The dynamic routing algorithm for renewable wireless sensor networks with wireless power transfer

Wireless sensor networks area collection of a large number of unattended sensor nodes. The sensor nodes are dynamically deployed in the region. In wireless sensor networks, the unlicensed sensor nodes use their temporarily available vacant licensed channels or spectrum band in a telecommunication network. The many open challenges with issues such as adaptive in self-organisation, fault-tolerance and network scalability with cooperative spectrum sensing and sharing are identifying new challenges in wireless sensor networks. In this paper, we proposed the bio-inspired adaptive routing algorithm for cognitive radio wireless sensor networks. The utilisation of the foraging approach of ANTs and BEEs for making the decision of using the available spectrum sensing and sharing of channels over multi-hops communication, provides the method to utilise idle channel and decrease the delay for communication in wireless sensor network. In this paper, we design the algorithm to solve the issue of wireless sensor network and performance of classical routing protocol LEACH and cognitive radio sensor networks (CRSN) evaluates the parameters which proof the self-organisation routing algorithm.

Recent breakthrough in the wireless energy transfer have attracted attention of the researchers due to its potential to prolong the lifetime of Wireless Sensor Networks (WSNs) and to eliminate energy bottlenecks. Through wireless charging vehicles sensor node's energy can be replenished periodically by using Wireless Charging Vehicles (WCVs). However, for a large scale WSN, the capacity of WCVs, positioning and coordination between them, and limited resources of WCVs have to be considered to implement a scalable charging system. Additionally, creating an efficient charging route for the WCVs considering the dynamic energy consumption of sensor nodes is also crucial. Since, WCVs have limited capacity and low system resources, the classic TSP-based Optimization algorithms, which requires high-performance computing, are not suitable for them. In this paper, we proposed GHSC (Guided Hilbert for Specified Cluster), which is based on the Hilbert space filling curve. We consider a clustered WSN with multiple WCVs, where each cluster is assigned to a single WCV. GHSC creates a primary charging route by considering a cluster as an unit square and dividing the square into small sub-squares. As the Hilbert curve goes through each sub-squares, the algorithm assigns a rank for each of them based on their position along the curve. The algorithm then map the nodes into vertices of the sub-squares and rank the nodes as well. Once ranking is done, the algorithm creates a charging route based on the node's ranking. This heuristic approach of the GHSC algorithm can find effective charging tours for the WCVs with a time complexity of (O(n log n) + Ω(nk)). Compared to other Global Optimization algorithms, GHSC was able to find tours, which was at most a logarithmic factor longer than the shortest tour.

Popularity of Mobile Wireless Sensor Network (MWSN) has increased tremendously due to the ability to connect the physical world with the virtual world. In MWSN, Sensor nodes move freely in a target area without the need of any special infrastructure. MWSN has attracted many researchers as it has introduced unique challenges in aspects like resource management, coverage, routing protocols, security in many applications such as target tracking in military applications, detection of catastrophic events, environment monitoring, health applications etc. Due to mobility, routing process in MWSN has become more complicated as connections in the network can change dynamically. This paper proposes a Mobility-Aware Multi-Objective Hybrid Routing Algorithm (MMOHRA) for Wireless Sensor Network (WSN). MMOHRA selects the best route and forwards the data packets from source to sink using multiple metrics such as Average Energy consumption, Control Overhead, Reaction Time, LQI, and HOP Count. Performance of MMOHRA is compared with Simple Hybrid Routing Protocol (SHRP) and Dynamic Multi-objective Routing Algorithm (DyMORA) using metrics such as Average Energy Consumption, Packet Delivery Ratio, and Jitter. MMOHRA improves the Average Energy Consumption (AEC) by a factor of 14.1% as compared with SHRP and 8.13 % as compared to DyMORA. MMOHRA outperformed SHRP and DyMORA in terms of packet Delivery Ratio (PDR) by 10.17 % and 9.83 % respectively.

A Wireless Sensor Network (WSN) is an emerging technology for a wide range of potential applications, including the environmental monitoring, medical, and target tracking systems. A WSN comprises a set of sensor nodes deployed in an area of interest. Sensor nodes are normally located in a dense and ad hoc manner, communicating each other in a multi-hop fashion in order to collect, process, and relay data. Most of WSNs are built on wireless, battery-powered sensor nodes. In such networks, it is hard to recharge or replace the energy-depleted nodes due to the desolate or harsh environment of the target area. Therefore, the efficient use of limited energy is a primary concern in designing protocols and usage strategies for WSNs. In this work an emergency scenario is considered and a WSN is used to monitoring the emergency area. To limit the power consumption, the WSN is activated only when the emergency occurs. Moreover an integrated protocol for routing and localization is developed to reduce communication, which is the most power-consuming operation in WSNs.

Automatic localization is one of the major issues in Wireless Sensor Networks (WSN). DV-hop algorithm is a well-known localization algorithm in WSN but with limited localization accuracy. In this paper, an improved DV-hop localization algorithm in hybrid optical wireless sensor networks is proposed based on the optimization of the parameters in WSN. Various factors that affect the localization accuracy of the DV-hop algorithm in WSN are investigated, including the communication radius of the node, the number of beacon nodes and the number of the total nodes. As the DV-hop algorithm is applied into hybrid optical sensor and WSNs (O-WSN) with rectangular topology, different parameters have to be optimized accordingly. Simulation results show that the square topology outperforms the rectangle topology more than 45 % under the same network parameters using the improved DV-hop algorithm. Therefore another improved DV-hop called Sub-Square Weighted DV-hop (SSW DV-hop) is proposed for the rectangle topology. Both simulation and experiment results demonstrate that applying the SSW DV-hop algorithmin O-WSNs could significantly improve the localization accuracy.

The wireless sensor networks (WSNs) are usually deployed among widely area for environmental monitoring, data collection and other applications. In order to reduce the energy consumption and extend the lifetime of WSNs, as well as receive the data quickly, a source-based data aggregation algorithm (SBDA) for clustering wireless sensor networks is proposed. The method aggregated the data from sensor nodes and marked different transmission priority for the data. Simulation results show that, compared to existing protocols, the proposed method achieves a longer life time, and a lower packet drop ratio.

With the advancement in the technology of wireless energy transfer based on magnetic resonant coupling, multiple nodes can be charged simultaneously. In this paper, we utilize this new breakthrough to transfer energy to sensor nodes in wireless sensor networks. We carry on the cellular structure in [4] to describe a wireless sensor network (WSN) and employ a wireless charging vehicle (WCV) periodically visiting each cell to charge nodes within it wirelessly. We propose a dynamic optimization model which is practical and feasible to forecast the departure time and charging time in each cell of the WCV. With the target of maximizing the time during which WCV stays at the service station, we develop two constraints as sufficient and necessary conditions to satisfy the energy requirement at each node and present through simulation how to schedule the WCV to accomplish its energy transfer tasks in a real-time WSN.

Recent years have witnessed a proliferation of routing algorithms for Wireless Sensor Networks (WSNs), hence complicating the choice of the proper algorithm to be used for a given application. Simulation frameworks represent a viable solution to anticipate crucial choices, however existing solutions do not encompass the impact of changes (e.g., route updates, node crashes) on the nodes behavior and vice-versa. This article proposes a novel adaptive modeling approach to master the complexity of the thorough simulation of routing algorithms for WSN. Experimental results are provided showing the effectiveness of the proposed approach at managing changes, and dealing with detailed aspects, during the simulation and comparison of several routing algorithms.

Recently, network localization systems that are based on inter-node ranges have received significant attention. Geographic routing has been considered an application which can utilize the location information from these localization systems. In this paper, we firstly recognize that sensor network localization algorithms generate positioning data with different error patterns compared to those networks where node positions are determined directly from GNSS measurements. Secondly, by simulating practical sensor network scenarios using data from our localization algorithm, we observe that existing geographic routing algorithms in wireless sensor networks (WSNs) adopt very simplistic methods in the treatment of position error, without due consideration of error distribution. Additionally, an insight is given into localization algorithms for WSNs with inhomogeneous error environments. Our observations represent an initial step toward a detailed understanding and design of efficient geographic routing algorithms in location aware WSNs.

One of the main emphases of the prevalent clustering and routing algorithms in wireless sensor networks is efficient energy utilization aimed towards enhanced network lifetime. In this paper we are proposing a clustering approach where the sensor nodes are clustered together based on a defined spatial correlation and the geographical location of each sensor nodes. The Cluster Head or Cluster Leader along with routing path is decided by our proposed algorithm based on the estimated chance-value during each rounds of data transfer. Thus in our scheme a multi-hop routing is effected wherein either two-level or three-level hops are dynamically chosen based on the spatial correlation existing between the nodes for the data transfer from the sensing node to the sink. It has been observed that our proposed algorithm outperforms the standard algorithms namely Low Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP) and Distributed Energy Efficient Clustering (DEEC) Protocol with regards to system throughput and Network Lifespan of WSN.

Energy efficiency is a key concern and challenging research issue during the design of routing algorithms for wireless sensor networks (WSNs). In order to effectively improve the energy utilization of each sensor node and network performance, mobility technology has been widely concerned. Since the implement of mobile sink node is relatively easier than normal sensor nodes, sink mobility technology has attracted much research interest in recent years. In this paper, we propose a mobile-sink routing algorithm based on energy and distance for WSNs. Trajectories of mobile sink nodes is predictable to improve energy efficiency of sensor networks. We first lay emphasis on the study of the selection of mobile sink node number and the selection of park positions, as well as their impact on energy consumption and network lifetime. Simulation results show that both the mobile sink nodes number and park positions have great influence on network performance, and our algorithm outperforms random movement and LEACH algorithm in terms of performance like energy consumption.

Utilization of energy and the lifetime increment are the big issues in designing of routing algorithms for wireless sensor networks (WSNs). Many routing algorithms have been developed by various researchers to achieve energy efficiency and to improve the lifetime of the network. But, the way to route the information from the sensor node (SN) to the base station (BS) and vice versa is an important issue, because of resource constraints. In this paper, we have proposed a low energy consumed, cluster-based routing protocol named an energy-efficient and double cluster-head routing (EEDCR) protocol, to increase the network lifetime and minimize the end-to-end delay. Selection of the cluster head (CH) is depending on random selection method, energy method, the total number of nodes, and its energy level. The performances of developed protocol were assessed using simulations and found that it provides successful outcomes in terms of energy-efficient and lifetime increment in routing for WSNs.

Energy balance is an important performance index in the design of routing algorithm for wireless sensor networks. A swarm intelligence optimization based routing algorithm for wireless sensor networks is proposed, whose kernel idea is taking less hop numbers into consideration and choosing the nodes with less pheromone as next hop to avoid some nodespsila prematurely exhausting their energy because of too concentrated routes through the nodes. The experiments show that the algorithm proposed in this paper is better than the directed diffusion routing protocol both in end-to-end delay and global energy balance and can effectively balance the global energy consumption and prolong the network lifetime.

Wireless sensor networks (WSN) have been widely used in urban network system and networked monitoring system, which provide easy connectivity and high physical data rate. Considering the battery-limited property of sensor nodes, recently, energy harvesting (EH) technology is introduced into WSN, which can alleviate traditional WSN problems (energy consumption, energy equilibrium, transmission efficiency, etc.). Current EH-WSN routing algorithms generally use the continuous energy harvesting mode, therefore, how to design an efficient routing algorithm for discrete energy harvesting mode and ensure the overall energy balance and conservation is still a great challenge and needs to be solved. Especially, under the mobile environment, the impact of route stability needs to be considered, which makes the design more complicated. To address the above problems, we propose a learning automata (LA) theory based stable and energy-efficient routing algorithm for discrete EH-mobile WSN (DEH-LA-SERA, for short). Firstly, we construct a multi-factors measurement model for sensor nodes, which contains node stability model, energy ratio function, expected harvesting energy model (using Markov decision process method) and direction judgement model. On this basis, we derive the node weighted value, i.e., selecting probability, which can be used to determine whether a node can be chosen as relay node. Secondly, with the help of LA theory, we construct a feedback mechanism to adjust the optimal path. With this solution, we can ensure the overall energy balance and conservation while holding the stability of selected path. As demonstrated in simulation experiments, our algorithm, DEH-LA-SERA, achieved the best performance in route survival time, energy consumption, energy balance and acceptable performance in end-to-end delay and packets delivery ratio.


 
 
 Cluditem is a routing algorithm for wireless sensor networks developed for applications of environmental monitoring with periodic measurement of variables. These applications tolerate a maximum phase shift of the clocks of nodes in the order of milliseconds. This paper proposes two centralized synchronization schemes that introduce a limited processing load. The objective of the work was to assess the impact on the energy consumption of the incorporation of synchronization techniques described. Simulations of the full communication protocol were conducted in the NS2 environment and a comparative study of results was performed. This study showed that the first proposed schema is more convenient with respect to energy consumption, when the area to monitor has reduced dimensions. On the other hand, the second scheme, although it permits to work in larger areas, introduces a decrease in the network lifetime in the order of 14%.