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Energy Hole Minimization Techniques in Wireless Sensor Networks
Abstract and Figures
Revolutionary development in integrated circuit miniaturisation facilitates the in-volvement of electronic sensors in every aspect of our life. This involvement results in a wide range of Wireless Sensor Network (WSN) applications in terrestrial, underwater and health care. However, small size poses power limitation on these sensors. In order to conserve their energy, energy efficient strategies are needed at all layers of network model. However, this dissertation focuses on energy hole analysis and proposition of energy efficient solutions in WSNs (terrestrial, underwater,
and body area) at the network layer only.
In terrestrial WSNs, we identify that uneven number of Cluster Heads (CHs) selection is the major cause of uneven cluster size. This uneven cluster size leads to imbalanced energy consumption of sensors (nodes) in the network, which ultimately leads to creation of energy hole. In order to cope with this issue, we propose two energy efficient routing techniques; Density Controlled Divide-and- Rule (DDR) and Divide-and-Rule (DR). These techniques logically divide the network area into static clusters (regions) and nodes are randomly distributed in these regions. The two techniques differ in terms of regions’ formation and nodes’ association with CH(s). In Wireless Body Area Networks (WBANs), limited number of nodes are placed on the human body, and typically, three communication modes are used; direct, intermediate node based, and cluster based. In this regard, our contribution factors in a detailed energy consumption analysis. Analytical and experimental analysis reveals important results regarding energy consumption of these techniques. In UWSNs, we propose two techniques; Delay Intolerant Energy Efficient Routing (DIEER) with sink mobility and Spherical Hole Repair Technique (SHORT). In DIEER, we analyze energy consumption of nodes in Depth Based Routing (DBR) techniques and devise an optimised way of forwarder node selection. On the other hand, SHORT’s energy hole analysis reveals that knowl- edge acquisition phase of DBR, and static transmission power level are the major contributors in nodes’ energy consumption. We devise a solution to repair the coverage holes which are created due to regular death of nodes. The simulation results show that our newly proposed techniques perform better than the selected existing ones in terms of the selected performance metrics.
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The Internet of Things (IoT) network is typified by deployments such as a Wireless Sensor Network (WSN). These WSN's are commonly deployed within a target area for a specific task such as farm monitoring and asset movement control. A group of sensors are typically led by a Personal Area Network Coordinator (PANC). In some situations like in large scale greenhouse monitoring, mobile PANC are required to eliminate energy-hole issues and hence improve the performance of the WSN. The energy-hole issue is a problem caused by the depleted cluster head nodes. In this paper we analyse the performance of a WSN with a mobile PANC. Using inputs from previous empirical studies we designed a scenario of a mobile PAN coordinator using a simulation package. The performance was evaluated. The mobile PANC speed and contact time is monitored and the average network throughput and delay are measured. Based on an analysis of these results a comprehensive set of guidelines are provided for operators of IoT networks. These guidelines optimise the network performance and ultimately lead to cost savings for network providers.
Underwater wireless sensor network (UWSN) features many unique characteristics, including slow propagation speed, high end-to-end delay, low available bandwidth, variable link quality, and energy constraint. All these problems pose a big challenge to devise a transmission efficient, energy-saving, and low delay routing protocol for UWSNs. In this paper we devise a relative distance based forwarding (RDBF) routing protocol, which aims to provide transmission efficient, energy-saving, and low delay routing. We utilize a fitness factor to measure and judge the degree of appropriateness for a node to forward the packets. Under the limitations of the fitness factor, RDBF can confine the scope of the candidate forwarders and find the beneficial relays to forward packets. In this way, only a small fraction of nodes are involved in forwarding process, which can distinctly reduce the energy consumption. Moreover, using only the selected beneficial nodes as forwarders can both enhance the transmission efficiency and reduce the end-to-end delay. This is because the distances of these nodes to the sink are the shortest and the hop counts of routing paths consisted by these nodes are minimum. We use the ns-2 based simulator to conduct our experiment; the results show that RDBF performs better in terms of packet delivery ratio, end-to-end delay, and energy efficiency.
The underwater acoustic channel is characterized by a path loss that depends not only on the transmission distance, but also on the signal frequency. As a consequence, transmission bandwidth depends on the transmission distance, a feature that distinguishes an underwater acoustic system from a terrestrial radio system. The exact relationship between power, transmission band, distance and capacity for the Gaussian noise scenario is a complicated one. This work provides a closed-form approximate model for 1) power consumption, 2) band-edge frequency and 3) bandwidth as functions of distance and capacity required for a data link. This approximate model is obtained by numerical evaluation of analytical results which takes into account physical models of acoustic propagation loss and ambient noise. The closed-form approximations may become useful tools in the design and analysis of underwater acoustic networks.
In wireless sensor networks, random deployment of nodes may cause serious coverage overlapping among the nodes and the original network may suffer severe coverage problems due to death of the nodes after deployment. In this paper, efficient distributed coverage hole repair algorithms are proposed taking density of the nodes in the post deployment scenario. The proposed algorithms consider limited mobility of the nodes and can select the mobile nodes based on their degree of coverage overlapping. In order to repair coverage holes of the network, nodes with higher degree of density are moved to maintain uniform network density without increasing the coverage degree of the neighbors of a mobile node. Simulation results show that the energy consumption due to mobility of nodes is least as compared to other similar protocols of the Wireless Sensor Networks. Besides, it is observed that substantial amount of coverage overlapping can be minimized and percentage of coverage of the holes can be maximized.
Random mobility and energy constraint are two main factors affecting system performance in mobile sensor networks, which cause many difficulties to system design. It is necessary to develop high-efficiency algorithms and protocols for mobile sensor networks to adapt to dynamic network environment and energy limitation. In this paper, a new clustering algorithm based on residual energy difference ratio is presented to improve system performance. Firstly, it is an energy-efficient algorithm. The residual energy of sensor nodes and average residual energy of system are considered in the residual energy difference ratio, which effectively avoid the nodes with low residual energy being selected as cluster heads. An energy-optimal scheme is used in cluster formation phase to minimize energy consumption. Secondly, it is a dynamic algorithm. The system dynamically clusters the sensor nodes according to the data transmission delays. It makes the whole system adapt to the random mobility of sensor nodes. The NS2 software is used to simulate the new clustering algorithm. The simulation experiments can verify the validity of the proposed theory.
Wireless Sensor Networks (WSNs) can benefit from ad hoc networking technology characterized by multihop wireless connectivity and infrastructure less framework. These features make them suitable for next-generation networks to support several applications such M2M applications for smart cities and public safety scenarios. Pivotal design requirements for these scenarios are energy efficiency, since many of these devices will be battery powered placing a fundamental limit on network, and specifically node lifetime. Moreover, the way in which traffic is managed also influences network lifetime, since there is a high probability for some nodes to become overloaded by packet forwarding operations in order to support neighbour data exchange. These issues imply the need for energy efficient and load balanced routing approaches that can manage the network load and not only provide reduced energy consumption on the network but also prolong the network lifetime providing robust and continuous. This work proposes a new energy efficient and traffic balancing routing approach that can provide a weighted and flexible trade-off between energy consumption and load dispersion. Simulation results show that the proposed protocol achieves high energy efficiency, decreases the percentage of failed nodes due to lack of battery power, and extends the lifespan of the network.
Node localization in wireless sensor networks is one of the key technologies as it plays a critical role in many applications. By the analysis of localization algorithm based on support vector machine, and using the classification function of SVM and combined with the RSSI(Received Signal Strength Indicator) location algorithm, a new localization algorithm based classification is proposed in the paper. The location area is firstly divided into densely populated regions and sparse regions by SVM, and then different algorithms are used to realize the localization, this can save computation and improve the accuracy. Simulation results show that the algorithm works well, and the algorithm ensures the algorithm complexity in the case of increased positioning accuracy.
As for cluster-based wireless sensor networks (WSNs), cluster lifetime is one of the most important subjects in recent researches. Besides reducing the energy consumptions of the clusters, it is necessary to make the clusters achieve equal lifetimes so that the whole network can survive longer. In this paper, we focus on the cluster lifetimes in multi-hop WSNs with cooperative multiinput single-output scheme. With a simplified model of multi-hop WSNs, we change the transmission schemes, the sizes and transmission distances of clusters to investigate their effects on the cluster lifetimes. Furthermore, linear and uniform data aggregations are considered in our model. As a result, we analyze the cluster lifetimes in different situations and discuss the requirements on the sizes and transmission distances of clusters for equal lifetimes.
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.
Wireless Sensor Networks lifetime mainly depends on energy saving efficiency. In this paper, we propose an energy-efficient self-stabilizing topology control protocol for WSN. We reduce the transmission power of each node so as to maintain network connectivity while saving maximum energy. Besides, we propose an approximation algorithm for minimum weighted connected dominating set that builds a virtual backbone formed by sensors with maximum energy. This backbone is used for efficient routing purpose. We proved the algorithm correctness and through our simulation results, we showed the efficiency of our proposed solution.