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WSNHA-GAHR: A greedy and A* heuristic routing algorithm for wireless sensor networks in home automation
IET Communications
Abstract
The use of wireless sensor networks in home automation (WSNHA) is a growing trend, on account of their self-organisation, low cost and potential for rapid deployment. Routing in WSNHA is a challenging research topic, because of the requirements of low energy consumption, low storage, low computational complexity, fast response, self-adaptation to unpredictable topological changes and robustness with respect to discontinuous interference. With the development of localisation techniques, localised routing offers a number of attractive benefits, but not all are suitable for WSNHA. In this study, the authors propose a new routing algorithm for WSNHA, called WSNHA-GAHR (greedy and A* heuristic routing for WSNHA). The algorithm uses greedy forwarding, based on the smallest Euclidean distance, to minimise the number of hops for data packet transmission, and thus conserve energy. It also automatically adjusts the route, using the A* heuristic algorithm, when local minimum problems and unpredictable topological changes occur in WSNHA. In addition, link priority classification gives WSNHA-GAHR a greater tolerance than ZigBee routing algorithm for discontinuous interference. Simulation results show that this routing protocol dramatically improves reliability and reduces average packet delay, without introducing additional overhead.
... Much work has been done developing WSN routing (e.g., see [16][17][18][19][20][21][22][23][24][25][26][27] for extensive reviews). Most existing energyaware routing algorithms assume that the communication load is evenly distributed; however, this assumption is not consistent with the data usage requirements of individual nodes within many WSNs. ...
... The clustering algorithm is based on cluster selecting, which incurs an additional energy cost. The other type is centralized routing, which uses probabilistic forwarding [18] or an optimization strategy, such as ant colony optimization, linear programming, or heuristic approaches, to find an energy-balanced route based on the global information on the network topology and energy consumption [16,17,[20][21][22]25]. ...
... Obviously, it is desirable for each sensor node to forward the data packet to a neighboring node that is both close to the destination and has sufficient energy to forward the data packet. This greedy forwarding criterion can be described as a selection function that determines which candidate is nearest to the destination [16]. Suppose that node has direct (one-hop) neighbors, 1 , 2 , . . . ...
We propose an energy-aware dynamic routing strategy in order to provide balanced energy consumption in wireless sensor networks, hence, prolonging the lifetime of the network. The proposed routing algorithm uses local betweenness centrality to estimate the energy consumption of the neighboring nodes around a given local sensor node, without requiring global information about the network topology or energy consumption, and to divert traffic from nodes that are more heavily used. Because nodes with large local betweenness centrality consume energy more quickly, the network lifetime can be prolonged by redistributing energy consumption to nodes with smaller local betweenness centrality. Simulation results showed that the proposed routing strategy has advantages over shortest path routing with respect to extending network lifetime and balancing energy consumption in wireless sensor networks, yet does not introduce significant additional transmission overhead or a longer average path length.
... In [9], proposed the new routing algorithm called WSNHA-GAHR. The protocol is using the greedy forwarding technique and the A-star algorithm to reduce the hop count and to overcome the local minimum problem. ...
... The direct link d= (v, u), d exists if the Euclidean distance between node v and u inside the domain of r, where r is the radius of the node transmission range. The sink is accountable for gathering sensory data from all sensors within its communication range [3,4,9].The model for the proposed method assumes that the WSN has the following properties :-1. Each sensor node has different quantities of traffic load inside its queue. ...
Uneven Energy Depletion (UED) is an innate drawback in wireless networks which dramatically reduce the network lifetime. This paper proposed an Energy Efficient Routing protocol to addressing the problem of UED and improving the WSN lifetime. The proposed method used LPA-star algorithm for choosing the appropriate optimum path from the source node to the base station. the routing algorithm using the dynamic threshold to find alternate route path to obviate choose the nodes that have low energies in order to prolong the lifetime of the network. The simulation results reveal significant improvements of the proposed approach as compared to the performance of the other related protocol.
... A-star algorithm will find a path with the lowest possible cost. This will depend heavily upon the quality of the cost function and estimates provided [26]. A-star algorithm (Pseudo-code A*) may be expressed as following [25], [ ...
... In this paper, the topology of a WSN is modeled as a directed graph G( N , A), where N is the set of nodes, and A is the set of direct links between the nodes. A sink node is responsible for collecting data from all other nodes within its transmission range [5], [9], [10], [26]. The routing schedule is computed by the base station. ...
... In [13], WSNHA-GAHR is a greedy and A-star heuristic routing algorithm for WSNs in home automation. The algorithm minimizes the number of hops for data transmission by using the greedy forwarding technique. ...
... A direct link d= (v, u), d ∈ D exists if the Euclidean distance between node v and u inside the domain of r, where r is the radius of the transmission range of nodes. The Base station (BS) is responsible for sensory data gathered from all other nodes in the network within its transmission range [13], [26][27]. The procedure of finding an optimum path from the source node to the BS is regard to some parameters in each sensor node like the residual energy, traffic load and the distance to the sink. ...
Since sensors have limited power resources, energy consumption has become a critical challenge to Wireless Sensor Networks (WSNs). Most of the routing protocols proposed to transmit data packets through paths which consume low energy aim simply to reduce battery power consumption. This can lead to lead to network partition and reduce network lifetime.Therefore, to balance energy consumption and extend network lifetime while minimizing packet delivery delay; this paper proposes a new energy-routing protocol using the lifelong planning A-star (LPA-star) search algorithm. This algorithm is used to find an optimum forwarding path between the source node and the sink. The optimum path can be selected depending on highest residual sensor energy, the shortest distance to the sink and lowest traffic load. Simulation results indicate that the proposed protocol increased the lifetime of the network compared with the A-star routing (EERP) protocol.
... In [13], WSNHA-GAHR is a greedy and A-star heuristic routing algorithm for WSNs in home automation. The algorithm minimizes the number of hops for data transmission by using the greedy forwarding technique. ...
... A direct link d= (v, u), d ∈ D exists if the Euclidean distance between node v and u inside the domain of r, where r is the radius of the transmission range of nodes. The Base station (BS) is responsible for sensory data gathered from all other nodes in the network within its transmission range [13], [26][27]. The procedure of finding an optimum path from the source node to the BS is regard to some parameters in each sensor node like the residual energy, traffic load and the distance to the sink. ...
Since sensors have limited power resources, energy consumption has become a critical challenge to Wireless Sensor Networks (WSNs). Most of the routing protocols proposed to transmit data packets through paths which consume low energy aim simply to reduce battery power consumption. This can lead to lead to network partition and reduce network lifetime.Therefore, to balance energy consumption and extend network lifetime while minimizing packet delivery delay; this paper proposes a new energy-routing protocol using the lifelong planning A-star (LPA-star) search algorithm. This algorithm is used to find an optimum forwarding path between the source node and the sink. The optimum path can be selected depending on highest residual sensor energy, the shortest distance to the sink and lowest traffic load. Simulation results indicate that the proposed protocol increased the lifetime of the network compared with the A-star routing (EERP) protocol.
... A-star algorithm will find a path with the lowest possible cost. It looks for the shortest path with minimum cost, which mainly depends on the choice of the evaluation function [43]. ...
... NA ( If (temp rnd >= * + 1) (9) ( ).type ← nor; (10) else ( ).type ← adv; (11) end if (12) end for (13) / * for every clustering round * / (14) For = 1 : 1 : (15) if(( ( ).type== nor && (temp rand <= ( nrm/ (1 -nrm * mod( , round(1/ nrm))))))) (16) ( ).type ← ch; //Election CHs from normal nodes (17) end if (18) if(( ( ).type == adv && (temp rand <= ( adv/ (1 − adv * mod( , round(1/ adv))))))) (19) ( ).type ← ch; //Election CHs from advanced nodes (20) end if (21) end for (31) end if (32) while(( Node ∼= Target || Node ∼= Target) && NoPath == 1) (33) if node is in Exp Array table and not in OPEN table (34) OPEN(OPEN COUNT,:) ← Insert Open( Exp Array( , 1), Exp Array( , 2), Node, Node, Exp Array( , 3), Exp Array( , 4), Exp Array( , 5)); (35) end if (36) index max node ← Max Fn(OPEN, OPEN COUNT, Target, Target); (37) if (index max node ∼= −1) (38) CLOSED(CLOSED COUNT,1) ← Node; (39) CLOSED(CLOSED COUNT,2) ← Node; (40) else NoPath ← 0; (41) end if (42) end while (43) while(parent ∼= Start || parent ∼= Start) (44) parent ← OPEN(Node Index(OPEN, val, val),4); (45) parent ← OPEN(node index(OPEN, val, val),5); (46) node ← node index(OPEN, parent ,parent ); the region size of B is 200 m × 50 m. According to the actual situation, coordinates of the base station are fixed and are far from the sensor nodes in the network, so this paper sets the base station coordinates as follows: A is (50, 300) and B is (100, 150). ...
Energy is a major factor in designing wireless sensor networks (WSNs). In particular, in the real world, battery energy is limited; thus the effective improvement of the energy becomes the key of the routing protocols. Besides, the sensor nodes are always deployed far away from the base station and the transmission energy consumption is index times increasing with the increase of distance as well. This paper proposes a new routing method for WSNs to extend the network lifetime using a combination of a clustering algorithm, a fuzzy approach, and an A-star method. The proposal is divided into two steps. Firstly, WSNs are separated into clusters using the Stable Election Protocol (SEP) method. Secondly, the combined methods of fuzzy inference and A-star algorithm are adopted, taking into account the factors such as the remaining power, the minimum hops, and the traffic numbers of nodes. Simulation results demonstrate that the proposed method has significant effectiveness in terms of balancing energy consumption as well as maximizing the network lifetime by comparing the performance of the A-star and fuzzy (AF) approach, cluster and fuzzy (CF)method, cluster and A-star (CA)method, A-star method, and SEP algorithm under the same routing criteria.
... The throughput [23] is defined as the total amount of data a receiver actually receives from the sender divided by the time between receiving the fast packet and last packet. The Average Throughput is the throughput per unit of time. . ...
... The Average Throughput is the throughput per unit of time. The throughput [23] is defined as the total amount of data a receiver actually receives from the sender divided by the time between receiving the fast packet and last packet. The Average Throughput is the throughput per unit of time. ...
... Thanks to the fast development of computer and wireless transmission technologies, information exchange and transmission have becoming increasingly convenient these days [1]. Now the one-way communication can no longer meet user needs in real-time data sharing at low costs, and the construction of networks not only consumes large amounts of material resources such as electric and optical cables, but also requires high maintenance costs [2]. ...
... These algorithms are based on the static wireless ad hoc network for dynamic routing selection. The selected routing path is relatively fixed, which cannot dynamically change according to network conditions, cannot make full use of network resources, and easily lead to network segmentation [9]. Moreover, it not suitable for the "mountain-type" scenic areas mobile wireless ad hoc network with frequent changes in node locations. ...
To reduce the security risks and guide management pressure of “mountain-type” scenic areas with steep and changeable topography, this paper combines the idea of swarm security intelligence and proposes a swarm security intelligent dynamic networking algorithm based on multiple constraints to ensure the swarm safety of the tour group and relieve the management pressure of tour guide through the dynamic group and the self-discovery after leaving the group. Based on multiple constraints such as signal strength, power consumption and fault probability etc, the algorithm optimizes the network topology in real-time, which can effectively reduce the high false-positive rate o f leaving the group due to node failure. Secondly, the algorithm constructs the Spf constrained fitness function and introduces the ant colony optimization algorithm to avoid the situation that the optimal routing path falls into the local optimal solution. Finally, the algorithm converts the adjacency matrix composed of routing table and node connection signals into areachable matrix to judge whether the member has left the group and reduce the false-negative rate of group loss in the case of multi-node connection. Experimental results show that the algorithm has good stability and robustness in mobile wireless adhoc networks
... introduced by the transmission of heuristic value. Heuristic route-finding algorithm efficiently adjusts routes, particularly when unpredictable topological changes occur [44]. ...
A single tree topology is a commonly employed topology for wireless sensor networks (WSN) to connect sensors to one or more remote gateways. However, its many-to-one traffic routing pattern imposes heavy burden on downstream nodes, as the same routes are repeatedly used for packet transfer, from one or more upstream branches. The challenge is how to choose the most optimal routing paths that minimizes energy consumption across the entire network. This paper proposes a proactive energy awareness-based many-to-one traffic routing scheme to alleviate the above said problem referred to as Energy Balance-Based Energy Hole Alleviation in tree topology (EBEHA-T). This protocol combines updated status of variations in energy consumption pattern around sink-hole zones and distribution of joint nodes among the trees. With this approach, EBEHA-T proactively prevents sink-hole formation instead of just a reactive response after they have occurred. Performance evaluation of EBEHA-T against benchmark method RaSMaLai shows increased energy saving across the entire network and a marked improvement in energy consumption balance in energy-hole zones. This precludes energy hole formation and the consequent network partitioning, leading to improved network lifetime beyond that of the RasMaLai. OMNET++ network simulation software has been used for the evaluation.
... After the A-star algorithm is completed, it will find a solution; otherwise, it can guarantee that no such solution exists. The A-star algorithm will find a path with the lowest possible cost, which will depend heavily upon the quality of the cost function and estimates provided [23]. ...
We describe a novel technique to speed up the reconfiguration for the very large scale integration (VLSI) arrays. We propose an efficient algorithm, making use of the idea of the A‐star algorithm, for accelerating the reconfiguration of the VLSI processor arrays to meet the real‐time constraints of embedded systems. The proposed algorithm treats the problem of constructing a local optimal logical column that has the minimum number of long interconnects as a shortest path problem. Then the local optimal column can be constructed by utilizing the A‐star algorithm with the appropriate heuristic strategy. We prove that the proposed method can find the shortest local logical column. Simulation experiments reveal that the proposed algorithm can greatly reduce the number of visits to the fault‐free processing elements (PEs) for constructing a local optimal logical column and effectively decrease the reconfiguration running time. Experimental results show that the computation time can be reduced by more than 38.64% for a 128 × 128 host array with fault density of 20%, without loss of harvest. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
... However, the protocol is not energy efficient and is not suitable for a noisy channel. A Greedy and A * Heuristic Routing (GAHR) algorithm based on Euclidean distance is proposed for WHANs[15]. The algorithm uses greedy forwarding to limit the number of hops required for data transmission. ...
... A Greedy and A * Heuristic Routing (GAHR) algorithm based on Euclidean distance is proposed for WHANs [15]. The algorithm uses greedy forwarding to limit the number of hops required for data transmission. ...
Wireless Home Automation Networks consist of battery powered sensors and actuators that communicate with each other over wireless channels. The sensor nodes collect environmental information such as temperature, light intensity, humidity, and pressure to provide context-aware services and to facilitate smart home control. However, resource limitations, unpredictable topology changes, and interference introduce a number of challenges to the design of home automation protocols. One of the challenging tasks is developing energy efficient routing protocols to prolong the network lifetime. This paper proposes an interference aware heuristic routing protocol which determines the forwarding path between sensors and the base station using a heuristic function and a heuristic search algorithm. On the basis of local and global distance, longevity factor (LF), and link quality (LQ), the heuristic function generates a heuristic value for each node and this value is used in A_ search algorithm to determine the efficient route. Simulation results show that the proposed routing scheme outperforms GAHR and AODV_jr protocols in terms of network lifetime, energy consumption, and message throughput. Furthermore, it achieves up to 15% increase in packet delivery ratio over GAHR protocol in a noisy environment.
... WSNHA-GAHR is a greedy and A * heuristic routing algorithm for wireless sensor networks in home automation [9]. The algorithm uses greedy forwarding technique based on the smallest Euclidean distance to minimize the number of hops for data transmission. ...
Wireless Sensor Networks (WSNs) consist of small nodes equipped with sensing, data processing and radio transmis-sion units. A number of clustering, routing, power management and data aggregation protocols are specially designed for WSNs where energy awareness is an essential design issue. Due to the resource constrained nature of sensor nodes, innovative techniques are required to extend the network lifetime in WSNs. This paper proposes an energy efficient routing protocol to find the forwarding path between source and destination node using heuristic function and A * search algorithm. Simulation results with OMNET++ show that our proposed protocol is efficient in terms of network lifetime, total energy dissipation and message throughput.
... One type is the distributed clustering routing algorithm, which groups sensor nodes into clusters and balances the energy consumption by the cluster head selection strategy in order to extend the network lifetime [3], [4], [5]. The other type is the centralized routing algorithm, which adopts optimization strategy such as ant colony optimization, linear program and heuristic approach, to find a energy-balance rout based on the global information of the network topology and energy consumption [6], [7], [8], [9], [10]. However, most existing energy aware routing algorithms assumed that WSNs are evenly distributed, which is different from the real WSNs topology, and almost all the existing studies have not studied the energy-aware routing in WSNs from the view of the structure and dynamics of large complex networks. ...
In this paper, an energy-balance routing strategy is proposed for prolonging the network lifetime for wireless sensor networks with scale-free characteristic. In order to avoid the nodes with high traffic using up their energy too early and prolong the network lifetime, the new routing strategy adopts the shortest path routing algorithm on weighted wireless sensor networks, where the weight values are calculated based on betweenness centrality of the nodes. Since the nodes with large betweenness centrality consumed energy more quickly, the network lifetime can be prolonged by distributing energy consumption from nodes with large betweenness centrality to nodes with small betweenness centrality by increasing weight value on every link that connects the node with the highest betweenness centrality to other nodes. Simulation results show that the proposed routing strategy is better than the shortest path routing as regards extending the network lifetime and balancing the energy consumption.
Wireless Sensor Networks (WSNs) emerged as major data gathering paradigm due to its wide variety of applications. Achieving energy efficient reliable data delivery is an important concern in WSNs. In a network, packet loss reduces the reliable data transmission rate. Retransmissions are required to increase the reliable data transmission rate. However, number of retransmissions also increase the network energy consumptions and packet delivery delay. Packet loss rate can be reduced by selecting a best successor node in a routing path. In this work, a Learning Automata based Routing mechanism is proposed for wireless sensor networks to achieve energy efficiency and reliable data delivery. In this paper, learning automata has been adopted to calculate next node’s selection probability in a routing path using node’s score, quality of link and previous selection probability. Further, an energy efficient reliable routing mechanism is proposed using combination of learning automata and A-star search algorithm. The proposed mechanism determines energy efficient and reliable routing paths in WSNs by favoring highest residual energy, good quality of link , more free buffer space and less distance. Finally, simulation results indicate that the proposed algorithm reduces the energy consumptions, data delivery delay, data transmissions and increases the network lifetime.
Routing protocols are used in wireless sensor network (WSN) to transmit data to a centre (e.g. a base station). In this study, the authors propose a routing protocol called dynamic three-dimensional fuzzy routing based on traffic probability to enhance network lifetime and increase packet delivery ratio. It uses a fuzzy-based procedure to transmit packets by hop-to-hop delivery from source nodes toward destination nodes. The proposed fuzzy system uses two input parameters including ‘distance’ and ‘number of neighbours’ and one output parameter denoted by ‘traffic probability’. When a node has a sensed data or buffered data packet, it selects one of its neighbours, called chosen node, from among a list of candidate nodes (CNs). Candidates are the neighbours which have power energy higher than average remaining energy and free buffer more than average available buffer size. Distance and number of neighbours for each CN are fed in the fuzzy system to calculate traffic probability. The CN having the lowest traffic probability is selected as an appropriate chosen node to transmit packets to the destination. Simulation results show that the proposed protocol surpasses the greedy and A* heuristic routing for wireless sensor networks in home automation, dynamic optimal progress routing, and A-star & Fuzzy methods in terms of network lifetime and packet delivery ratio.
Energy conservation of battery-powered sensor nodes is an exceedingly critical issue for Wireless Sensor Networks (WSNs), thus the extending of battery life has become a main driver for designing an energy-efficient protocol. Most routing protocol schemes achieving energy efficiency through forwarding packets to the base station along the shortest paths simply to save energy, which cause non-uniform energy consumption among sensor nodes and eventually lead to network partition. The selection of a suitable routing protocol can significantly improve overall performance in WSNs and especially energy awareness. Therefore, this paper proposes a new approach called Fuzzy_ LPA-star protocol which achieved by combining an LPA-star search algorithm with a fuzzy system in order to extend the WSNs lifetime. The proposed protocol is based on three important parameters for choosing the appropriate optimum path, which are; residual energy, distance to the sink and the traffic load of nodes. The simulation results reveal significant improvements of the proposed approaches as compared to the performance of the Fuzzy system, Fuzzy_A-star protocol, and LPA-star algorithm under the same routing criteria.
Geographic routing (GR) is designed for forwarding packets within a specific geographic region, and it enjoys the advantages of its scalability and simplicity. GR can provide a promising solution for packet delivering in next generation wireless network, and has gained much research attention in the areas of Wireless Sensor Networks (WSNs), Vehicular Ad Hoc Networks (VANETs) and Mobile Ad hoc Networks (MANETs). However, it suffers from communication holes or voids in the network areas due to network dynamics or random deployments. Most of current void handling schemes use local or whole topology information. In this paper, we propose a heuristic geographic routing (HGR) to avoid holes over a few iterations by using only local geographic information. Through simulation and analysis, we find that HGR has an outstanding performance in the respect of void bypassing. In addition, this algorithm keeps simplicity and has low communication overhead.
Routing protocols are used in wireless sensor network (WSN) to transmit data to a centre (e.g. a base station). In this study, the authors propose a routing protocol called dynamic three-dimensional fuzzy routing based on traffic probability to enhance network lifetime and increase packet delivery ratio. It uses a fuzzy-based procedure to transmit packets by hop-to-hop delivery from source nodes toward destination nodes. The proposed fuzzy system uses two input parameters including 'distance' and 'number of neighbours' and one output parameter denoted by 'traffic probability'. When a node has a sensed data or buffered data packet, it selects one of its neighbours, called chosen node, from among a list of candidate nodes (CNs). Candidates are the neighbours which have power energy higher than average remaining energy and free buffer more than average available buffer size. Distance and number of neighbours for each CN are fed in the fuzzy system to calculate traffic probability. The CN having the lowest traffic probability is selected as an appropriate chosen node to transmit packets to the destination. Simulation results show that the proposed protocol surpasses the greedy and A∗heuristic routing for wireless sensor networks in home automation, dynamic optimal progress routing, and A-star & Fuzzy methods in terms of network lifetime and packet delivery ratio.
In order to meet the requirements of Smart Grid in data acquisition, transmission reliability, stability, robustness and low power consumption of devices, ZigBee with its significant advantages of low power, low cost, low rate and easy to use, can play an important role in Smart Grid. As one of the key technologies of ZigBee, routing technology plays an important role in the performance optimization of network. Thus, in this paper, we focus on cluster-tree routing algorithm and hybrid routing algorithm in ZigBee network. Simulation and results show that, hybrid routing algorithm has better performance than cluster-tree routing algorithm in network throughput, average traffic received, average number of hops, network delay and network load.
Wireless sensor networks (WSNs) are used in many applications to gather sensitive information which is then forwarded to an analysis center. Resource limitations have to be taken into account when designing a WSN infrastructure. Unbalanced energy consumption is an inherent problem in WSNs, characterized by multihop routing and a many-to-one traffic pattern. This uneven energy dissipation can significantly reduce network lifetime. This paper proposes a new routing method for WSNs to extend network lifetime using a combination of a fuzzy approach and an A-star algorithm. The proposal is to determine an optimal routing path from the source to the destination by favoring the highest remaining battery power, minimum number of hops, and minimum traffic loads. To demonstrate the effectiveness of the proposed method in terms of balancing energy consumption and maximization of network lifetime, we compare our approach with the A-star search algorithm and fuzzy approach using the same routing criteria in two different topographical areas. Simulation results demonstrate that the network lifetime achieved by the proposed method could be increased by nearly 25% more than that obtained by the A-star algorithm and by nearly 20% more than that obtained by the fuzzy approach.
IEEE 802.15.4 is the prevailing standard for low-rate wireless personal area networks. It specifies the physical layer and medium access control sub-layer. Some emerging standards such as ZigBee define the network layer on top of these lower levels to support routing and multi-hop communication. Tree routing is a favourable basis for ZigBee routing because of its simplicity and limited use of resources. However, in data collection systems that are based on spanning trees rooted at a sink node, non-optimal route selection, congestion and uneven distribution of traffic in tree routing can adversely contribute to network performance and lifetime. The imbalance in workload can result in hotspot problems and early energy depletion of specific nodes that are normally the crucial routers of the network. The authors propose a novel light-weight routing protocol, energy aware multi-tree routing (EAMTR) protocol, to balance the workload of data gathering and alleviate the hotspot and single points of failure problems for high-density sink-type networks. In this scheme, multiple trees are formed in the initialisation phase and according to network traffic, each node selects the least congested route to the root node. The results of simulation and performance evaluation of EAMTR show significant improvement in network lifetime and traffic distribution.
KEYWORDS:
Wireless Personal Area Networks; multi-hop communication; Energy Aware Multi-Tree Routing (EAMTR); Sensors; Wireless Sensor Networks; traffic distribution
A hybrid anchor-free localisation scheme for multihop wireless sensor networks is presented. First, a relatively dense group of nodes is selected as a base, which are localised by using the multidimensional scaling method. Secondly, the robust quads (RQ) method is employed to localise other nodes, following which the robust triangle and radio range (RTRR) approach is used to perform the localisation task. The RQ and the RTRR methods are used alternately until no more nodes can be localised by the two approaches. Simulation results demonstrate that the proposed hybrid localisation algorithm performs well in terms of both accuracy and the success rate of localisation. To evaluate the accuracy of anchor-free localisation algorithms, the authors derive two different accuracy measures: the Cramer-Rao lower bound (CRLB) to benchmark the coordinate estimation errors and the approximate lower bound to benchmark the distance errors. Simulation results demonstrate that both the CRLB and the distance error lower bound provide references for the accuracy of the location algorithms.
This paper describes the concept of sensor networks which has been made viable by the convergence of micro-electro-mechanical systems technology, wireless communications and digital electronics. First, the sensing tasks and the potential sensor networks applications are explored, and a review of factors influencing the design of sensor networks is provided. Then, the communication architecture for sensor networks is outlined, and the algorithms and protocols developed for each layer in the literature are explored. Open research issues for the realization of sensor networks are also discussed.
An ad-hoc network is the cooperative engagement of a collection of
mobile nodes without the required intervention of any centralized access
point or existing infrastructure. We present Ad-hoc On Demand Distance
Vector Routing (AODV), a novel algorithm for the operation of such
ad-hoc networks. Each mobile host operates as a specialized router, and
routes are obtained as needed (i.e., on-demand) with little or no
reliance on periodic advertisements. Our new routing algorithm is quite
suitable for a dynamic self starting network, as required by users
wishing to utilize ad-hoc networks. AODV provides loop-free routes even
while repairing broken links. Because the protocol does not require
global periodic routing advertisements, the demand on the overall
bandwidth available to the mobile nodes is substantially less than in
those protocols that do necessitate such advertisements. Nevertheless we
can still maintain most of the advantages of basic distance vector
routing mechanisms. We show that our algorithm scales to large
populations of mobile nodes wishing to form ad-hoc networks. We also
include an evaluation methodology and simulation results to verify the
operation of our algorithm
A protocol named RFGFR (Restricted Flooding and Greedy Forwarding Routing) is presented in this paper. RFGFR propagates query packets from the sink to the centroid of a target region, it employs a scheme of restricted flooding and greedy forwarding results in fewer nodes to forward packets, which means less energy consumption. Greedy forwarding decision can reduce transmission delay by reducing communication hops. Simulations show RFGFR exhibits better performances for object tracking in sensor networks.
Wireless sensor networks consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. In this article we present a survey of state-of-the-art routing techniques in WSNs. We first outline the design challenges for routing protocols in WSNs followed by a comprehensive survey of routing techniques. Overall, the routing techniques are classified into three categories based on the underlying network structure: flit, hierarchical, and location-based routing. Furthermore, these protocols can be classified into multipath-based, query-based, negotiation-based, QoS-based, and coherent-based depending on the protocol operation. We study the design trade-offs between energy and communication overhead savings in every routing paradigm. We also highlight the advantages and performance issues of each routing technique. The article concludes with possible future research areas.
In the future ubiquitous home network, sensors will collect various home environment data in the home. Since the sensor nodes are equipped with small, often irreplaceable, batteries with limited power capacity, it is essential that the network be energy-efficient in order to maximize its lifetime. Our study, described in this paper, was divided into two classes: the primary class was to set a power-based level and the secondary class was to propose an offer of a home automation using a routing technique centered on a sensor network to set a flooding level. The proposed scheme divides the home into areas such as rooms and locates the WENs in each area. The WENs collect data from sensors and deliver the data to the home base station only. Sensors deliver the data to the WENs or the home base station through the sensor with the stronger power. Performance results show that the proposed scheme is more, efficient with a wireless home network.
Given a graph with arcs that have costs, the A* algorithm is
designed to find the shortest path from a single node to a set of nodes.
While the A* algorithm is well understood, it is somewhat limited in its
application due to the fact that it is often difficult to specify the
“heuristic function” so that A* exhibits desirable
computational properties. In this paper a metric space approach to the
specification of the heuristic function is introduced. It is shown how
to specify an admissible and monotone heuristic function for a wide
class of problem domains. In addition, when the cost structure for the
underlying graph is specified via a metric, it is shown that admissible
and monotone heuristic functions are easy to specify and further
computational advantages can be obtained. Applications to an optimal
parts distribution problem in flexible manufacturing systems and
artificial intelligence planning problems are provided
Home automation systems based on wireless sensor/actuator networks are characterized by diversity of node power sources, limited computational power, and mobility. We propose a routing protocol that fully uses the location of static nodes to limit the search for a route to a small zone based on the analysis of characteristics and requirements. The calculation of two different kinds of zone and the route discovery procedure are described in this paper. According to the environment of home automation, we compared the performance of our routing protocols with the ad-hoc on-demand distance-vector protocol using simulation and gave suggestions for zone selection. Simulation results showed that our routing protocol dramatically reduced the routing overhead and increased the reliability.
Our paper on the use of heuristic information in graph searching defined a path-finding algorithm, A*, and proved that it had two important properties. In the notation of the paper, we proved that if the heuristic function ñ (n) is a lower bound on the true minimal cost from node n to a goal node, then A* is admissible; i.e., it would find a minimal cost path if any path to a goal node existed. Further, we proved that if the heuristic function also satisfied something called the consistency assumption, then A* was optimal; i.e., it expanded no more nodes than any other admissible algorithm A no more informed than A*. These results were summarized in a book by one of us.
This paper presents a model for analyzing the performance of transmission strategies in a multihop packet radio network where each station has adjustable transmission radius. A larger transmission radius will increase the probability of finding a receiver in the desired direction and contribute bigger progress if the transmission is successful, but it also has a higher probability of collision with other transmissions. The converse is true for shorter transmission range. We illustrate our model by comparing three transmission strategies. Our results show that the network can achieve better performance by suitably controlling the transmission range. One of the transmission strategies, namely transmitting to the nearest forward neighbor by using adjustable transmission power, has desirable features in a high terminal density environment.
Location-based routing has been considered as an efficient routing paradigm for wireless sensor networks (WSNs). The performance of location-based routing highly depends on the way the position information of mobile sinks are updated and managed, which is the typical function of location service. Frequent location updating can improve the location accuracy at the expense of additional communication overhead. In this study, the authors propose a scalable location service for supporting efficient location-based routing in WSNs with mobile sinks. The proposed location service enables each sensor node to locate its closest (mobile) sink with low overhead. Analytical and simulation results show that it can significantly reduce the communication overhead for providing location service while maintaining high routing performance.
In wireless sensor networks, data aggregation routing could reduce the number of data transmission so as to achieve efficient total energy consumption. However, this kind of data aggregation introduces data retransmission that is caused by co-channel interference from neighbouring sensor nodes. Hence, more data aggregation leads to more extra energy consumption and significant retransmission delay from retransmission. This could jeopardise the benefits of data aggregation. One possible solution to circumvent retransmission caused by co-channel interference is to assign different channel to every sensor node that is within each other's interference range on the data aggregation tree. As the number of non-overlapping channels is limited in wireless networks, it is unlikely that we could assign a different channel to every sensor node on the data aggregation tree. Then, an interesting problem is to perform data aggregation routing in conjunction with channel assignment to minimise total transmission power under limited number of non-overlapping channels. This problem is an NP-complete problem. We devise heuristic algorithm, iterative channel adjustment data aggregation routing algorithm (ICADAR), and other three heuristics, to tackle this problem. From the simulation results, the ICADAR algorithm outperforms the other three algorithms under all experimental cases.
In this paper AODVjr, a simplified version of the AODV protocol, is described. AODVjr is compared in simulation to a full featured AODV implementation. The results show that AODVjr performs as well as AODV and describes other positive effects of a smaller protocol specification.
The use of wireless technologies in automation systems offers attractive benefits, but introduces a number of new technological challenges. The paper discusses these aspects for home and building automation applications. Relevant standards are surveyed. A wireless extension to KNX/EIB based on tunnelling over IEEE 802.15.4 is presented. The design emulates the properties of the KNX/EIB wired medium via wireless communication, allowing a seamless extension. Furthermore, it is geared towards zero-configuration and supports the easy integration of protocol security.
Owing to the growing demand for low-cost 'networkable' sensors in conjunction with recent developments of micro-electro mechanical system (MEMS) and radio frequency (RF) technology, new sensors come with advanced functionalities for processing and communication. Since these nodes are normally very small and powered with irreplaceable batteries, efficient use of energy is paramount and one of the most challenging tasks in designing wireless sensor networks (WSN). A new energy-aware WSN routing protocol, reliable and energy efficient protocol (REEP), which is proposed, makes sensor nodes establish more reliable and energy-efficient paths for data transmission. The performance of REEP has been evaluated under different scenarios, and has been found to be superior to the popular data-centric routing protocol, directed-diffusion (DD) (discussed by Intanagonwiwat et al. in 'Directed diffusion for wireless sensor networking' IEEE/ACM Trans. Netw., 2003, 11(1), pp. 2-16), used as the benchmark.
Node localisation is a fundamental problem in wireless sensor networks. Many applications require the location information of sensor nodes. Received signal strength (RSS) is a simple and inexpensive approach for localisation purpose. However, the accuracy of RSS measurement is unpredictable owing to the nature of the radio frequency (RF) channel. An RSS-based Monte Carlo localisation scheme is proposed to sequentially estimate the location of mobile nodes, using the log-normal statistical model of RSS measurement. The RSS measurement is treated as the observation model in Monte Carlo method and the mobility feature of nodes as the transition model. Our method is widely applicable because the RSS function is easy to implement on nodes, and the mathematical model for mobile nodes may have non-analytic forms. Simulation results about localisation accuracy and cost show that this scheme is better than other methods.
Ineffective sensor node (InESN) in a wireless sensor network (WSN) is defined as one whose position cannot be estimated by traditional localisation methods. Incremental localisation method is investigated and the existence of the InESNs is confirmed. By analysing the existing characteristics, the InESNs are classified into three categories: InESNs connecting with one known node, InESNs connecting with two known nodes and InESNs standing alone. It is impossible to locate the InESNs of the third category because they cannot receive any information from the known nodes. With a moving target in the WSN, a constrained least-squares formulation is developed to estimate the InESNs of the first two categories. Numerical evaluations are carried out to examine the performance of the proposed method and show that it is indeed effective for locating the InESNs. By incorporating the InESNs in the tracking applications, the performance of the target tracking can be greatly enhanced.
Although the problem of determining the minimum cost path through a graph arises naturally in a number of interesting applications, there has been no underlying theory to guide the development of efficient search procedures. Moreover, there is no adequate conceptual framework within which the various ad hoc search strategies proposed to date can be compared. This paper describes how heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching and demonstrates an optimality property of a class of search strategies.
In the emerging ubiquitous home, sensors are placed everywhere in the house and collect various physical data such as temperature, humidity, and light to provide information to consumer electronics devices. The devices are then automatically activated if necessary. For example, the ventilator works when the air is foul and the heating system performs according to the weather and the existence of people in the house. Because sensors have limited battery power, energy-efficient routing is important. In this paper, we present a new sensor routing scheme that provides energy-efficient data delivery from sensors to the home base station. The proposed scheme divides the home area into sectors and locates a manager node to each sector. The manager node receives collected data from sensors and delivers the data to the base station through the shortest path of the 2-dimensional (x, y) coordinates. Performance results show that the proposed scheme reduces energy consumption significantly compared with conventional sensor routing schemes.
Geographical routing is powerful for its ability to discover a path to the destination without the help of global states. However, stateless geographical routing usually involves a large number of hops when detouring around voids of the network. In this paper, we propose an efficient path pruning (PP) strategy to reduce the excessive number of hops caused by the detouring mode of geographical routing protocols. The PP algorithm finds routing shortcuts by exploiting the channel listening capability of wireless nodes and is able to reduce a large number of hops with the help of a little state information passively maintained by a subset of nodes on the route. We also discuss algorithm properties and implementation considerations and provide simulation results demonstrating the effectiveness of the proposed algorithm in shortening the routing path and improving delivery rate when it is applied to existing geographical routing protocols.
The dead end problem in greedy forwarding is an important issue of location based routing in sensor networks. It occurs when a message falls into a local minimum using greedy forwarding. Current solutions to this problem are insufficient in either eliminating traffic/path memorization or finding satisfactory short paths. In this paper, we propose a novel algorithm, called partial-partition avoiding geographic routing (PAGER), to solve the problem. The basic idea of PAGER is to divide a sensor network graph into functional subgraphs and provide each sensor node with message forwarding directions based on these subgraphs. PAGER results in loop free short paths without memorization of traffics/paths in sensor nodes. It does not require planarization of the underlying network graph. Further, the mobility adaptability of PAGER makes it suitable for use in mobile sensor networks with frequent topology changes. We implement the PAGER algorithm in two protocols and evaluate them in sensor networks with different parameters. Experimental results show the advantage of PAGER in the context of sensor networks.
Building automation systems (BAS) provide automatic control of the conditions of indoor environments. The historical root and still core domain of BAS is the automation of heating, ventilation and air-conditioning systems in large functional buildings. Their primary goal is to realize significant savings in energy and reduce cost. Yet the reach of BAS has extended to include information from all kinds of building systems, working toward the goal of "intelligent buildings". Since these systems are diverse by tradition, integration issues are of particular importance. When compared with the field of industrial automation, building automation exhibits specific, differing characteristics. The present paper introduces the task of building automation and the systems and communications infrastructure necessary to address it. Basic requirements are covered as well as standard application models and typical services. An overview of relevant standards is given, including BACnet, LonWorks and EIB/KNX as open systems of key significance in the building automation domain.
We present Greedy Perimeter Stateless Routing (GPSR), a novel routing protocol for wireless datagram networks that uses the positions of routers and a packet's destination to make packet forwarding decisions. GPSR makes greedy forwarding decisions using only information about a router's immediate neighbors in the network topology. When a packet reaches a region where greedy forwarding is impossible, the algorithm recovers by routing around the perimeter of the region. By keeping state only about the local topology, GPSR scales better in per-router state than shortest-path and ad-hoc routing protocols as the number of network destinations increases. Under mobility's frequent topology changes, GPSR can use local topology information to find correct new routes quickly. We describe the GPSR protocol, and use extensive simulation of mobile wireless networks to compare its performance with that of Dynamic Source Routing. Our simulations demonstrate GPSR's scalability on densely deployed wir...
ZigBee Specification, ZigBee Alliance Std
ZigBee Specification, ZigBee Alliance Std. Document 053 474r17, 2007