E. Golden Julie

Development of Energy Efficient Clustering Protocol in Wireless Sensor Network Using Neuro-Fuzzy Approach.

Wireless sensor networks (WSNs) consist of sensor nodes with limited processing capability and limited nonrechargeable battery power. Energy consumption in WSN is a significant issue in networks for improving network lifetime. It is essential to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network lifetime. In this paper, a neuro-fuzzy energy aware clustering scheme (NFEACS) is proposed to form optimum and energy aware clusters. NFEACS consists of two parts: fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. NFEACS used neural network that provides effective training set related to energy and received signal strength of all nodes to estimate the expected energy for tentative cluster heads. Sensor nodes with higher energy are trained with center location of base station to select energy aware cluster heads. Fuzzy rule is used in fuzzy logic part that inputs to form clusters. NFEACS is designed for WSN handling mobility of node. The proposed scheme NFEACS is compared with related clustering schemes, cluster-head election mechanism using fuzzy logic, and energy aware fuzzy unequal clustering. The experiment results show that NFEACS performs better than the other related schemes.

Energy Aware Clustering Scheme in Wireless Sensor Network Using Neuro-Fuzzy Approach

Nowadays sensor plays an important role in the day today life. People uses wireless technology along with sensor for monitoring home held devices, security alerts, natural disasters alert, building supervision, industrial quality management, etc. Wireless Sensor Network (WSN) consists of thousands of economical and feasible disposable sensors, deployed in the environment to sense parameters related to the surroundings such as temperature, moisture level, pressure etc., Number of sensor nodes are connected in these networks for communication. Each nodes are self-organized, having the capacity of sense, process, and aggregate data. Energy utilization in WSN is major issue in networks for improving network lifetime. Conventional clustering schemes are created with static cluster heads that die past than the normal nodes that degrade the network performance in routing. It is very vital area to develop an energy aware clustering protocol in WSN to reduce energy consumption for increasing network life time. In this paper, a Energy Aware Clustering using Neuro-fuzzy approach (EACNF) is proposed to form finest and energy aware clusters. The proposed scheme consists of fuzzy subsystem and neural network system that achieved energy efficiency in forming clusters and cluster heads in WSN. EACNF used neural network that provide effective training set related to energy and density of all nodes to estimate the expected energy for Uncertain cluster heads. Sensor nodes with higher energy are trained with various location of base station to select energy aware cluster heads. Fuzzy if–then mapping rule is used in fuzzy logic part that inputs to form clusters and cluster heads. EACNF is designed for WSN that handling Trust factor for security to the network. EACNF used three metric such as transmission range, residual energy and Trust factor for improving network life time. The proposed scheme EACNF is compared with related clustering schemes namely Cluster-Head Election Mechanism using Fuzzy Logic and Energy-Aware Fuzzy Unequal Clustering. The experiment results show that EACNF performs better than the other related schemes.

Performance Analysis of Energy Efficient Virtual Back Bone Path Based Cluster Routing Protocol for WSN

Wireless sensor networks consist of hundreds and thousands of nodes which are deployed to sense parameters related to the surroundings such as temperature, moisture level, pressure etc. Network topology and energy consumption are important issue in WSN for improving network performance in critical applications. The cluster-based routing is the best way to decrease energy consumption by reducing the number of hops to transmit messages to the sink node. The cluster heads are responsible for gathering data from cluster members and forwarding them to the base station. Hence the cluster heads are expected to be more energy efficient compared to other sensor nodes. LEACH is the popular cluster-based routing protocol in which cluster heads are selected on a rotation basis. It is based on the assumption that sensor nodes can directly communicate with the sink node. We propose a CCE Virtual Backbone cluster-based routing protocol to overcome this assumption by selecting cluster heads using generated Virtual back bone path with multi-hop routing protocol. Virtual back bone path calculation is based on the parameters like message success rate, communication cost, and maximum connectivity. It is proved that our protocol highly reliable energy efficient and increase the life time of the network.

SMR: A Synchronized Multipath Re-broadcasting Mechanism for Improving the Quality of Conversational Video Service

Multipath broadcasting is the one solution for conversational video broadcasting to increase the bandwidth of end-to-end systems and increase the video quality. Conversely, traditional multipath broadcasting methods are not appropriate for conversational video service delivery due to the high amount of duplicated packets that causes the delay in service. In this proposed work, rebroadcasting technique is used to assure the reduced amount of delay with the low packet loss. Delay is the main problem of rebroadcasting technique. A Synchronized Multipath Re-broadcasting mechanism (SMR) is proposed to improve the performance of rebroadcasting. A lot of other mechanisms are implemented to rebroadcast the non broadcasting packets in a best way. SMR scrutinizes and evaluates the delay and bandwidth of every packet. SMR will differ for dissimilar structures of packet loss. At last, SMR rebroadcasts the important elements of video stream information over other path with available parameters of decoding limit, rebroadcasting interruption and feature of video flow. SMR is a dependable multipath rebroadcasting mechanism for conversational video service and is estimated by simulations. The Simulation results prove that SMR is an efficient way to increase the QoS for the broadcast of conversational video service.Multipath broadcasting is the one solution for conversational video broadcasting to increase the bandwidth of end-to-end systems and increase the video quality. Conversely, traditional multipath broadcasting methods are not appropriate for conversational video service delivery due to the high amount of duplicated packets that causes the delay in service. In this proposed work, rebroadcasting technique is used to assure the reduced amount of delay with the low packet loss. Delay is the main problem of rebroadcasting technique. A Synchronized Multipath Re-broadcasting mechanism (SMR) is proposed to improve the performance of rebroadcasting. A lot of other mechanisms are implemented to rebroadcast the non broadcasting packets in a best way. SMR scrutinizes and evaluates the delay and bandwidth of every packet. SMR will differ for dissimilar structures of packet loss. At last, SMR rebroadcasts the important elements of video stream information over other path with available parameters of decoding limit, rebroadcasting interruption and feature of video flow. SMR is a dependable multipath rebroadcasting mechanism for conversational video service and is estimated by simulations. The Simulation results prove that SMR is an efficient way to increase the QoS for the broadcast of conversational video service.

Cluster based Routing in Sensor Network using Soft Computing Techniquies: A Survey

Research in Wireless Sensor Networks (WSNs) has gained importance in the recent years. These networks are battery driven and are usually deployed in hazardous or isolated areas. The main objective of these networks is to collect environmental data and forward it to the base station. Hence routing has become an important area of research. Energy efficiency and timely delivery of sensed data are critical criteria for these networks. The position of sensor nodes should not be pre-determined. Clustering is a key method used to extend the lifetime of a sensor network. It has many applications, such as building supervision, industrial quality management, and environmental monitoring. The characteristics of WSNs are Low energy usage, Dynamic network operations and autonomous process of networks. Soft computing techniques can be incorporated to achieve better performance. This paper surveys the recent trends in routing contain fuzzy logic and Neuro fuzzy logic based clustering techniques and presents a comparative study of the various approaches.

Reliable Virtual Cluster-Based Opportunistic Routing Protocol for Mobile Ad hoc Networks

Geographic opportunistic routing protocols overcome the failure of traditional routing protocols which fail due to the dynamic nature of mobile ad hoc networks. When link stability is considered for forwarder selection, the hop count and delay become unpredictable. Hence, a new protocol, delay-aware cluster-based opportunistic Routing (DACOR) protocol, has been proposed. In DACOR, nodes with high transmission range form loose clusters with surrounding nodes. When such high-power nodes are not available, nodes with lower transmission range enable the routing process by opportunistically selecting the best forwarder based on link stability. When no neighbors are found, a routing hole handling mechanism is also proposed. Simulation results show that the presence of high transmission nodes reduces the hop count, thus ensuring low delay, and opportunistic routing guarantees reliable data delivery.