Keynotes Speaker: Energy Optimization of Wireless Sensor Networks Using Swarm Intelligence

Wireless Sensor Network (WSN) is a self-configured network of light-weight nodes, that are used in many applications by sending their data through this network to a Base Station (BS), which in turn, delivers the data to its final destination. In WSN, the sensor node’s energy is usually limited, and thus, the overall power consumption of the network is a real challenge. Numerous methods have been proposed to overcome this challenge by improving the overall power consumption and thus, prolonging the lifetime of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) protocol has been considered as a leading routing protocol in WSN, due to its low power consumption resultant from its cluster-based behavior. However, for dense networks, LEACH suffers from large burden over cluster head (CH), which might result in packet loss due to the induced congestion in the CH. In this paper, an improved algorithm based on LEACH is proposed to maximize the lifetime of WSN, by using another node to relieve CH’s burden. The routing path selection process is refined through selecting a new node that has the highest residual energy in each cluster to be an alternative gateway for the cluster head. Then, the routing path will be decided based on distance. This modified algorithm outperforms the original LEACH by 4.35% increase in the residual energy, which prolongs the network lifetime. However, there is a slight increase in the overhead ratio.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

Wireless Sensor Networks (WSNs) allow a large area to be monitored with various sensors. WSNs, although useful, are subject to Black Hole attacks. Defenses against attacks typically require more energy which reduces WSN lifetime. This thesis proposes a novel approach to detect and recover from attacks using an improved version of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is an energy efficient protocol for groups of battery-operated computers with sensor components in WSNs. This protocol works by having a node become a cluster head responsible for sending data to a sink. The sink can be either an access point or base station. After a set time the cluster heads go back to being regular nodes and a completely new set of nodes become cluster heads. There are secure versions of LEACH such as S-LEACH and MS-LEACH that provide encryption, but LEACH and its encrypted variants do not secure against Black Hole attacks. Our proposed approach, referred to as Anomaly Report Cycling - Low Energy Adaptive Clustering Hierarchy (ARC-LEACH), aims to provide defense from Black Hole attacks while also providing low energy cost. ARC-LEACH does this by absorbing an attack. When an attack occurs, it rotates cluster heads to reestablish communication, then sending a message from the sink to coordinate all nodes against the malicious nodes. ARC-LEACH actively blocks malicious nodes while leveraging the resilience of LEACH by building up stronger resistance to attacks. ARC-LEACH provides more defense capability when under attack from multiple malicious nodes that would otherwise be defenseless by LEACH, with only a limited increase in power consumption. The prototype for ARC-LEACH is implemented to show feasibility of the proposed approach.

Wireless Sensor Networks (WSNs) are a network of large number of wireless sensor nodes deployed over a wide geographical area. The sensor nodes have a limited amount of memory as well as power. Excess extent of energy is dissipated during data transmission to the base station (sink) from normal sensor nodes. The efficient way of prolonging the lifetime of sensor nodes is clustering which optimizes the energy dissipation of WSNs. In this paper, a homogenous clustering algorithm based on fuzzy logic has been proposed in which cluster head election is done with the help of two fuzzy descriptors namely residual energy and proximity distance. The sensor nodes have been hexagonally deployed in the homogenous environment. This covers the sensing area efficiently along with reducing the redundancy in data being transmitted by the sensor nodes. This algorithm has been compared with the low energy adaptive clustering hierarchy (LEACH) protocol. The simulation results show that the proposed approach outperforms the LEACH protocol in terms of number of data packets transmitted to base station, energy consumption and prolonged network lifetime.

Wireless sensor networks (WSN) are a yield of advancement in information technology and the requirement of large-scale communication infrastructures. Routing of data via selected paths is a critical task in WSN as process need to be carried on under resource constraint situations. This route identification problem can be better handled by employing appropriate heuristic bio-inspired computational intelligence optimization method. The most frequently applied routing is hierarchical routing algorithm is Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm which has limitations in identifying energy efficient inter and intra route communication, identification of number of cluster head (CH), an eminent node to communicate to CH and Base Station (BS), selection of CH, and computing residual energy level, etc. Hence, researchers are focusing on boosting the capability of LEACH clustering algorithm by applying heuristic bio-inspired computational intelligence optimization methods. The proposed work is an attempt in this direction through applying heuristic bio-inspired Grey Wolf Optimization algorithm (GWO) for improving the performance of LEACH algorithm. In this paper, focus is given to increase the overall network time by adapting two modifications to conventional algorithms (i) selection of vice cluster head (VCH) in addition to CH (VCH node will replace the CH when CH when CH node goes down due to unexpected reasons as sensor node work under critical and uninterruptable environments and (ii) selection of intra and inter relay nodes (intra relay node will enhance the life span during CH data gathering and inter relay node will further enhance the life span of CH by acting as a mediator between CH an BS). The Spyder-py3 tool is used to simulate the proposed algorithms, LEACH Binary Grey Wolf search based Optimization (LEACH-BGWO) and LEACH Discrete Grey Wolf search based Optimization (LEACH-DGWO) protocols. The proposed work is compared with cluster based LEACH algorithm, chain based power-efficient gathering in sensor information systems (PEGASIS) algorithm, bio-inspired GWO and Genetic Algorithm data Aggregation (GADA) LEACH protocols. The results prove that both proposed algorithms outperformed other conventional algorithms in terms of prolonged network lifespan and increased throughput. Among proposed algorithms LEACH-BGWO outperformed LEACH-DGWO

Wireless sensor network (WSN), a network of minute interconnected sensing element nodes communicating within themselves utilizing radio frequency signals and utilized in immensely enormous quantities to examine and realize the physical world. The communicating sensing element nodes are power-driven by batteries, which have a circumscribed lifetime. Hence managing the energy is a primary requisite for the design of WSN. In this paper, an efficient wireless sensor network utilizing a cooperative Multiple Input Multiple Output (MIMO) predicated on Space Time Trellis Code (STTC) is proposed. This STTC based cooperative MIMO technique is incorporated into Exclusive OR — Low Energy Adaptive Clustering Hierarchy (XOR-LEACH) protocol. For selection of cluster head, the last cluster head and a arbitrary binary vector are XORed together. The proposed system obtains amended performance and is compared with the existing LEACH protocol in terms of network lifespan and residual energy. This system performance in terms of Bit Error Rate (BER) has been analyzed for various detection techniques.

Wireless sensor networks (WSN) usually contains sensors powered by small batteries with limited power. These sensors collect data and transfer it to the base station (BS) where it will be manipulated; the process of data transfer could be direct or indirect depending on the used protocol. The batteries’ limited power will be partially consumed during every data transfer process. In some applications, such as agricultural, military and others, WSN use a large number of these sensors, so the energy consumption should be taken into consideration during the design of such networks as the batteries’ replacement is sometimes very difficult and expensive. Many researchers have been working on inventing the best battery-conserving protocols to extend the lifetime of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) protocol have better power-saving performance in this field, where the network is divided into groups called clusters, and each cluster selects its cluster head (CH). Sensors will transfer its data to the CH that belongs to it which in turn will transfer this data to the BS. However, a selection of CHs that ignores a node's energy change will cause the nodes serving as CHs to die earlier than the other nodes as too much energy is consumed. Also, the high frequency of re-use wastes a certain amount of energy. In order to distribute the power consumption evenly between the different nodes, we intend to classify the CH according to its distance from the BS, one operating at a close distance from the BS and the other at a far distance from it. The CH in the far distance will transfer its data not directly to the BS but through CH near to the BS. We aim with this proposal to distribute the energy consumption evenly between the nodes. Simulation results show that the proposed protocol GE-LEACH gives better results in the lifetime of the node especially in a field with a large area

Wireless Sensor Networks (WSNs) is the vast area and developing very speedily now-a-days. This paper gives some of the major applications and critical limitations of WSNs like power and lifespan, communication bandwidth, memory size. Sensor nodes are working by node energy so the energy consumption is the essential issue in WSN. Routing in WSN consumes more energy than any other phase. Various routing techniques in WSNs are discussed and different routing protocols are illustrated. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the popular and feasible hierarchical clustering routing protocols in WSN. Working of LEACH is explained in brief. Furthermore, the descendants of LEACH e.g. LEACH-C (Centralized LEACH), LEACH-B (Balanced LEACH), LEACH-F, Multihop LEACH, MS-LEACH (Multihop and Single hop LEACH), MH-LEACH etc. are discussed in terms of the energy utilization. By analyzing the variants of LEACH, it is observed that the energy requirement in the cluster set up phase or data transmission phase is minimized to minimize the total energy consumption of the WSN. To elect the proper cluster head node, centralized approach is followed. Afterwards, data transmission will use the multihop communication technique. This will help to save some energy when base station is located far away from the cluster head node. Proposed protocol aims to decrease the energy overhead of the sensor nodes. The new approach is proposed entitled PV-LEACH which will save the energy consumption in cluster setup phase and also in data transmission phase of the conventional LEACH protocol. So, this will enhance the performance ratio in terms of energy consumption and life time of the sensor nodes.

Background/Objectives: In the current work, a new zone based and energy-efficient cooperative routing protocol is presented by equally distributes the load of network among all nodes by establishing zones; separation of zones depends on the directions that address some of the requirements of Wireless Sensor Networks (WSNs). Methods/Statistical Analysis: Based on the analysis, cooperative communication improves the reliability and can be made the network topology more energy-efficient and stable. Reduction in the Transmission Time (TT) from source to destination by using Cluster Coordinates (CCOs) in inter-cluster and relay nodes in intra-cluster communication helps to prolong the network lifetime. The primary problem with existing solutions is the location of the Base Station (BS) increases transmission load upon Cluster Head (CH) which is nearby to the BS, so cluster depletes energy earlier as compared to others. Findings: The performance of proposed protocol is tested for dead nodes, alive nodes and packet send to BS. In homogeneous scenario, the results reveal that proposed Zone based Cooperative Routing Protocol (ZCRP) performs better in terms of energyefficiency and stability as compared to Chain based Cooperative Routing Protocol (CBCCP), Low Energy Adaptive Clustering Hierarchy (LEACH) and Stable Electron Protocol (SEP). Application/Improvements: Based on the performance of ZCRP, this can be beneficial for those real time applications where data delivered on time is essential like Border surveillance, healthcare systems and many others.

Restricted battery life is a crucial constraint in wireless sensor networks (WSNs). Many routing protocols have been proposed to reduce the energy consumption by extending the network lifetime. So, a new design of energy efficient routing using clustering is proposed where we use heterogeneous nodes for data transmission through the optimal path between cluster heads (CHs) and the base station (BS). This paper discusses the algorithm called Advanced-Multi-hop Low Energy Adaptive Clustering Hierarchy (LEACH) protocol with heterogeneous nodes. Multi-hop LEACH protocol changes the mode of communication to prolong the network lifetime from single hop to multi-hop between the CH and BS by reducing energy consumption. The paper tries to evaluate the performance of the network in terms of lifetime and stability by introducing the concept of optimum number of clusters and also considers the optimum number of hops in the network with heterogeneous nodes. This paper also provides the algorithm for the avoidance of the overlapping of the clusters and collisions in the network. For the evaluation and comparison of the performance of advanced single-hop and multi-hop energy efficient LEACH protocols with heterogeneous nodes, MATLAB simulations are carried out. Results show that advanced-multi-hop LEACH protocol outperforms the advanced single-hop LEACH protocol regarding energy efficiency, stability and network lifetime.

Wireless sensor networks are battery-powered ad hoc networks in which sensor nodes that are scattered over a region connect to each other and form multi-hop networks. Since these networks consist of sensors that are battery operated, care has to be taken so that these sensors use energy efficiently. This paper proposes an optimized hierarchical routing technique which aims to reduce the energy consumption and prolong network lifetime. In this technique, the selection of optimal cluster head (CHs) locations is based on artificial fish swarm algorithm that applies various behaviors such as preying, swarming, and following to the formulated clusters and then uses a fitness function to compare the outputs of these behaviors to select the best CHs locations. To prove the efficiency of the proposed technique, its performance is analyzed and compared to two other well-known energy efficient routing techniques: low-energy adaptive clustering hierarchy (LEACH) technique and particle swarm optimized (PSO) routing technique. Simulation results show the stability and efficiency of the proposed technique. Simulation results show that the proposed method outperforms both LEACH and PSO in terms of energy consumption, number of alive nodes, first node die, network lifetime, and total data packets received by the base station. This may be due to considering residual energies of nodes and their distance from base station , and alternating the CH role among cluster's members. Alternating the CH role balances energy consumption and saves more energy in nodes.

Wireless sensor networks (WSNs) are collection of sensor nodes that co-operate together to monitor an environment or a system. These sensor nodes works on limited battery source, one of the factor to be consider while designing a WSNs protocol is by efficient use of available energy resources to prolong network lifetime. Studies show that one of the efficient WSNs protocol is Low Energy Adaptive Cluster Hierarchy (LEACH). To modify LEACH protocol much more energy efficient, few improvements such as election of Cluster Head, assigning TDMA (Time division multiple access) slot to Cluster Members and multi hop for long distance communication were done. In this paper we propose Modified LEACH protocol for small network areas and Modified Multi hop LEACH protocol for large network areas. Simulation on LEACH, Modified LEACH and Modified Multi-hop LEACH protocol are done. Results shows that Modified LEACH have better network lifetime than LEACH protocol.

The Internet of Things (IoT) now uses the Wireless Sensor Network (WSN) as a platform to sense and communicate data. The increase in the number of embedded and interconnected devices on the Internet has resulted in a need for software solutions to manage them proficiently in an elegant and scalable manner. Also, these devices can generate massive amounts of data, resulting in a classic Big Data problem that must be stored and processed. Large volumes of information have to be produced by using IoT applications, thus raising two major issues in big data analytics. To ensure an efficient form of mining of both spatial and temporal data, a sensed sample has to be collected. So for this work, a new strategy to remove redundancy has been proposed. This classifies all forms of collected data to be either relevant or irrelevant in choosing suitable information even before they are forwarded to the base station or the cluster head. A Low-Energy Adaptive Clustering Hierarchy (LEACH) is a cluster-based routing protocol that uses cluster formation. The LEACH chooses one head from the network sensor nodes, such as the Cluster Head (CH), to rotate the role to a new distributed energy load. The CHs were chosen randomly with the possibility of all CHs being concentrated in one locality. The primary idea behind such dynamic clustering was them resulted in more overheads due to changes in the CH and advertisements. Therefore, the LEACH was not suitable for large networks. Here, Particle Swarm Optimization (PSO) and River Formation Dynamics are used to optimize the CH selection (RFD). The results proved that the proposed method to have performed better compared to other methods.

Routing protocols in wireless sensor network are vulnerable to various malicious security attacks that can degrade network performance and lifetime. This becomes more important in cluster routing protocols that is composed of multiple node and cluster head, such as low energy adaptive clustering hierarchy (LEACH) protocol. Namely, if an attack succeeds in failing the cluster head, then the entire set of nodes fail. Therefore, it is necessary to develop robust recovery schemes to overcome security attacks and recover packets at short times. Hence this paper proposes a detection and recovery scheme for selective forwarding attacks in wireless sensor networks using LEACH protocol. The proposed solution features near-instantaneous recovery times, without the requirement for feedback or retransmissions once an attack occurs.

The integration of cognitive radios and wireless sensor networks enables a new paradigm of communication in which, sensor nodes can avoid heavily crowded transmission bands by tuning their transmission parameters to less crowded bands thanks to the cognitive radio capabilities. In such setting, sensor nodes act as a secondary user, opportunistically accessing vacant channels within a band originally licensed to a primary user. In this paper, we discuss the problem of how to cluster cognitive radio sensor nodes in a dynamic frequency environment set by the primary users. We introduce Cognitive LEACH (CogLEACH), which is a spectrum-aware extension of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. CogLEACH is a fast, decentralized, spectrum-aware, and energy efficient clustering protocol for cognitive radio sensor networks. CogLEACH uses the number of vacant channels as a weight in the probability of each node to become a cluster head. We show that CogLEACH improves the throughput and lifetime of the network compared to the regular LEACH protocol that is operating in the same settings.