A fuzzy model for content-centric routing in Zigbee-based wireless sensor networks (WSNs).

Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing protocol have been specifically designed for WSNs. And energy awareness is an essential design issue. In this paper, We study the routing protocol of wireless sensor network and describe the ZigBee based wireless sensor network architecture, analyze the principles of tree-structured routing and AODV routing, and then apply Zigbee technology to intelligent parking system.

In this paper, we propose a non-cooperative, dynamic and extensive game model for routing in a wireless sensor network (WSN). We treat each sensor node as a player who has a strategy to choose from in order to find the route that meets certain objective functions. A multi-hop routing is performed concurrently between multiple source and multiple destination nodes considering signal-to-noise-interference ratio (SINR) as the constraint. The goal to be achieved by each of the player in the game is to minimize the (i) energy consumption and (ii) delay in routing towards the sink nodes. The players choose their strategies independently and selfishly to optimize the energy and delay in routing through the optimal routing path that is guided by SINR values. An experimental study on the SINR values manifests the effect of noise and integrity in communication with varying network conditions. With varying node density, we study the performance of our proposed routing game in terms of packet reception ratio (PRR) and network lifetime. The effectiveness of the dynamic routing game in its extensive regime is also highlighted and the self-imposed Nash equilibrium is ascertained.

Energy efficiency is a critical problem for wireless sensor networks. In past decades, network coding has been proved as a promising technology to reduce the number of transmissions, save energy, and improve network throughput, especially suitable for the wireless network that motivates the emergence of network coding aware routings. However, existing network coding aware routings have the failure decoding problem, because of defective network coding conditions. On the other hand, existing network coding aware routings usually consider the ideal traffic scheduling and neglect nodes’ energy and load which are important to wireless sensor networks. Therefore, it is not appropriate to directly apply existing network coding aware routings in wireless sensor networks. Regarding the problems above problems, this paper proposes traffic-shaped network coding aware routing (TSCAR) for wireless sensor networks. In the TSCAR, a universal network coding condition is presented to solve the false decoding problem. And traffic shaping mechanism is proposed to shape the traffic of different flows to create more coding actions when coding opportunities exist. In addition, network calculus is used to analyze the delay of the TSCAR. Besides, a coding, load, and energy aware routing metrics are proposed to evaluate the discovered paths. Extensive simulation results demonstrate that the TSCAR increases the number of coding opportunities and the proportion of coded packets, improves network throughput, and extends the network lifetime of wireless sensor networks.

A wireless sensor network is an enormous assortment of sensor nodes with inadequate power supply and self-conscious computational competence. Due to the circumscribed communication range and high density of sensor nodes, packet dispatching in sensor networks is usually performed through multi-hop data transmission. For that reason, routing in wireless sensor networks has been deliberated as an imperative field of research over the past decade. These days, multipath routing techniques is widely used in wireless sensor networks to improve network performance over and done with efficient utilization of accessible network resources. Consequently, the main intention of this review is to present the conception of the various routing approaches and its fundamental experiments, as well as the basic motivations for exploiting these techniques in wireless sensor networks. Routing procedures for WSNs are responsible for selecting and maintaining the routes in the network and ensure reliable and effective communication in inadequate periods. The energy constriction of WSNs make energy saving become the most significant objective of various routing algorithms. In this paper, a review of routing protocols and algorithms used in WSNs is presented with energy efficiency as the main goalmouth.

Landmark-based routing (LR) provides a promising approach for scalable point-to-point routing in wireless sensor networks (WSNs). Though various approaches have been proposed for landmark-based routing, they either introduce significant computational complexity or are inefficient in realistic, dynamic environments. In this paper, we identify three design principles that could form the basis of efficiency: algorithmic simplicity, update efficiency, and application awareness. Motivated by these principles, we present XLR, a new, flexible and comprehensive framework that tackles the inefficiency of landmark-based routing. XLR consists of four components: Relay Selection (RS), Parametric P-Norm distance function (PPN), Efficient Update with Coordinate Difference (EUCD) and General Forwarding (GF). The key advantage of XLR is that any subset of XLR's components can be independently incorporated into most landmark-based routing protocols.We perform extensive simulations to demonstrate that: (i) RS, a simple method, yields good performance comparable with previous methods, (ii) PPN increases LR performance considerably, (iii) EUCD reduces coordinate update overhead by up to 39%, and (iv) our GF outperforms previous approaches that consider factors such as link quality, delay and power consumption independently.

Wireless sensor networks (WSNs) struggle with energy efficiency because of limited node power. This paper presents an approach that uses evolutionary algorithms to choose the Cluster Head (CH) and optimize routing in wireless sensor networks (WSNs) using grid-based topologies. The proposed method repeatedly develops solutions based on criteria for node density, distance, and energy level by using the evolutionary capabilities of the genetic algorithm. A fitness function that considers latency, coverage, and energy efficiency is used to evaluate the solutions. The process selects CHs dynamically and uses GA-guided optimization to construct paths. Simulation results indicate improved network performance and energy efficiency over existing protocols. Evolutionary algorithm integration enables flexibility and optimization for energy-efficient CH selection and routing in WSNs with a grid-based design.

With rapid development of wireless communication, sensor, micro power system and electronic technology, the research on wireless sensor network has attracted more and more attention. The work proposed routing algorithm in wireless sensor network based on ant colony optimization by analyzing routing protocol and utilizing advanced idea. Ant colony optimization algorithm has advantages in implementing local work, supporting multiple paths and integrating link quality into pheromone formation. In routing selection, the work calculated probability that node is selected as the next hop according to pheromone concentration on the path. With characteristics including self-organization, dynamic and multipath, ant colony optimization algorithm is suitable for routing in wireless sensor network. With low routing cost, good adaptability and multipath, the algorithm balanced energy consumption to prolong network lifetime. In terms of simulation and experiments, ant colony algorithm was proved to be suitable for finding optimal routing in wireless sensor network, thus achieving design goal of routing algorithm.

Routing in sensor networks is very challenging compared to contemporary communication and wireless ad–hoc networks. This is attributed to several characteristics that distinguish them from such networks. Transmitting data from every sensor node within the deployment region might result in significant and unnecessary redundancy in data and incur avoidable energy and traffic expenditure; thus, a routing protocol which is able to select a set of sensor nodes and utilise data aggregation during the relaying of data is of great importance. Furthermore, timely delivery of data is required in many applications of Wireless Sensor Networks (WSNs), such as real–time target tracking in battle environments, emergent event triggering in monitoring applications impose the need of efficient routing protocol. In this paper, we propose a data routing scheme which ensures increased network lifetime by exploiting energy efficiently, supporting reliability, fast delivery of delay–sensitive data and achieving low–cost sensor design. Simulation results demonstrate that, the proposed routing scheme outperforms related existing approaches in terms of all the evaluation metrics such as packet delivery ratio, energy efficiency and timely delivery of data.

Wireless sensor networks are generally composed of densely deployed sensor nodes that collaboratively sense, compute and communicate the sensed information. Routing in sensor networks is based on energy optimisation and quality of service. In this paper, a meta-heuristic technique comprising particle swarm optimisation and Tabu search (TS) is used for energy efficient routing in sensor network. The hybrid approach has better network performance compared with the traditional approaches, simple particle swarm algorithm and TS, respectively. Experimental results penlight the efficacy of the proposed approach.

This paper focuses on the experimental validation of the Fuzzy Logic Based Routing Algorithm (FLBRA) proposed for wireless sensor networks which operates in indoor environments in the context of building management systems. The fuzzy logic determines the cost of each link for the routing algorithm and calculates the lower cost path for packet forwarding. The network parameters used to determine the cost of each link through the Fuzzy Logic are the Received Signal Strength Indicator (RSSI), the standard deviation of the RSSI and the packet error rate. The routing algorithm based solely on the RSSI was also tested and compared to the FLBRA one. The proposal performance was evaluated using different scenarios in which different numbers of sensor nodes were considered in the same indoor environment. Both FLBRA and RSSI-based solutions were monitored and analyzed using the same testbed. It can be seen from the results that the FLBRA has a better performance, selecting the best routes with lower cost, in comparison to the solution solely based on the RSSI.

Energy conservation and fault tolerance are the most two important challenging issues for the development of large scale wireless sensor networks (WSNs). Failure of cluster heads in a cluster based WSN is more catastrophic as they are responsible not only for data aggregation and transmission of the aggregated data to the base station but also relaying data for multi-hop communication. Therefore, a routing algorithm in WSNs should be energy aware as well as fault tolerant. In this paper, we present a distributed energy efficient and fault tolerant routing algorithm for WSNs. The algorithm selects next-hop cluster head in energy efficient manner in the data routing phase and carefully restores the connectivity of the neighbours of a cluster head in case of its failure. The algorithm is tested extensively by considering several scenarios of WSN. The experimental results are compared with the existing algorithms in terms of several metrics to show the effectiveness of the proposed algorithm.

The rumor routing is a method extracted from the random movement of software agents basis. This paper presents a model based on the mentioned principal for routing in wireless sensor networks. First in this article we will present a model based on query agents dispatch which is called Serial Directional Rumor Routing (SDRR.) Then we will examine the advantages and disadvantages of this model compared to Directional Rumor Routing (DRR) which is an other model based on parallel agent dispatch. Next will propose a method to improve SDRR so that by removing some of shortcomings such as delays and path lengths, model can gain and edge over other models. The obtained results show a considerable improvement over Directional Rumor Routing (DRR).

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This paper proposes a clustering technique, called ELECT, to provide an energy efficient and reliable routing in wireless sensor networks. The ELECT considers node status and link condition, and introduces a clustering metric, called predicted transmission count (PTX), to evaluate the qualification of nodes for clusterheads and gateways. Each clusterhead or gateway candidate depends on the PTX to derive a priority. The clusterhead or gateway candidate with the highest priority will become the clusterhead or gateway. Simulation results show that the proposed ELECT significantly outperforms the clustering technique using a random selection and considering only link quality and remaining energy in packet delivery ratio and energy consumption.

As a popular routing protocol in wireless sensor networks (WSNs), greedy routing has received great attention. The previous works characterize its data deliverability in WSNs by the probability of all nodes successfully sending their data to the base station. Their analysis, however, neither provides the information of the quantitative relation between successful data delivery ratio and transmission power of sensor nodes nor considers the impact of the network congestion or link collision on the data deliverability. To address these problems, in this paper, we characterize the data deliverability of greedy routing by the ratio of successful data transmissions from sensors to the base station. We introduce η-guaranteed delivery which means that the ratio of successful data deliveries is not less than η, and study the relationship between the transmission power of sensors and the probability of achieving η-guaranteed delivery. Furthermore, with considering the effect of network congestion and link collision, we provide a more precise and full characterization for the deliverability of greedy routing. Extensive simulation and real-world experimental results show the correctness and tightness of the upper bound of the smallest transmission power for achieving η-guaranteed delivery.