Power Aware Differentiated Routing (PADR) in Wireless Sensor Networks


 
 
 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%.
 
 

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.

Routing algorithms for large-scale sensor networks should be capable of finding energy efficient paths to prolong the lifetime of the networks in a decentralized manner. With this respect, Ant System has several proper characteristics for routing algorithm in large-scale wireless sensor networks. First, its distributed mechanism enables routing algorithm to find a solution with only local information and be robust for uncertainties in wireless sensor networks. Second, the framework of the Ant System is proper to solve dynamic problems such as routing problem. Transition probability in Ant System can be used to estimate how good a given routing path is. Capturing these features, this work proposes two Ant Systems based routing algorithms, which are AS-RWSNs (Ant System for Routing in Wireless Sensor Networks) and SAAS-RWSN (Structure-Aware AS-RWSN). The AS-RWSN applies the original Ant System to routing algorithm for wireless sensor network and SAAS-RSN upgrades AS-RWSN with considering properties of network structure such as degree of node. In SAAS-RSN, sensors with high node degree have high data traffic since they have more routing paths. Consequently, SAAS-RSN achieves an energy balance over sensor network through this routing scheme. We demonstrate the effectiveness of the proposed algorithms by comparing three existing routing algorithms.

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.

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.

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.

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.

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.

Appropriate clustering and routing algorithms in multi-hop wireless sensor networks considerably affect the energy consumption and prolong the network lifetime. Besides, the required inter-cluster communications in these networks may lead to imbalanced energy consumption among cluster-heads that in turn decreases the network lifetime. In this paper, a gradient-based clustering algorithm for energy-efficient routing (GCER) in wireless sensor networks is proposed. The main idea is based on partitioning the sensing region in such a way that the total energy consumption of the network is minimized. The algorithm uses unequal clustering structure which balances the energy consumption among the cluster-heads and lessens the effect of hotspot problem. Furthermore, a distributed protocol for choosing cluster-heads and routing is deployed to balance the energy among all sensor nodes. Simulation results show that the proposed scheme balances the energy consumption among the cluster-heads and increases the network lifetime compared to some recent reported clustering schemes in the literature.

The extensive usage of wireless sensor networks (WSNs) has led to the development of many power- and energy-efficient routing protocols. Cooperative routing in WSNs can improve performance in these types of networks. In this paper we discuss the existing proposals and we propose a routing algorithm for wireless sensor networks called Power Efficient Location-based Cooperative Routing with Transmission Power-upper-limit (PELCR-TP). The algorithm is based on the principle of minimum link power and aims to take advantage of nodes cooperation to make the link work well in WSNs with a low transmission power. In the proposed scheme, with a determined transmission power upper limit, nodes find the most appropriate next nodes and single-relay nodes with the proposed algorithm. Moreover, this proposal subtly avoids non-working nodes, because we add a Bad nodes Avoidance Strategy (BAS). Simulation results show that the proposed algorithm with BAS can significantly improve the performance in reducing the overall link power, enhancing the transmission success rate and decreasing the retransmission rate.

The main goal of research concerning energy aware routing algorithm for wireless sensor network is to increase the lifetime and long-term connectivity of the wireless sensor networks. However, most of energy aware routing algorithms do not take into account the clustering mechanism efficiently. In this paper, we present an efficient energy aware routing algorithm for the wireless sensor networks. In our algorithm, the data aggregation technique and adaptive clustering mechanism are considered for reducing and compacting the cumulative size of packets on the wireless sensor networks. Simulation results show that the energy usage of EAR-ACM is significantly reduced compared with the previous clustering based routing algorithm for the sensor networks.KeywordsSensor NetworkSensor NodeWireless Sensor NetworkCluster HeadData PacketThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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.

To overcome the threats of internal malicious nodes in wireless sensor networks(WSNs), a trust-based secure routing algorithm is proposed in this paper. It uses μTESLA(micro Timed, Efficient, Streaming, Loss tolerant Authentication) algorithm to ensure that the data should not be tampered by malicious nodes. Using the improved D-S evidence theory to evaluate the trust degree of internal nodes and obtain the optimal route selection. The experimental results show that the algorithm can effectively find and successfully keep away from the malicious nodes in the networks. Moreover, the algorithm can reduce the number of data packets dropped, providing reliable data transmission.

This paper introduces the measure of information as a new criterion for the performance analysis of routing algorithms in wireless sensor networks. We argue that since the objective of a sensor network is to estimate a two dimensional random field, a routing algorithm must maximize information flow about the underlying field over the lifetime of the sensor network. We develop two novel algorithms, MIR (maximum information routing) and CMIR (conditional maximum information routing) designed to maximize information flow, and present a comparison of the algorithms to a previously proposed algorithm-MREP (maximum residual energy path) through simulations. We show that the proposed algorithms give significant improvement in terms of information flow, when compared to MREP.