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(LEACH) 2 : Combining LEACH with Linearly Enhanced Approach for Cluster Handling in WSNs
Abstract
Wireless Sensor Networks (WSNs) are expected to have wide applicability in the near future. In this paper, we propose (LEACH) 2 : Linearly Enhanced Approach for cluster handling improving the conventional protocol LEACH (Low Energy Adaptive Clustering Hierarchy) in WSNs. We divide the network area into four regions and study the network perfor-mance in the presence of one, two and three sinks. Simulation results show that our technique with three sinks performs better than other conventional routing techniques. (LEACH) 2 offers increased stability period, network lifetime and throughput than LEACH.
... Because the sensor nodes in the vicinity of the static sink die fast and make a hotspot or a problem of energy hole, the SNs near the static sink must transmit the data packets to the SNs further away from the static sink.Many researchers have found that SNs that are located distant from the static sink may be able to retain more than 91% of the energy and the SNs with one hop distance die soon [7]. The proposed work uses the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, a randomization-based clustering techniqueto disperse the energy load across the network's sensor nodes [9]. The LEACH protocol divides the network into multiple clusters and allocates a head for a cluster based on amount of energy remaining. ...
The energy near the static sink normally suffers from energy depletion issue since the node near the sink propagates signals to other nodes and acts as a convener, which leads the energy dissipation of sensor nodes near to the mobile sink, resulting in a network energy hole. In order to resolve these concerns, we have proposed a protocol known as Improved Mobile Sink Low Energy Adaptive Clustering Hierarchy (IMS-LEACH) protocol toreduce the problems with wireless sensor networks and to extend the life of sensor nodes. The proposed mechanism uses two methods, the first method organizes the cluster and a cluster head is selected for every cluster. And in the second technique, the selected cluster is in charge of gathering data from the cluster's sensor nodes and eventually transmitting it to the sink node. In the proposed methods Sink Node can move to any sensor node in a cluster to gather data and it leads to minimized energy consumption compared to other protocols.
... The proposed scheme outperformed LEACH protocol. K. Khan, M. Sajid, S. Mahmood, Z. A. Khan, U. Qasim, and N. Javaid [16] proposed LEACH 2. In this paper, an enhanced technique over the original LEACH is implemented in which the network has been studied on the basis of dividing the network into four regions and performance has been studied on the basis of one, two and three sinks. Three sinks were deployed at center, left and right of the field and from each of these regions a cluster head was selected. ...
Wireless Sensor Networks(WSNs) comprise sensor nodes which find applications in a wide variety of fields such as medical, wildlife, security, environment, industry. A network communication is initialized and accomplished with the aid of routing protocols. A routing protocol is a set of rules which govern the routing phenomenon. WSNs protocols for the purpose of routing have been the ubiquitous option of the researchers in the recent years due to their exorbitant scope of improvement. The objective of a routing protocol is to inquest for a relevant route amidst sender and receiver to accomplish successful transmission at the destination .Dissipation of energy and lengthening the duration of the network have always been one of the major points of research gaps. As the nodes in WSNs in are battery operated, so they can only use restricted energy to proceed with the communication and transmission operation. To cope up with this, a number of researchers have come up with developments in the field of energy efficacy and optimizations in WSNs routing protocols. A reify summarization of some protocols for routing purposes has been manifested in this paper.
... The proposal to combine LEACH with a Linearly Enhanced Approach (LEACH)2 [9] divides the entire sensing region into four parts, each with a BS located at different locations in the region . CHs are chosen based on probability as in LEACH, but the non-CH nodes associate themselves either to a BS or to the nearest CH based on RSS. ...
A wireless sensor network (WSN) is composed of many small sensors with limited energy that are deployed in a large geographical region. The Low-Energy Adaptive Clustering Hierarchy (LEACH) is a well-known cluster head selection algorithm for WSNs. Over the years, there have been many improvements to the LEACH algorithm in terms of the choice of the cluster head. One such protocol is V-LEACH, where every cluster has a vice-cluster head in addition to the cluster head, so that it can take over if the cluster head dies. But these two algorithms adopted the stochastic cluster head selection, leading to unbalanced partitioning of clusters. This leads to a negative impact on the network lifetime. To address this problem, this paper proposes a (Political) Party-based Cluster Head selection algorithm called PartyCH. The proposed algorithm utilizes multiple dynamic decision parameters such as residual energy, distance, and neighbourhood degree to elect the Cluster Head and Vice Cluster Head. This adaptive selection guarantees longer network lifetime by minimizing energy consumption and routing overhead. The comprehensive comparisons between PartyCH against both LEACH and V-LEACH protocols are provided and analysed. The simulation results indicate an improvement in network lifetime by over 150%.
... (LEACH) 2 in [14] is a combination of LEACH with an improved approach for Cluster Handling in WSNs. In this algorithm the entire filed is divided into four regions, using multi sink and four scenarios for sink replacement. ...
In this paper a new method, Optimal Path from Source to Sink Node (OPSSN), is proposed for achieving the Quality of Service (QoS) in terms of packet delivery reliability and better energy consumption in Wireless Sensor Networks (WSN). Routing in WSN has more expected node failures than the traditional networks; so to establish a routing protocol which supports QoS in WSN, requires considering the reasons for node failure to improve network performance. In case of failure (node failure or link failure), this method will offer automatic adaptation to dynamic linking and low processing overhead by choosing the default path through intensive nodes. This method increases the number of spare neighbors for original nodes which are preserved for data transmission through them, to be used in case of failure. This algorithm is simulated using MATLAB. Results showed that OPSSN achieved better performance compared to LEACH in terms of network life time, packets received at Base Station (BS), number of Cluster Heads (CH) per round, and total energy consumption.
Owing to the fact that the selection of cluster heads has a significant effect on the lifetime of the network, many researches have proposed various cluster head election methodologies for cluster-based WSNs. Although recent studies have focused on adaptive approaches, in which different parameters are assembled under a function, the effect of these parameters on cluster head election is not investigated in detail. In this paper, initially, a small-scale dataset is constructed by evaluating the death of the first, the half and the last node in a cluster-based WSN using three popular cluster head parameters, including the remaining energy of the nodes, the intra-cluster communication cost and the number of neighbours. In consideration of the results, a dynamically changeable coefficient based adaptive cluster head election, DCoCH, is proposed. The coefficients of the cluster head election parameters show alteration within three different periods of the lifetime of the network. DCoCH is compared with two recent adaptive based cluster head election methodologies for various WSN parameters and the results show that DCoCH outperforms equivalent approaches for different values of the location of the base station, the size of the network, the number of the nodes, the initial batteries of the nodes and the distribution of the nodes.
The design and analysis of routing algorithm is an important issue in wireless sensor networks (WSNs). Most traditional geographical routing algorithms cannot achieve good
performance in duty-cycled networks. In this paper, we propose a k-connected overlapping clustering approach with energy awareness, namely, k-OCHE, for routing in WSNs. The basic idea of this
approach is to select a cluster head by energy availability (EA)
status. The k-OCHE scheme adopts a sleep scheduling strategy of
CKN, where neighbors will remain awake to keep it k connected,
so that it can balance energy distributions well. Compared with
traditional routing algorithms, the proposed k-OCHE approach
obtains a balanced load distribution, consequently a longer
network lifetime, and a quicker routing recovery time.
We study the impact of heterogeneity of nodes, in terms of their energy, in wireless sensor networks that are hierarchically clustered. In these networks some of the nodes become cluster heads, aggregate the data of their cluster members and transmit it to the sink. We assume that a percentage of the population of sensor nodes is equipped with additional energy resources—this is a source of heterogeneity which may result from the initial setting or as the operation of the network evolves. We also assume that the sensors are randomly (uniformly) distributed and are not mobile, the coordinates of the sink and the dimensions of the sensor field are known. We show that the behavior of such sensor networks becomes very unstable once the first node dies, especially in the presence of node heterogeneity. Classical clustering protocols assume that all the nodes are equipped with the same amount of energy and as a result, they can not take full advantage of the presence of node heterogeneity. We propose SEP, a heterogeneous-aware protocol to prolong the time interval before the death of the first node (we refer to as stability period), which is crucial for many applications where the feedback from the sensor network must be reliable. SEP is based on weighted election probabilities of each node to become cluster head according to the remaining energy in each node. We show by simulation that SEP always prolongs the stability period compared to (and that the average throughput is greater than) the one obtained using current clustering protocols. We conclude by studying the sensitivity of our SEP protocol to heterogeneity parameters capturing energy imbalance in the network. We found that SEP yields longer stability region for higher values of extra energy brought by more powerful nodes.
Wireless sensor networks (WSNs) are an emerging technology for monitoring physical world. Different from the traditional wireless
networks and ad hoc networks, the energy constraint of WSNs makes energy saving become the most important goal of various
routing algorithms. For this purpose, a cluster based routing algorithm LEACH (low energy adaptive clustering hierarchy) has
been proposed to organize a sensor network into a set of clusters so that the energy consumption can be evenly distributed
among all the sensor nodes. Periodical cluster head voting in LEACH, however, consumes non-negligible energy and other resources.
While another chain-based algorithm PEGASIS (power- efficient gathering in sensor information systems) can reduce such energy
consumption, it causes a longer delay for data transmission. In this paper, we propose a routing algorithm called CCM (Chain-Cluster
based Mixed routing), which makes full use of the advantages of LEACH and PEGASIS, and provide improved performance. It divides
a WSN into a few chains and runs in two stages. In the first stage, sensor nodes in each chain transmit data to their own
chain head node in parallel, using an improved chain routing protocol. In the second stage, all chain head nodes group as
a cluster in a self- organized manner, where they transmit fused data to a voted cluster head using the cluster based routing.
Experimental results demonstrate that our CCM algorithm outperforms both LEACH and PEGASIS in terms of the product of consumed
energy and delay, weighting the overall performance of both energy consumption and transmission delay.
KeywordsWireless sensor network-Chain based routing-Cluster based routing-Mobile and ubiquitous computing
Wireless sensor networks with thousands of tiny sensor nodes, are expected to find wide applicability and increasing deployment in coming years, as they enable reliable monitoring and analysis of the environment. In this paper, we propose a hybrid routing protocol (APTEEN) which allows for comprehensive information retrieval. The nodes in such a network not only react to time-critical situations, but also give an overall picture of the network at periodic intervals in a very energy efficient manner. Such a network enables the user to request past, present and future data from the network in the form of historical, one-time and persistent queries respectively. We evaluated the performance of these protocols and observe that these protocols are observed to outperform existing protocols in terms of energy consumption and longevity of the network.
Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.
Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. Several network layer protocols have been proposed to improve the effective lifetime of a network with a limited energy supply. In this article we propose a centralized routing protocol called base-station controlled dynamic clustering protocol (BCDCP), which distributes the energy dissipation evenly among all sensor nodes to improve network lifetime and average energy savings. The performance of BCDCP is then compared to clustering-based schemes such as low-energy adaptive clustering hierarchy (LEACH), LEACH-centralized (LEACH-C), and power-efficient gathering in sensor information systems (PEGASIS). Simulation results show that BCDCP reduces overall energy consumption and improves network lifetime over its comparatives.
In order to prolong the network lifetime, energy-efficient protocols should be designed to adapt the characteristic of wireless sensor networks. Clustering Algorithm is a kind of key technique used to reduce energy consumption, which can increase network scalability and lifetime. This paper studies the performance of clustering algorithm in saving energy for heterogeneous wireless sensor networks. A new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks is proposed and evaluated. In the new clustering scheme, cluster-heads are elected by a probability based on the ratio between residual energy of node and the average energy of network. The high initial and residual energy nodes will have more chances to be the cluster-heads than the low energy nodes. Simulational results show that the clustering scheme provides longer lifetime and higher throughput than the current important clustering protocols in heterogeneous environments.
Regarding energy efficiency in Wireless Sensor Net-works (WSNs), routing protocols are engaged in a playful manner suggesting a consciousness of high value. In this research work, we present Away Cluster Heads with Adaptive Clustering Habit ((ACH) 2) scheme for WSNs. Our proposed scheme increases the stability period, network lifetime and throughput of the WSN. The beauty of our proposed scheme is its away Cluster Heads (CHs) formation, and free association mechanisms. The (ACH) 2 controls the CHs' election and selection in such a way that uniform load on CHs is ensured. On the other hand, free association mechanism removes back transmissions. Thus, the scheme operations minimize the over all energy consumption of the network. In subject to throughput maximization, a linear programming based mathematical formulation is carried out in which the induced subproblem of bandwidth allocation is solved by mixed-bias resource allocation scheme. We implement (ACH) 2 scheme, by varying node density and initial energy of nodes in homogeneous, heterogeneous, reactive and proactive simulation environments. Results justify its applicability.
In wireless sensor networks, nodes in the area of interest must report sensing readings to the sink, and this report always satisfies the report frequency required by the sink. This paper proposes a link-aware clustering mechanism, called LCM, to determine an energy-efficient and reliable routing path. The LCM primarily considers node status and link condition, and uses a novel clustering metric called the predicted transmission count (PTX), to evaluate the qualification of nodes for clusterheads and gateways to construct clusters. Each clusterhead or gateway candidate depends on the PTX to derive its priority, and the candidate with the highest priority becomes the clusterhead or gateway. Simulation results validate that the proposed LCM significantly outperforms the clustering mechanisms using random selection and by considering only link quality and residual energy in the packet delivery ratio, energy consumption, and delivery latency.
The clustering Algorithm is a kind of key technique used to reduce energy consumption. It can increase the scalability and lifetime of the network. Energy-efficient clustering protocols should be designed for the characteristic of heterogeneous wireless sensor networks. We propose and evaluate a new distributed energy-efficient clustering scheme for heterogeneous wireless sensor networks, which is called DEEC. In DEEC, the cluster-heads are elected by a probability based on the ratio between residual energy of each node and the average energy of the network. The epochs of being cluster-heads for nodes are different according to their initial and residual energy. The nodes with high initial and residual energy will have more chances to be the cluster-heads than the nodes with low energy. Finally, the simulation results show that DEEC achieves longer lifetime and more effective messages than current important clustering protocols in heterogeneous environments.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000. Includes bibliographical references (p. 145-154).
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