Improved Energy Aware Cluster based Data Routing Scheme for WSN

Wireless sensor network (WSN) consists of several tiny devices that are dispersed randomly for gathering network field. Clustering mechanism divides the WSN into different sub-regions called clusters. Individual cluster is consisting of cluster head (CH) and member nodes. The main research challenges behind clustering mechanism are to optimize network overheads with efficient data delivery. Sensor nodes are operated by batteries and practically it is not feasible to replace them during sensing the environment so energy should be effectively utilized among sensors for improving overall network performance. This research paper presents an improved energy aware cluster based data routing (i-ECBR) scheme, by dividing the network regions into uniform sized square partitions and localized CH election mechanism. In addition, consistent end-to-end data routing is performed for improving data dissemination. Simulation results illustrate that our proposed scheme outperforms than existing work in terms of different performance metrics

Grid Based Cluster Head Selection Mechanism for Wireless sensor network

Wireless sensor network (WSN) consists of hundred to thousands sensor nodes to gathered the information from physical environment. Different clustering based algorithms have been proposed to improve network lifetime and energy efficiency. Practically it is not feasible to recharge the battery of sensor nodes when they are sensing the data. In such situation energy is crucial resource and it should be improved for life span of WSN. Cluster head (CH) has an important role in hierarchical energy efficient routing protocols because it receives data from nodes and sends towards base station (BS) or sink node. This paper presents a grid based cluster head selection (GBCHS) mechanism by dividing the network field into MXN uniform size partitions that aims to minimize the energy dissipation of sensor nodes and enhancing network lifetime. Simulation experiments have been performed in network simulator (NS2) that show our proposed GBCHS approach outperformed than standard clustering hierarchy LEACH protocol

The Dynamics of Vehicular Networks in Urban Environments

Vehicular Ad hoc NETworks (VANETs) have emerged as a platform to support intelligent inter-vehicle communication and improve traffic safety and performance. The road-constrained, high mobility of vehicles, their unbounded power source, and the emergence of roadside wireless infrastructures make VANETs a challenging research topic. A key to the development of protocols for inter-vehicle communication and services lies in the knowledge of the topological characteristics of the VANET communication graph. This paper explores the dynamics of VANETs in urban environments and investigates the impact of these findings in the design of VANET routing protocols. Using both real and realistic mobility traces, we study the networking shape of VANETs under different transmission and market penetration ranges. Given that a number of RSUs have to be deployed for disseminating information to vehicles in an urban area, we also study their impact on vehicular connectivity. Through extensive simulations we investigate the performance of VANET routing protocols by exploiting the knowledge of VANET graphs analysis.Comment: Revised our testbed with even more realistic mobility traces. Used the location of real Wi-Fi hotspots to simulate RSUs in our study. Used a larger, real mobility trace set, from taxis in Shanghai. Examine the implications of our findings in the design of VANET routing protocols by implementing in ns-3 two routing protocols (GPCR & VADD). Updated the bibliography section with new research work

Average Case Network Lifetime on an Interval with Adjustable Sensing Ranges

Given n sensors on an interval, each of which is equipped with an adjustable sensing radius and a unit battery charge that drains in inverse linear proportion to its radius, what schedule will maximize the lifetime of a network that covers the entire interval? Trivially, any reasonable algorithm is at least a 2-approximation for this Sensor Strip Cover problem, so we focus on developing an efficient algorithm that maximizes the expected network lifetime under a random uniform model of sensor distribution. We demonstrate one such algorithm that achieves an expected network lifetime within 12 % of the theoretical maximum. Most of the algorithms that we consider come from a particular family of RoundRobin coverage, in which sensors take turns covering predefined areas until their battery runs out