has enabled the improvement of low-power and low cost wireless sensors networks.. One of the most important challenges in WSNs is to design energy (resource) efficient routing mechanism to increase the network lifetime due to the limited energy capacity of the network nodes. This Work also proposed a minimum distance based cluster formation and member nodes allotment process to enhance lifetime. Results will be in terms of Network lifetime (Number of dead sensors), Percentage dead, Network Stability, Network Energy, Network throughput, error rate and delay. The validation parameters will show that; the proposed method will outperform the existing method in [18 and 19].

Wireless sensor networks have been studied for several applications. Disaster damage monitoring is one of the significant applications in sensor networks. If sensors are set up in buildings or on water pipelines, they could detect damage, victims trapped beneath rubble, or water leakage in case of a natural disaster. Since such a monitoring system is required to operate for a long term (e.g. several years) by batteries, power consumption of a node would be a critical issue. To fulfill the requirement, intermittent operation is employed in several medium access control (MAC) protocols in sensor networks. Moreover, those monitoring systems have to deal with several types of information, such as temperature, acceleration, alarm signals and so on, in some cases including image data to comprehend surrounding conditions. Some of them are gathered periodically, and some are in event-driven operation. Due to the diversity of information resources in sensor networks, the monitoring system requires short latency in bidirectional communications to control the process of data transmission dynamically. Considering these conditions, this paper describes a damage monitoring scheme using bidirectional low latency operation on a MAC protocol, which implements a short latency on bidirectional transmission in an active/sleep operation mode. Some fundamental evaluations show that the protocol is capable of achieving the short latency.

Wireless sensor networks have become increasingly popular due to their wide range of applications. Energy consumption is one of the biggest constraints of the wireless sensor node and this limitation combined with a typical deployment of large number of nodes has added many challenges to the design and management of wireless sensor networks. At high temperature the transmission power and sensitivity will decrease which leads to the degradation of wireless links. To avoid that we have implemented a hybrid routing protocol: Zonal-Stable Election Protocol (Z-SEP) for heterogeneous WSNs. In this protocol, some nodes transmit data directly to base station while some use clustering technique to send data to base station as in SEP. We implemented Z-SEP and compared it with traditional Low Energy Adaptive Clustering Hierarchy (LEACH) and SEP. In addition, that energy can be optimized by scheduling the node to sleep mode and alive mode. Simulation results showed that Z-SEP enhanced the stability period and throughput than existing protocols like LEACH and SEP.

Wireless sensor networks have a most stimulating affair of Energy conservation. Different types of techniques were introduced to increase lifetime of network. Clustering is one of them to reduce energy consumption in network. This paper presents an idea of a novel protocol Multilevel Balanced Distributed Energy Efficient Heterogeneous Protocol (MBDEEHP) to create clustering in heterogeneous environment. Since network performance is depend on the number of clusters, so we present a different probability function and threshold formula to get the appropriate number of clusters. After simulation, our protocol is measured on some parameters like stability period, throughput, and network lifetime. So we get that stability period is Nineteen percent better and system lifetime is Twenty two percent better as compared to BEENISH.

Wireless sensor networks consists of thousands of tiny, low cost, low power and multifunctional sensor nodes where each sensor node has very low battery life. Purpose is to conserve the transmitted energy from various sensor nodes. Various energy efficient algorithms have been designed for this. LEACH uses distributed cluster formation & randomized rotation of the cluster head to minimize the network energy consumption. Our paper is proposing an algorithm which is the enhancement of existing IB-LEACH. It reduces the energy consumption by using energy bank. This energy bank stores the energy after each round in both routing and clustering phase which overall increases the life time of the network. In this approach, ACTIVE_ROUTE_TIMEOUT is also enhanced by shamming the static parameters of HELLO_INTERVAL, RREQ_RETRIES and NET_DIAMETER. Results are compared through MATLAB and provide better approach than previous ones.

Wireless sensor networks consists of thousands of tiny, low cost, low power and multifunctional sensor nodes where each sensor node has very low battery life. Purpose is to conserve the transmitted energy from various sensor nodes. Various energy efficient algorithms have been designed for this. LEACH uses distributed cluster formation & randomized rotation of the cluster head to minimize the network energy consumption. Our paper is proposing an algorithm which is the enhancement of existing IB-LEACH. It reduces the energy consumption by using energy bank. This energy bank stores the energy after each round in both routing and clustering phase which overall increases the life time of the network. In this approach, ACTIVE_ROUTE_TIMEOUT is also enhanced by shamming the static parameters of HELLO_INTERVAL, RREQ_RETRIES and NET_DIAMETER. Results are compared through MATLAB and provide better approach than previous ones.