Traffic Based Clustering In Wireless Sensor Network

2009 11th International Conference on Computer Modelling and Simulation, 2009

Wireless sensor networks have the problem of lifetime and scalability. To increase lifetime and scalability it's necessary to have control over topology of the network. Dynamic clustering with adaptive feature is the best way to achieve the above. In this paper we propose a dynamic multi-level hierarchal clustering (DMH) approach for sensor networks. The proposed approach will create a dynamic system which can vary topology architecture according to traffic patterns. This approach can decide size of cluster, nodes in a cluster and level of hierarchy of a cluster and will vary according to state of the system. In this approach for clustering we use nodes having multiple energy level for energy efficient clustering and cluster heads are selected periodically based on different attributes (i.e. residual energy, node degree etc) but unlike previous approaches here we use mutual negotiation between nodes as a criteria for cluster formation. Also here we used dynamic adaptive level of hierarchy according to the traffic pattern and use the highest level of hierarchy for routing of aggregated data to the base station.

International Journal of Research and Analytical Reviews (IJRAR), 2018

The field of Wireless sensor networks is the main attraction of various researchers due to its practical applications in daily life. It comprises of sensor nodes geographically distributed over an area, which sense the environmental conditions like temperature, humidity etc and pass this information to the sink .As these nodes are non-rechargeable means energy constrained, so main focus of the researches in this field is to make it energy efficient as par as possible and prolong its network lifetime .Clustering is one of the hierarchical routing technique which is used to make the network energy efficient. It can be further improved by adopting non-uniform cluster size techniques and sub-clustering in farther as well as larger clusters. Cluster heads of distant clusters will need to communicate with only sub-cluster heads which further covers the entire cluster members. This proposed model effectively improves lifetime over LEACH. Keywords-Wireless Sensor Networks, effective lifetime, sub-clustering, cluster head and residual energy. I. INTRODUCTION As sensor nodes have limited and non-rechargeable energy resources, energy is a very scarce resource and has to be managed carefully in order to extend the lifetime of the sensor networks [1]. In recent years, researchers have done a lot of studies and proved that clustering is an effective scheme in increasing the scalability and lifetime of wireless sensor networks [2-5]. In clustering schemes, there are two kinds of nodes in one cluster, one cluster head (CH) and several cluster members (CMs). Cluster members gather data from the environment periodically and send the data to cluster heads. Cluster heads aggregate the data from their cluster members, and send the aggregated data to the base station (BS). There are two kinds of communications between cluster heads and the BS, single-hop communication and multi-hop communication. In multi-hop communication clustering algorithms, the energy consumption of cluster heads consists of the energy for receiving, aggregating and sending the data from their cluster members (intra-cluster energy consumption) and the energy for forwarding data for their neighbor cluster heads (inter-cluster energy consumption) [1]. Cluster-based communication protocols have significant savings in total energy consumption of a sensor network. In these protocols, creation of clusters and assigning special tasks to cluster heads can greatly contribute to overall system scalability, lifetime, and bandwidth efficiency [6].Clustering reduces the energy dissipation in the network by aggregating the messages of cluster members ,thus reducing the number of messages being transferred to the sink. Moreover, the size of the clusters must be optimum as exploiting both small and large clusters would make the sensor networks energy inefficient. When the cluster size is very large (e.g. one cluster of whole network), the nodes have to transmit data very far to the cluster head, consuming more energy. And when the cluster size is very small (e.g. one node in each cluster) the number of messages to be transferred to the sink increases, so the energy saving by aggregation would be reduced, thus resulting in more dissipation of network energy. [6] Clustering is grouping of sensor nodes. Here, each cluster is managed by a special node or leader, called cluster head (CH), which is responsible for coordinating the data transmission activities of all sensors in its group.CH is decided with a different probability [7,8].The selection of cluster head in the clusters contribute a lot to the overall efficiency. In clustering networks, the imbalanced energy consumption among nodes is the key factor affecting the network lifetime. In order to balance the energy consumption among nodes, clustering algorithms for networks with uniform node distribution tend to construct uniformly distributed cluster heads, so that the clusters have the approximate number of members and coverage areas. Thus, the intra-cluster energy consumption of cluster heads is approximate and the energy consumption of cluster heads can be balanced. For cluster members, the maximum communicate distances of cluster members are approximate, because of the uniform cluster sizes. Thus, the energy consumption of cluster members can be balanced too. Therefore, the uniformly distributed cluster head set can balance the energy consumption among nodes and finally prolong the network lifetime [1]. Leach is the very basic protocol used for uniformly distributed nodes. It is simple and does not require a large communication overhead. But its performance in heterogeneous networks is not very well; because it elects cluster heads without considering the residual energy of the nodes .To solve this problem. Researchers improved LEACH and proposed new algorithms [1, 9-11]. Also, LEACH has a disadvantage of non-uniform energy consumption by the cluster heads, so they dissipate their energy quickly. Its proposed solution is non uniform clustering.

2012 5th International Conference on New Technologies, Mobility and Security (NTMS), 2012

Clustering can be used as an effective technique to achieve both energy load balancing and an extended lifetime for a wireless sensor network (WSN). This paper presents a novel approach that first creates energy balanced fixed/static clusters, and then, to attain energy load balancing within each fixed cluster, rotates the role of cluster head through uniformly quantized energy levels based approach to prolong the overall network lifetime. The method provided herein, not only provides near-dynamic clustering performance but also reduces the complexity due to the fact that cluster formation phase is implemented once. The presented simulation results clearly show the efficacy of this proposed algorithm and thus, it can be used as a practical approach to obtain maximized network lifetime for energy balanced clusters in fixed clustering environments.

Extending the longevity, is a significant job to be accomplished by these sensor networks. The traditional routing protocols could not be applied here, due to its nodes powered by batteries. Nodes are often clustered in to non-overlapping clusters, so as to provide energy efficiency. A concise overview on clustering processes, within wireless sensor networks is given in this paper. But it is difficult to replace the deceased batteries of the sensor nodes. A distinctive sensor node consumes much of its energy during wireless communication. This research work suggests the development of a hierarchical distributed clustering mechanism, which gives improved performance over the existing clustering algorithm LEACH. The two hiding concepts behind the proposed scheme are the hierarchical distributed clustering mechanism and the concept of threshold. Energy utilization is significantly reduced, thereby greatly prolonging the lifetime of the sensor nodes.

Clustering is a well known approach to cope with large nodes density and efficiently conserving energy in Wireless Sensor Networks (WSN). Load balancing is an effective approach for optimizing resources like channel bandwidth, the main objective of this paper is to combine these two valuable approaches in order to significantly improve the main WSN service such as information routing. So, our proposal is a routing protocol in which load traffic is shared among cluster members in order to reduce the dropping probability due to queue overflow at some nodes. To this end, a novel hierarchical approach, called Hierarchical Energy-Balancing Multipath routing protocol for Wireless Sensor Networks (HEBM) is proposed. The HEBM approach aims to fulfill the following purposes: decreasing the overall network energy consumption, balancing the energy dissipation among the sensor nodes and as direct consequence: extending the lifetime of the network. In fact, the cluster-heads are optimally determined and suitably distributed over the area of interest allowing the member nodes reaching them with adequate energy dissipation and appropriate load balancing utilization. In addition, nodes radio are turned off for fixed time duration according to sleeping control rules optimizing so their energy consumption. The performance evaluation of the proposed protocol is carried out through the well-known NS2 simulator and the exhibited results are convincing. Like this, the residual energy of sensor nodes was measured every 20 s throughout the duration of simulation, in order to calculate the total number of alive nodes. Based on the simulation results, we concluded that our proposed HEBM protocol increases the profit of energy, and prolongs the network lifetime duration from 32% to 40% compared to DEEAC reference protocol and from 25% to 28% compared to FEMCHRP protocol. The authors also note that the proposed protocol is 41.7% better than DEEAC with respect to FND (Fist node die), and 25.5% better than FEMCHRP with respect to LND (last node die) while maintaining the average data transmission delay. We found also that HEBM achieved 66.5% and 40.6% more rounds than DEEAC and FEMCHRP respectively.

International …, 2011

Wireless sensor nodes are use most embedded computing application. Multihop cluster hierarchy has been presented for large wireless sensor networks (WSNs) that can provide scalable routing, data aggregation, and querying. The energy consumption rate for sensors in a WSN varies greatly based on the protocols the sensors use for communications. In this paper we present a cluster based routing algorithm. One of our main goals is to design the energy efficient routing protocol.

2018

One of the major challenges in wireless sensor network (WSN) is to curb down congestion in the network’s traffic, without compromising with the energy of the sensor nodes. Congestion affects the continuous flow of data, loss of information, delay in the arrival of data to the destination and unwanted consumption of significant amount of the very limited amount of energy in the nodes. In wireless sensor networks (WSN), unbalanced load allocation results in congestion. Load balancing is of great importance in wireless sensor networks because of the limited resource constraint. Proposed method combines the idea of clustering and traffic allocation protocol to achieve load balancing and network life time. Analysis and simulation shows that the new approach can improve the network performance in terms of network life time, energy, load balancing, end-to-end delay, packet drop ratio. KeywordsClustering, disjoint path, load balancing, traffic distribution, wireless sensor network (WSN). IN...

Wireless sensor networks represent the next generation of sensing machines and structures. Inherent limited energy resource is the one of the limitations of wireless sensor nodes. In order to distribute the energy dissipated throughout the wireless sensor network, data load of the sensor nodes must be balanced. Clustering is one of the key mechanisms for load balancing. Clustering algorithms may result in some clusters that have more members than other clusters in the network and uneven cluster sizes negatively affect the load balancing in the network. In our proposed work we improve a cluster algorithm for load balancing in clusters. Efficiency of WSNs measured by the total distance between nodes to the base station and data amount that has is transfer. Cluster–Head which is totally responsible for the creating cluster and cluster nodes may affect the performance of the cluster. The purposed algorithm we choose a Master Node and vice master node for regions and sub regions. To find out the master node we partition the region and find out the centered of region, by which we select the master node. For every partitioned region again portioned if required and much like depend on master node and nodes in that partitioned area. Our purposed algorithm we can find the better lifetime and energy efficiency.

2003

Wireless sensor networks have potential to monitor environments for both military and civil applications. Due to inhospitable conditions these sensors are not always deployed uniformly ion the area of interest. Since sensors are generally constrained in on-board energy supply, efficient management of the network is crucial to extend the life of the sensors. Sensors' energy cannot support long haul communication to reach a remote command site and thus requires many levels of hops or a gateway to forward the data on behalf of the sensor. In this paper, we propose an algorithm to network these sensors in to well define clusters with less energy-constrained gateway nodes acting as cluster-heads, and balance load among these gateways. Simulation results show how our approach can balance the load and improve the lifetime of the system.

International Journal of Information Technology and Computer Science, 2014

Generally, grouping sensor nodes into clusters has been widely adopted by the research community to satisfy the above scalability objective and generally achieve high energy efficiency and prolong network lifetime in large scale WSN environments. The corresponding hierarchical routing and data gathering protocols imply cluster based organization of the sensor nodes in order that data fusion and aggregation are possible, thus leading to significant energy savings. We propose a clustering approach which organizes the whole network into a connected hierarchy and discuss the design rationale of the different clustering approaches and design principles. Further, we propose several key issues that affect the practical deployment of clustering techniques in wireless sensor network applications. Index Terms-WSN (Wireless Sensor Network), Sensor Node (SN), Base Station (BS), Cluster Head (CH), Mobile ad hoc network (MANET).