Power Efficient Hierarchical Routing Protocols

Published Date: 02 Nov 2017

The significant advances in wireless sensor network technology has provided the need of small and low cost sensor nodes with the ability of sensing, processing and communication capabilities. By networking large number of tiny sensor nodes various applications in the wireless sensor networks that connect the physical world to the virtual world. In wireless sensor networks have a limited energy resources,minimum transmission range,less processing capabilities and storage capabilities.Each node act as router and host and the topology of network also varies.In wireless sensor networks the routing protocols are responsible for reliable communication by maintaining the routes in the networks.The number of routing protocols achieving the contemporary methodologies such as network flow,energy efficiency,Quality of service,security in the wireless sensor networks are proposed.Yet now,these routing protocols are not achieved the maximum range of energy efficiency,storage capacity,computing power.In this paper we give a survey of hierarchical routing protocols and their classification for maximum energy efficient in wireless sensor networks.

Keywords:

WirelesssensorsNetworks,HierarchicalRoutingProtocols,Energy Efficiency

Introduction

The recent technological advancement in the Wireless sensor network (WSN) has become hot area nowadays in research [1]. The WSN typically consists of a large number of low-cost, low-power, and multifunctional wireless sensor nodes,these sensor nodes consists of mobility,sensing, transmission, processing, communications and computation capabilities [2]. Using these sensor nodes all the wireless mobile devices will be capable to communicate with each other to form complete infrastructure. Several Hundreds or even thousands of tiny sensor nodes connected forms Wireless Sensor Networks.Due to the vast potential of sensor networks to enable the applications that connect the physical world to the virtual world.Each node acts both router and host and the topology of network also varies rapidly.The characteristics of sensor networks and application requirements have a decisive impact on the network design objectives in term of network capabilities and network performance[3].The design of routing protocols for WSN is challenging because of several network constraints like synchronization,node localization,low battery power etc.A large number of research activities have been carried out to explore and overcome the various issues and energy constraints in wireless sensor networks.In this paper we discuss and survey hierarchical routing protocols and their classification in briefly.

Dr.D.Sivakumar.,Dean,ArunaiCollegeof Engineering,Thiruvannamalai-Tamilnadu,INDIA

Routing Protocols in Wireless Sensor Networks

For an efficient route for an un-interrupted communication, many protocols are suggested depending upon the various applications and type of networks.Routing protocols can be classified into three categories namely,proactive,reactive and hybrid. In proactive protocols, all routes are computed before they are really needed,while in reactive protocols,routes are computed on demand.Hybrid protocols use a combination of these two ideas.A significant amount of energy is used in route discovery and setup of reactive protocols.

Routing protocols are classified into three techniques are Flat,Hierarchical,Location-based Protocols.The Hierarchical routing protocols is the major important most significant to get high efficient energy consumption in wireless sensor networks.

Hierarchical Routing Protocols

Hierarchical or cluster –based routing is utilized to perform energy-efficient routing in WSNs.The creation of clusters and assigning special tasks to cluster heads can greatly contribute to overall system scalability,lifetime,energy efficiency.Hierarchical routing is an efficient way to lower energy consumption within a cluster and by performing data aggregation and fusion in order to decrease the number of transmitted messages to the BS.Hierarchical routing is mainly two layer routing where one layer is used to select clusterheads and the other layer is used for routing.

Low Energy Adaptive Clustering Hierarchy (LEACH):LEACH [4 ][5][6] is the first and most popular energy-efficient hierarchical clustering algorithms for sensor networks.This was proposed for reducing power consumption..Based on the duration the clustering task is rotated among the sensor nodes.The Cluster Head (CH) uses direct communication by forwading the data to the base station (BS).LEACH uses clusters to lengthen the life of the wireless sensor network.LEACH uses the aggregation technique that combines the original data into a smaller size of data to carry out meaningful information to all sensors in the sensor field.LEACH divides the network into several cluster of sensors,which are constructed by using localized coordination and control not only to reduce the amount of data that are transmitted to the sink,but also to make routing and data dissemination more scalable and robust.LEACH uses a randomize rotation of high-energy CH position rather than selecting in static manner,to give a chance to all sensors to act as CHs and battery depletion of an individual sensor and dieing quickly.The operation of LEACH is divided into rounds having two phases namely a setup phase to organize the network into clusters,CH advertisement,and transmission to the sink by minimizing the communication cost between sensors and their cluster heads.

LEACH uses single-hop routing where each node can transmit directly to the cluster-head and the sink.Therefore,it is not applicable to networks deployed in large regions.Furthermore, the idea of dynamic clustering brings extra overhead,e.g. head changes,adversiments etc.,which may diminish the gain in energy consumption.While LEACH helps the sensors within the cluster dissipate their energy slowly,the CHs consume a large amount of energy when they are located farther away from the sink.

Power-Efficient Gathering in sensor Information Systems (PEGASIS): PEGASIS [4,7] is an extension of the LEACH protocol,which forms chains from sensor nodes so that each node transmits and receives from a neighbor and only one node is selected from that chain to transmit to the base station(sink). The data is gathered and moves from node to node, aggregated and eventually sent to the base station. The chain construction is performed in a greedy way. Unlike LEACH, PEGASIS avoids cluster formation and uses only one node in a chain to transmit to the BS (sink) instead of using multiple nodes. A sensor transmits to its local neighbors in the data fusion phase instead of sending directly to its CH as in the case of LEACH. In PEGASIS routing protocol, the construction phase assumes that all the sensors have global knowledge about the network, particularly, the positions of the sensors, and use a greedy approach. When a sensor fails or dies due to low battery power, the chain is constructed using the same greedy approach by bypassing the failed sensor. In each round, a randomly chosen sensor node from the chain will transmit the aggregated data to the BS, thus reducing the per round energy expenditure compared to LEACH.

Simulation results showed that PEGASIS is able to increase the lifetime of the network twice as much the lifetime of the network under the LEACH protocol. Such performance gain is achieved through the elimination of the overhead caused by dynamic cluster formation in LEACH and through decreasing the number of transmissions and reception by using data aggregation. Although the clustering overhead is avoided, PEGASIS still requires dynamic topology adjustment since a sensor node needs to know about energy status of its neighbors in order to know where to route its data. Such topology adjustment can introduce significant overhead especially for highly utilized networks.

Hybrid,Energy-Efficient Distributed Clustering (HEED): HEED [4,8,9] extends the basic scheme of LEACH by using residual energy and node degree or density as a metric for cluster selection to achieve power balancing. It operates in multi-hop networks, using an adaptive transmission power in the inter-clustering communication. HEED was proposed with four primary goals namely (i) prolonging network lifetime by distributing energy consumption, (ii) terminating the clustering process within a constant number of iterations, (iii) minimizing control overhead, and (iv) producing well-distributed CHs and compact clusters. In HEED, the proposed algorithm periodically selects CHs according to a combination of two clustering parameters. The primary parameter is their residual energy of each sensor node (used in calculating probability of becoming a CH) and the secondary parameter is the intra-cluster communication cost as a function of cluster density or node degree (i.e. number of neighbors). The primary parameter is used to probabilistically select an initial set of CHs while the secondary parameter is used for breaking ties. The HEED clustering improves network lifetime over LEACH clustering because LEACH randomly selects CHs (and hence cluster size), which may result in faster death of some nodes. The final CHs selected in HEED are well distributed across the network and the communication cost is minimized. However, the cluster selection deals with only a subset of parameters, which can possibly impose constraints on the system. These methods are suitable for prolonging the network lifetime rather than for the entire needs of WSN.

Threshold Sensitive Energy Efficient Sensor Network Protocol (TEEN): TEEN [4,10,11] is a hierarchical clustering protocol, which groups sensors into clusters with each led by a CH. The sensors within a cluster report their sensed data to their CH. The CH sends aggregated data to higher level CH until the data reaches the sink. Thus, the sensor network architecture in TEEN is based on a hierarchical grouping where closer nodes form clusters and this process goes on the second level until the BS (sink) is reached. TEEN is useful for applications where the users can control a trade-off between energy efficiency, data accuracy, and response time dynamically. TEEN uses a data-centric method with hierarchical approach. Important features of TEEN include its suitability for time critical sensing applications. Also, since message transmission consumes more energy than data sensing, so the energy consumption in this scheme is less than the proactive networks. However, TEEN is not suitable for sensing applications where periodic reports are needed since the user may not get any data at all if the thresholds are not reached.

Adaptive Periodic Threshold Sensitive Energy Efficient Sensor Network Protocol (APTEEN): APTEEN [4,12] is an improvement to TEEN to overcome its shortcomings and aims at both capturing periodic data collections (LEACH) and reacting to time-critical events (TEEN). Thus, APTEEN is a hybrid clustering-based routing protocol that allows the sensor to send their sensed data periodically and react to any sudden change in the value of the sensed attribute by reporting the corresponding values to their CHs. The architecture of APTEEN is same as in TEEN, which uses the concept hierarchical clustering for energy efficient communication between source sensors and the sink. APTEEN supports three different query types namely (i) historical query, to analyze past data values, (ii) one-time query, to take a snapshot view of the network; and (iii) persistent queries, to monitor an event for a period of time. APTEEN guarantees lower energy dissipation and a larger number of sensors alive [44].

Energy-Aware Qos Routing Protocol:

In this QoS (Quality of service) aware protocol [47] for sensor networks,real-time traffic is generated by imaging sensors.This protocol extends the routing approach in and finds a least cost and energy efficient path that meets certain end-to-end delay during the connection.The link cost used is a function that captures the nodes’energy reserve,transmission energy,error rate and other communication parameters.In order to support both best effort and real-time traffic at the same time, a class-based queuing model is employed.The queuing model allows service sharing for real-time and non-real-time traffic.The protocol finds a list of least cost paths by using an entended version of Dijkstra’s algorithm and picks a path form that list which meets the end-to-end delay requirement.

Conclusion and Future Research

Due to the tremendous growth of wireless sensor network nowadays.There are many issues for developing the routing protocols in efficient manner.In this paper we studied and suryed various hierarchical routing protocols and their classification criteria,including location information,network layering and data centricity,path redundancy,network dynamics,QoS requirements.Routing protocols designed for WSNs should be as energy efficient as possible to prolong the lifetime of individual sensors,and hence the network lifetime.In future large set of research activities have to be done to design a new routing protocols for power consumption.

Acknowledgements

We would like to thank Shio Kumar Singh,M.P.Singh and D.K.Singh for their valuable suggestions and letting us to use their Hierarchical Routing Protocols notes.

References

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One of the main challenges in the design of routing protocols for WSNs is energy efficiency due to the scarce energy resources of sensors.The energy consumption of the sensors is dominated by data transmission and reception.Therefore,routing protocols designed for WSNs should be as energy efficient as possible to prolong the lifetime of individual sensors,and hence the network lifetime.In this paper,we have surveyed routing protocols by taking into account several classification criteria,including location information,network layering and in-network processing,data centricity,path redundancy,network dynamics,QoS requirements,and network heterogeneity.The protocols discussed in this paper have individual advantages and pitfalls.Based on the topology,the protocol and routing strategies can be applied.For realization of sensor networks,it is needed to satisfy the constraints introduced by factors such as fault tolerance,scalability,cost,topology change,environment,and power consumption.Since these constraints are highly stringent and specific for sensor networks,new wireless adhoc networking techniques are required to be explored further.

A large number of research activities have been carried out to explore and overcome the various issues and energy constraints in wireless sensor networks.In this paper we discuss and survey hierarchical routing protocols and their classification in briefly.

One of the main challenges in the design of routing protocols for WSNs is energy efficiency due to the scarce energy resources of sensors. The ultimate objective behind the routing protocol design is to keep the sensors operating for as long as possible, thus extending the network lifetime. The energy consumption of the sensors is dominated by data transmission and reception. Therefore, routing protocols designed for WSNs should be as energy efficient as possible to prolong the lifetime of individual sensors, and hence the network lifetime.

In this paper, we have surveyed a sample of routing protocols by taking into account several classification criteria, including location information, network layering and in-network processing, data centricity, path redundancy, network dynamics, QoS requirements, and network heterogeneity. For each of these categories, we have discussed a few example protocols.

Two important related research directions should receive attention from the researcher namely the design of routing protocols for duty-cycled WSNs, and three-dimensional (3D) sensor fields when designing such protocols. Although most of research work on WSNs, in particular, on

routing, considered two-dimensional (2D) settings, where sensors are deployed on a planar field, there are some situations where the 2D assumption is not reasonable and the use of a 3D design becomes a necessity. In fact, 3D settings reflect more accurate network design for real-world applications. For example, a network deployed on the trees of different heights in a forest, in a building with multiple floors, or underwater [54], requires design in 3D rather than 2D space. Although some efforts have been devoted to the design of routing and data dissemination protocols for 3D sensing applications, we believe that these first-step attempts are in their infancy, and more powerful and efficient protocols are required to satisfactorily address all problems that may occur.

The main idea is to form clusters of the sensor nodes based on the received signal strength and use local cluster heads as routers to the sink.This will save energy since the transmissions will only be done be such cluster heads rather thatn all sensor nodes.However,LEACH uses single-hop routing where each node can transmit directly to the cluster –head and the sink.Therefore,it is not applicable to networks deployed in large regions.Furthermore,the idea of dynamic clustering brings extra overhead,e.g.head changes,advertisements etc., which may diminish the gain in energy consumption.(all the above copied from akkaya).

Problem:

The reason we need network protocol such as LEACH is due to the fact that a node in the network is no longer useful when its battery dies.

PEGASIS(Power Efficient Gathering for Sensor Information via Negotiation): Unlike LEACH protocol the sensor nodes in the network form a chain based arrangement. In LEACH the nodes are arranged in clustered manner. And in PEGASIS there is no cluster head selection phase. Hence it avoids overhead fairly. The sensed data is sent to single hop neighbor node. Each node sends data to its neighbor and thus forms a chain arrangement. A token is passed to the nodes. After receiving the token the node delivers the data to neighbor. As shown in Figure 2, a hierarchical approach breaks the network into clustered layers [55]. Nodes are grouped into clusters with a cluster head that has the responsibility of routing from the

cluster to the other cluster heads or base stations. Data travel from a lower clustered layer to a higher one. Although, it hops from one node to another, but as it hops from one layer to another it

covers larger distances. This moves the data faster to the base station. Clustering provides inherent optimization capabilities at the cluster heads. In this section, we review a sample of hierarchical-based routing protocols for WSNs.

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Experimental

Material and Methods:

General procedure:

Detection Method:

Results and Discussion

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Conclusions

Acknowledgements