Decrease In Network Lifetime Research Articles

Pegasis Double Cluster Head Hybrid Congestion Control in Wireless Sensor Networks

Wireless sensor network (WSN) is the fastest growing technology that dominates the future world into wireless communication. It is a collection of a number of self-governing sensor nodes responsible to sense, process and manipulate the nodes. The sensor nodes are regulated by a battery where the network gets failed if the battery is dead. Thus, energy is an important factor to be efficiently used. Furthermore, congestion occurs in WSN when the incoming traffic load exceeds the capacity of the network. The major factors that lead to congestion are buffer overflow, varying rates of transmission, packet collision, and many-to-one data transmission. Due to these, the network suffers from packet loss, queuing delay, end-to-end delay, decrease in network lifetime, and increase in energy consumption. Hence, a clustering-based routing protocol is introduced in this paper to improve the performance of the network and reduce congestion. In the proposed method, Power-Efficient Gathering in Sensor Information Systems (PEGASIS) double cluster head with artificial neural network (ANN) is utilized to analyze the overall network lifetime. The proposed technique is comprised of four phases: clustering the network nodes, cluster head (CH) selection, chain formation, and secondary CH (SCH) selection. The sensor nodes are initially clustered with the firefly algorithm in which the cluster heads of each node are elected via an artificial neural network. Meanwhile, chain formation is processed by PEGASIS double cluster head (PDCH) and the SCH is selected through grey wolf optimizer (GWO) to afford equivalent energy utilization between the sensor nodes. The simulation outcomes proved that the proposed method efficiently increases the lifetime of the network and reduces congestion level in WSN.

Heed Protocol Using A Cluster Based V2V Communication

Objectives: Wireless sensor Networks employs a set a sensor nodes to monitor the parameters of the environment. The sensory information collected by the sensor nodes can be retrieved with the help of Mobile Nodes fixed upon vehicles. Existing scenarios engage both single-hop data transfer from Sensor nodes that lie within the mobile network range or profound participation of network margin nodes. These nodes are at the peril of quick energy collapse resulting in loss of network connectivity and decrease in network lifetime. The main idea behind this paper is to enhance the network lifetime and security. Methods/Statistical Analysis: The proposed HEED (Hybrid energy efficient Distributed Clustering) protocol reduces the overall network operating cost and energy disbursement associated with the multi hop data recovery process while also ensuring fair energy utilization among Sensor nodes and prolonged network lifetime. In multi hop network, the nodes closer to the sink node are involved in almost all data transmission, hence their energy would be quickly drained out. Since the energy depletion at sink node is more than other nodes, energy holes are created. Therefore other nodes in the VANET are disconnected from the network which reduces the network lifetime. To enhance network lifetime routing protocols are introduced in addition to HEED protocol which provides efficient clustering. To improve the security Intrusion-Tolerant Routing protocol (INSENS) protocol is used, which uses multipath technique in order to make the network resilient to attacks. Findings: The proposed HEED protocol elects the cluster head periodically based on a metric which is based on parameters like residual energy of the node, closeness of its neighbors and the degree of the node. The number of iterations involved in HEED protocol is very less and it achieves literally consistent distribution of cluster head allotment across the network involving a low level of information overhead. With suitable limits on node density, intra and inter cluster transmission ranges, this protocol can assure connectivity of clustered networks. Simulation results prove that this protocol is efficient in enhancing the lifetime of the network and sustaining scalable data aggregation. In case of Distributed clustering algorithms it is the responsibility of the base station to collect the information gathered by the cluster heads. In this work each and every sensor node broadcasts it accessibility to its surrounding. Based on the broadcast information the cluster head belonging to the specific cluster is identified in parallel. INSENS protocol is used to enhance network security. Simulation results prove that this protocol is efficient in enhancing the security of the network. Application/Improvements: This study proposes centralized, HEED_INSENS protocols to solve the coverage problem in VANETs. It is also useful for applications that require data aggregation and those where all data originated from sources should reach the sink without prior aggregation. Keywords: Sensor Nodes, Network Overhead, Network Lifetime, HEED, INSENS

Universal and Dynamic Clustering Scheme for Energy Constrained Cooperative Wireless Sensor Networks

Energy conservation is considered to be one of the key design challenges within resource constrained wireless sensor networks that leads the researchers to investigate energy efficient protocols with some application specific challenges. Dynamic clustering is generally considered as one of the energy conservation techniques; but unbalanced distribution of cluster heads, highly variable number of sensor nodes in the clusters and high number of sensor nodes involved in event reporting tend to drain out the network energy quickly resulting premature decrease in network lifetime. In this paper, a dynamic and cooperative clustering and neighborhood formation scheme is proposed that is expected to evenly distribute energy demand from the cluster heads and optimize the number of sensor nodes involved in event reporting. Assuming multiple sensors will form a cluster, while responding to an event to report to the fusion center. However, all the sensor nodes are assuming to report the sensing parameters to a cluster-head; which are to be summarized and then report it to fusion center. The transmission of the same event data from multiple sensors within the cluster at different distances with single or multiple antennas to the cluster-head with similar antenna characteristics can be realized as multiple-input multiple-output (MIMO) channel set up as found in the literature. Such realization among clusters of MIMO channel and existence of a feedback channel between the clusters and fusion center is the key of the proposed framework. The dynamic behavior has been adopted within the framework with a proposed index derived from the received measure of the channel quality, which has been attained through the feedback channel from the fusion center. The dynamic property of the proposed framework makes it robust against time-varying behavior of the propagation environment. The proposed framework is independent of the nature of the sensing application, providing with universal behavior. From simulation results, it is observed that the proposed clustering scheme enhances network lifetime by 24.5% and 36% as compared to existing schemes e.g. DDEEC and EDDEEC respectively. Furthermore, it is validated by simulation results that the proposed framework provides a trade-off model between network lifetime and transmission reliability.

A Location-Wise Predetermined Deployment for Optimizing Lifetime in Visual Sensor Networks

Visual sensor networks are receiving significant attention due to their potential applications ranging from surveillance to tracking domains. Nevertheless, due to the funneling effect, the unbalanced energy usage among visual sensor nodes (SNs) increases and leads to premature decrease in network lifetime. First, considering Rayleigh fading channel and routing models, we analyze the optimization of network lifetime by balancing the energy consumption among different SNs. From the analysis, it is revealed that the number of SNs and relay nodes and their locations have significant influence on limiting the energy hole problem and optimization of network lifetime. Based on the derived principle of energy balancing, we develop a heterogeneous SNs deployment strategy leading to optimization in network lifetime. Exhaustive simulation is performed, primarily to measure the extent of achieving our design goal of optimizing network lifetime while attaining energy balancing. We also measure the effect of placement errors on the performance and robustness of the scheme. The results show that even in the presence of placement error the performance is comparable and provides better robustness compared with the competing scheme. Further, the simulation results show that our scheme does not compromise with other performance metrics, e.g., end-to-end delay and throughput, while achieving the design goal. Finally, all the comparative results confirm our scheme’s supremacy over the competing schemes.

Lifespan prolonging location-wise predetermined deployment strategy for visual sensor networks

Visual sensor networks are widely used for surveillance, environmental monitoring and tracking. However, due to the funneling effect, visual sensor nodes (SNs) close to the sink tend to deplete their energy sooner than SNs farther away from the sink resulting in energy hole problem. This energy hole problem significantly increases the unbalanced energy usage among SNs and leads to premature decrease in network lifetime. Initially, we analyzed network lifetime and found number of relay nodes and their location has significant influence on limiting the energy hole problem and enhancement of network lifetime. Based on the principle of energy balancing, derived from this analysis, we develop a heterogeneous SNs deployment strategy leading to an enhancement of network lifetime. Exhaustive simulation is performed, primarily to measure the extent of achieving our design goal of limiting memory and computation overheads, enhancing network lifetime while attaining energy balancing. We also measure the effect of placement errors on the performance and show that even in presence of placement error the performance is comparable with the other competing scheme. Further, the simulation results show that our scheme does not compromise with other network performance metrics such as end-to-end delay and throughput while achieving the design goal. Finally, all the results are compared with a competing scheme and the results confirm our scheme׳s supremacy in terms of both design performance metrics as well as network performance metrics.

Impact of Limiting Hop Count on the Lifetime of Wireless Sensor Networks

In this study, we present a novel family of mixed integer programming (MIP) models to analyze the effects of limiting hop count on Wireless Sensor Network (WSN) lifetime. We performed analysis to uncover the trade-off between minimizing the number of hops and maximizing the network lifetime by exploring the parameter space through numerical evaluations of the optimization models. Our results reveal that minimum hop routing leads to significant decrease in network lifetime (up to 40%) when compared to the maximum network lifetime obtained without any restrictions on hop count. However, the decrease in network lifetime is negligible if the minimum hop routing criterion is modestly relaxed ( e.g ., 3% decrease in network lifetime is possible if the minimum hop count is increased by 15%).

에너지 효율적 무선 센서 네트워크를 위한 Strike and Bargaining 라우팅 기법

In order to resolve the energy efficiency in wireless sensor networks, a multihop transmission technique is utilized. However, multihop transmission in wireless sensor networks (WSN) has pros and cons. It reduces total energy consumption, while it may cause a severe decrease in network lifetime. To solve this problem, we suggest the so called strike and bargaining algorithm (SBA). The routing path is determined by wages of nodes. Each node negotiates its wage with their neighbor nodes and determine a reasonable value to reach a optimally balanced point. By analysis and simulations, we show SBA can achieve a near optimal solution.