An Efficient Clustering Protocol with Reduced Energy and Latency for Wireless Sensor Networks

Wireless sensor network is an emerging technology capable of having low-cost and low-power and battery-powered sensor node. At this point the protocol concentric clustered power-efficient gathering in sensor information systems and clustered general self organized tree based energy-balance routing protocol energy efficient protocol are used to increase the energy and to extend network lifetime. For these achievement of clustering techniques, optimization technique particle swarm optimization is used for data transmission through base station. If the base station is inaccessible region from the cluster-head, energy consumption will be augmented and it can shrink the lifetime of wireless sensor network. To conquer these, multi-hop gateway node is implemented with both protocol to achieve maximum lifetime and energy efficiency of wireless sensor network. To improve the quality-of-service (QoS) placing more number of gateways is required. So we propose a new algorithm nearer optimal algorithm which recursively computes least possible adequate dominating sets, at the time constantly preserving QoS requirements across iterations. In this paper comparison is done in terms of throughput, packets delivery ratio and number of nodes alive.

Division of the entire wireless sensor network geographic area into number of equal sized regions by applying virtual grid and strategy to appoint head node of the cluster in each region improves stability, consistency, and lifetime of the wireless sensor network. Applying the same size of grid to the different size of wireless sensor networks will not give consistent performance. In this paper, we are presenting a protocol which will dynamically determine the size of the virtual grid, which will give optimal performance of any geographic sized wireless sensor network. The protocol also allows to place sink node to any location and not at some fixed specific location. Protocol discussed in this paper can also support multiple sink nodes. Protocol dynamically takes decision to transmit the data directly to the sink node or by using multi-hop transmission by considering distances between sensor nodes internally and sink node(s), which will optimize energy efficiency of the sensor nodes and increases the lifetime of wireless sensor network.

Limited energy supply (battery-powered) is a crucial problem in wireless sensor networks (WSNs). Sensor node placement schemes and routing protocols are mostly proposed to address this problem. In this paper, we first present how to place sensor nodes by use of a minimal number of them to maximize the coverage area when the communication radius of the sensor node is different from the sensing radius, which results in the application of regular topology to WSNs deployment. With nodes placed at an equal distance and equipped with an equal power supply, the problem of unbalanced energy consumption in 2-D regular topologies becomes more severe and much more difficult to tackle than that in 1-D chains, though the latter is known as an already quite hard problem. We address this problem and propose an adaptive data collection scheme by employing different communication radii for nodes in different locations to balance the energy consumption in WSNs. In order to achieve the ultimate goal of maximizing network lifetime in grid-based WSNs, we give a mathematical formulation, which shows the problem of maximizing network lifetime is a nonlinear programming problem and NP-hard even in the 1-D case. We discuss several heuristic solutions and show that the halving shift data collection scheme is the best solution among them. We also generalize the maximizing network lifetime problem to the randomly-deployed WSNs, which shows the significance of our mathematical formulation for this crucial problem in WSNs.

We analyze the impact of the structure of the Data Gathering (DG) trees on node lifetime (round of first node failure) and network lifetime (minimum number of rounds by which the network gets either disconnected due to node failures or the fraction of coverage loss reaches a threshold) in wireless sensor networks through extensive simulations. The two categories of DG trees studied are: the Bottleneck Node Weight-Based (BNW-DG) trees and Bottleneck Link Weight-Based (BLW-DG) trees. The BNW-DG trees incur a smaller diameter and a significantly larger fraction of nodes as leaf nodes: thus, protecting a majority of the nodes in the network from simultaneously being exhausted of the energy resources (contributing to a significantly larger network lifetime); nevertheless the nodes that serve as intermediate nodes in the first few instances of the BNW-DG trees are bound to lose their energy more quickly than the other nodes, leading to a smaller node lifetime compared to that of the BLW-DG trees (that incur a larger diameter and a relatively lower fraction of nodes as leaf nodes).

Wireless sensor networks (WSNs) consist of an enormous number of tiny sensor nodes deployed in huge numbers which are able to sense, process and transmit environmental information to the base station (BS) for a variety of applications. Energy efficiency is one of the primary concerns for maintaining WSN in operation. In this study, an energy efficient clustering protocol based on K‐means algorithm named EECPK‐means has been proposed for WSN where midpoint algorithm is used to improve initial centroid selection procedure. The proposed approach produces balanced clusters to ultimately balance the load of cluster heads (CHs) and prolong the network lifetime. It considers residual energy as the parameter in addition to Euclidean distance used in basic K‐means algorithm for appropriate CH selection. Multi‐hop communication from CH nodes to BS takes place depending on their distances from BS. Simulation result shows that the proposed approach outperforms LEACH‐B, balanced parallel K‐means (BPK‐means), Park's approach and Mk‐means with respect to network lifetime and energy efficiency. Simulation result also demonstrates that the proposed approach can reduce the energy consumption at most 50% compared to LEACH‐B, 14% compared to BPK‐means protocol, 10% compared to Park's approach and 6% compared to Mk‐means.

Wireless sensor networks (WSNs) are composed of an enormous number of smart sensor nodes that are usually battery-powered and considered to work for a long period. Application areas are several and diverse, such as the environmental field, health and military sector. The main gain of these intelligent devices is a large-scale utilization without any maintenance. These sensors do not need to attain an established infrastructure to transfer vital data to the study of the environment. Decreasing energy dissipation and increasing network lifetime in wireless sensor networks are major challenges in the design of routing protocols for smart sensor networks, the main reason why these days several works are concentrating in WSN's energy management.Clustering technique is one of the most popular techniques used to reduce energy ingesting in WSN and boost the whole network life extent. LEACH protocol was presented to minimize energy ingesting. In this paper, a new approach based on pure LEACH is suggested. To measure the performance of modified algorithm, simulation is used to compare its consumption to pure LEACH. Results show that the proposed algorithm lengthens network lifetime and thus diminishes power ingesting.

Wireless Sensor Network (WSN) consists of small battery-powered sensor nodes with limited energy resources, with sensing, computation, and communications capabilities. One of the crucial issues in WSN is energy consumption thus, poor energy efficient routing. The lifetime of the entire network depending on the energy efficiency of the sensor network which finally requires an energy- efficient routing protocol. This paper provides energy-efficient routing by using a fuzzy logic approach in the clusterhead selection process that provides a completely non-probabilistic approach in order to balance the energy consumption of nodes and prolong the WSN lifetime. This approach uses three fuzzy variables: Residual energy of the nodes, distance to Base station and distance to the cluster-head. Simulations results show that the proposed algorithm improves energy consumption and significantly prolong the network lifetime in wireless sensor networks when compared with LEACH protocol.

It is important to prolong the network lifetime in Wireless Sensor Networks. There are two approaches to increase the network lifetime, which are balancing energy consumption and reducing the number of non-working nodes. This paper presents two Cluster head Selection algorithms, one is based on Ensuring target Area and the other is based on Affinity Propagation. We propose a method which makes the energy uniformly distributed throughout the network nodes. In particular, we analyse the effect of the powerful nodes on the network lifetime and cluster characteristics. Simulation results show that the two proposed algorithms distribute non-working nodes evenly, such that the target area is well covered by the remaining nodes. Our proposed algorithms balance the traffic load and energy distributions, and prolong the network lifetime effectively compared with the existing schemes.

Using the mobile sink for data collection from all sensors is the most highly effective way to prolong the network lifetime of wireless sensor networks(WSNs). Many studies focused on the anchors selection, aiming to reduce the path length of mobile sink and prolong the network lifetime. However, the appropriateness and the number of the selected anchors, which significantly impact the network lifetime of the entire WSNs, still can be improved. This paper proposes a Dynamic Anchor Points Mechanism for data collection, called DAM, aiming to select appropriate anchors under the path length constraint for prolonging the network lifetime. The experimental results show that the proposed DAM outperforms existing data collection mechanisms in term of network lifetime and fairness index.

Designing and development of energy effective path planning algorithm is very key research domain in order to tackle the issues of limited life-time for Wireless Sensor Networks (WSNs). So in WSNs, energy efficiency is major concern of researchers. Overall advancement in routing protocols prove that clustering is much better approach as compared to flat and location-based energy efficient routing protocols. Due to better performance, multiple energy efficient clustering routing protocols have been proposed. But existing clustering algorithms are centralized or distributed, which are not intelligent enough and do not produce hybrid cluster-head selection. In this paper, we propose a cluster structured path planning algorithm named, Hybrid Advance Distributed Centralized Clustering (HADCC) path planning energy efficient algorithm. HADCC proposed model is fascinated with hybrid cluster head selection algorithm. This hybrid algorithm makes decision of cluster head selection of nodes. In order to execute proposed model we have also proposed an advance network topology, in which the whole network region is divided into two physical levels. First physical level consists of a circular region, containing homogeneous normal nodes and all important Base Station. While, second physical level is outer region of the circle that contains advanced heterogeneous nodes. Simulation results indicate that HADCC prolongs the network lifetime as compared to existing advanced clustering routing protocols for both homogeneous and heterogeneous WSNs. HADCC outperforms in case of stability and network life time as compared to the existing clustering algorithms.

Maximization of lifetime of wireless sensor network (WSN) is an emerging area of research in present scenario. Many authors are performing their research work, so that they could achieve lower energy consumption for the sensor network which leads to increase in lifetime of network. Our work focuses on sink mobility in a fixed trajectory within a wireless sensor network while sensed data are required to be collected. We divide the whole sensor network into two different regions as direct communication area (DCA) and multi-hop communication area (MCA). Sensors node that lies in DCA is at one hop count distance from the sink node trajectory while sensors within MCA are at more than one hop count from the trajectory. We considered all the sensors that are within DCA as subsink nodes. During sink mobility, whenever a subsink is closer to the mobile sink node, then it starts transmitting its data to the sink node. But those sensors that are within MCA needs to search an appropriate sink node for sending its sensed data to the subsink so that on further stage, that subsink could provide those data to the sink node whenever it is in nearest proximity of that subsink. Basically, a sink node is the ultimate destination for the data while a subsink node acts as a relay node for the nodes that are within MCA. So our work is to find out the appropriate subsink node from a given set of subsinks. For doing so, we used location-aided routing on global positioning system (GPS)-enabled sensors and sink node. Our work is validated through simulation experiments using NS-2.

This paper proposes a framework to maximize the lifetime of the wireless sensor networks (WSNs) by using a mobile sink when the underlying applications tolerate delayed information delivery to the sink. Within a prescribed delay tolerance level, each node does not need to send the data immediately as it becomes available. Instead, the node can store the data temporarily and transmit it when the mobile sink is at the most favorable location for achieving the longest WSN lifetime. To find the best solution within the proposed framework, we formulate optimization problems that maximize the lifetime of the WSN subject to the delay bound constraints, node energy constraints, and flow conservation constraints. We conduct extensive computational experiments on the optimization problems and find that the lifetime can be increased significantly as compared to not only the stationary sink model but also more traditional mobile sink models. We also show that the delay tolerance level does not affect the maximum lifetime of the WSN.

Extensive research is being done on Wireless sensor Networks (WSNs) in present decade. WSNs consist of large number of sensor nodes which perform sensing of certain phenomena and send the sensed data to the sinks. This operation consumes energy of sensor nodes which effects the lifetime of a network. To prolong the lifetime of WSNs various strategies and routing algorithms have been proposed. Use of mobile sinks has proved effective in this respect. In this paper we are analyzing the impact of multiple mobile sinks with proactive hierarchical clustering protocols LEACH and network reactive hierarchical protocol TEEN. This paper will give simulation based analysis of using multiple mobile sinks in network and their effect on lifetime of a network. Performance analysis will be done on basis of dead nodes, alive nodes, throughput and residual energy.

A wireless sensor network (WSN) comprised of a plurality of sensor nodes powered by their internal batteries and one or more base stations. Efficient utilization of the energy resources leads to prolonged network lifetime. In this study, the effects of limiting the total hop count within the network on network lifetime is investigated by using a mixed integer programming (MIP) framework. Our results show that when the hop count of network is limited by minimum hop count, lifetime of network can decrease by %40 of the lifetime obtained without any constraint on hop count. If hop count limit of network is increased by %10, lifetime of network can reach %98 of maximum lifetime obtained without any restrictions on hop count.

Recent advances in Compact and wireless embedded Systems coupled with the technological innovations in Micro Electro Mechanical Systems(MEMS), Wireless Communications and networks paved the way for the development of small, resource constrained devices called Sensor Nodes (SNs). Performance of Sensor Node is highly dependent on the effective and efficient usage of the available limited resources with it, leading to maximum lifetime of Wireless Sensor Network (WSN) which is a primary concern of WSNs. The depletion of a SN energy leads to change in topology of WSNs often over a period of time. Therefore, protocols which consider the dynamic nature of WSNs are crucial for improving the network lifetime. In this paper, we propose bio inspired Ant Colony optimization based Self healing routing scheme inspired by swarm Intelligence technique to improve lifetime of a WSN.