Multihop clustering algorithm for load balancing in wireless sensor networks

The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach

Multihop clustering algorithm for load balancing in wireless sensor networks

The paper presents a new cluster based routing algorithm that exploits the redundancy properties of the sensor networks in order to address the traditional problem of load balancing and energy efficiency in the WSNs.The algorithm makes use of the nodes in a sensor network of which area coverage is covered by the neighbours of the nodes and mark them as temporary cluster heads. The algorithm then forms two layers of multi hop communication. The bottom layer which involves intra cluster communication and the top layer which involves inter cluster communication involving the temporary cluster heads. Performance studies indicate that the proposed algorithm solves effectively the problem of load balancing and is also more efficient in terms of energy consumption from Leach and the enhanced version of Leach

Study of Energy Efficient Clustering Algorithms for Wireless Sensor Network

Energy utilization and network life time are key issues in design of routing protocols for Wireless sensor network. Many algorithms have been proposed for reducing energy consumption and to increase network life time of the WSN. Clustering algorithms have gained popularity in this field, because of their approach in cluster head selection and data aggregation. LEACH (distributed) is the first clustering routing protocol which is proven to be better compared to other such algorithms. TL-LEACH is one of the descendants of LEACH that saves better the energy consumption by building a two-level hierarchy. It uses random rotation of local cluster base stations to better distribute the energy load among the sensors in the network especially when the density of network is higher. As the clusters are adaptive in LEACH and TL-LEACH, poor clustering set-up during a round will affect overall performance. However, using a central control scheme for cluster set-up may produce better clusters by distributing the cluster head nodes throughout the network. LEACH-C is another modification to LEACH that realizes the above idea and provides better results through uniform distribution of cluster heads avoiding redundant creation of cluster heads in a small area. In our project, we propose a centralized multilevel scheme called CML-LEACH for energy efficient clustering that assumes random distribution of sensor nodes which are not mobile. The proposed scheme merges the idea of multilevel hierarchy, with that of the central control algorithm providing uniform distribution of cluster heads throughout the network, better distribution of load among the sensors and improved packet aggregation. This scheme reduces energy consumption and prolongs network life time significantly as compared to LEACH, TL-LEACH and LEACH-C. The simulation results show comparisons of our scheme with the existing LEACH, TL-LEACH and LEACH-C protocols against chosen performance metrics, using Omnet++

FEHCA: A Fault-Tolerant Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks

Technological advancements have led to increased confidence in the design of large-scale wireless networks that comprise small energy constraint devices. Despite the boost in technological advancements, energy dissipation and fault tolerance are amongst the key deciding factors while designing and deploying wireless sensor networks. This paper proposes a Fault-tolerant Energy-efficient Hierarchical Clustering Algorithm (FEHCA) for wireless sensor networks (WSNs), which demonstrates energy-efficient clustering and fault-tolerant operation of cluster heads (CHs). It treats CHs as no special node but equally prone to faults as normal sensing nodes of the cluster. The proposed scheme addresses some of the limitations of prominent hierarchical clustering algorithms, such as the randomized election of the cluster heads after each round, which results in significant energy dissipation; non-consideration of the residual energy of the sensing nodes while selecting cluster heads, etc. It utilizes the capability of vector quantization to partition the deployed sensors into an optimal number of clusters and ensures that almost the entire area to be monitored is alive for most of the network’s lifetime. This supports better decision-making compared to decisions made on the basis of limited area sensing data after a few rounds of communication. The scheme is implemented for both friendly as well as hostile deployments. The simulation results are encouraging and validate the proposed algorithm.articl

Study of clustering algorithms for brain computer interface using wireless sensor networks

BCIs are often directed at expanding, assisting or restoring human sensory-motor or cognitive functions by offering a direct communication route between the human brain and any external devices. In Invasive BCI the sensors are implanted inside the brain on the surface of cerebrum. So far invasive BCI using wireless sensors has not been achieved. Most research to date regarding invasive BCI using wireless sensors has revolved around communications along the surface of the body by the use of traditional electromagnetic (EM) radio-frequency carrier waves. The major impediment that we face today in order to enable this dream of networked-implantable-devices is caused by the physical nature of propagation in humans. Our body is composed primarily of water, which is a medium through which Radio frequency EM waves do not easily propagate. Therefore, in this article we take a distinctive perspective and inspect the possibility of using ultrasonic waves to wirelessly interconnect sensors in the brain. We propose a new energy model required for ultrasonic propagation. Since the sensors need to be implanted inside the brain, therefore to avoid frequent implants we design a new clustering algorithm which overcomes the drawbacks of existing LEACH algorithm and uses lesser energy, hence enhancing the lifetime of sensors

A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks

The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios

DISTRIBUTED MULTI-HOP ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS

In a Wireless Sensor Network (WSN), routing is the process of finding a cost-effective route in terms of power consumption. As an evaluation criterion for the WSN performance, network lifetime is directly affected by the routing method. In a wide variety of WSNs, different techniques are used as routing methods, such as shortest distance path. In this paper, we propose a novel algorithm, optimizing power consumption in WSN nodes, based on the shortest path algorithm. In this approach, the energy level of nodes and their geographical distance from each other contribute to the weight of the connecting path. The proposed algorithm is used as a data dissemination method in WSNs with randomly scattered nodes. We also apply Dijkstra’s shortest path algorithm to the same networks. The results showed that the proposed algorithm increases the network lifetime up to 30 % by preventing nodes with low charge levels from early disconnection

Intrusion detection in IPv6-enabled sensor networks.

In this research, we study efficient and lightweight Intrusion Detection Systems (IDS) for ad-hoc networks through the lens of IPv6-enabled Wireless Sensor Actuator Networks. These networks consist of highly constrained devices able to communicate wirelessly in an ad-hoc fashion, thus following the architecture of ad-hoc networks. Current state of the art IDS in IoT and WSNs have been developed considering the architecture of conventional computer networks, and as such they do not efficiently address the paradigm of ad-hoc networks, which is highly relevant in emerging network paradigms, such as the Internet of Things (IoT). In this context, the network properties of resilience and redundancy have not been extensively studied. In this thesis, we first identify a trade-off between the communication and energy overheads of an IDS (as captured by the number of active IDS agents in the network) and the performance of the system in terms of successfully identifying attacks. In order to fine-tune this trade-off, we model networks as Random Geometric Graphs; these are a rigorous approach that allows us to capture underlying structural properties of the network. We then introduce a novel IDS architectural approach that consists of a central IDS agent and set of distributed IDS agents deployed uniformly at random over the network area. These nodes are able to efficiently detect attacks at the networking layer in a collaborative manner by monitoring locally available network information provided by IoT routing protocols, such as RPL. The detailed experimental evaluation conducted in this research demonstrates significant performance gains in terms of communication overhead and energy dissipation while maintaining high detection rates. We also show that the performance of our IDS in ad-hoc networks does not rely on the size of the network but on fundamental underling network properties, such as the network topology and the average degree of the nodes. The experiments show that our proposed IDS architecture is resilient against frequent topology changes due to node failures