Density Controlled Divide-and-Rule Scheme for Energy Efficient Routing in Wireless Sensor Networks

Cluster based routing technique is most popular routing technique in Wireless Sensor Networks (WSNs). Due to varying need of WSN applications efficient energy utilization in routing protocols is still a potential area of research. In this research work we introduced a new energy efficient cluster based routing technique. In this technique we tried to overcome the problem of coverage hole and energy hole. In our technique we controlled these problems by introducing density controlled uniform distribution of nodes and fixing optimum number of Cluster Heads (CHs) in each round. Finally we verified our technique by experimental results of MATLAB simulations.Comment: 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE2013), Regina, Saskatchewan, Canada, 201

On Modeling Geometric Joint Sink Mobility with Delay-Tolerant Cluster-less Wireless Sensor Networks

Moving Sink (MS) in Wireless Sensor Networks (WSNs) has appeared as a blessing because it collects data directly from the nodes where the concept of relay nodes is becomes obsolete. There are, however, a few challenges to be taken care of, like data delay tolerance and trajectory of MS which is NP-hard. In our proposed scheme, we divide the square field in small squares. Middle point of the partitioned area is the sojourn location of the sink, and nodes around MS are in its transmission range, which send directly the sensed data in a delay-tolerant fashion. Two sinks are moving simultaneously; one inside and having four sojourn locations and other in outer trajectory having twelve sojourn locations. Introduction of the joint mobility enhances network life and ultimately throughput. As the MS comes under the NP-hard problem, we convert it into a geometric problem and define it as, Geometric Sink Movement (GSM). A set of linear programming equations has also been given in support of GSM which prolongs network life time

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

A Detailed Overview of Life Cycle Enhancing Approaches for WSN

The major target of a wireless sensor network (WSNs) is to amass related data in the form of packets from the physical world. Transmission of these packets towards lengthier route consumes extra battery, and amplification and causes more intervening. As a result, these variables limit the lifespan of the network and operational ability. Numerous techniques exist in the past to augment the lifespan of the WSN. In this paper we have analyzed state of art techniques which enhance the lifecycle of a WSN