Threshold Sensitive Energy Efficient Sensor Network Research Articles

Optimization of wireless sensor networks energy consumption by the clustering method based on the firefly algorithm

Wireless sensor networks (WSNs) contain an inordinate number of sensor nodes that are spatially distributed. The network is composed of entities that determine its lifetime. The WSN nodes are equipped with a battery whose autonomy is limited in duration. In this paper, different solutions are introduced to improve the overall energy consumption of the network in order to improve its lifetime. Contrary to many works considering the clustering algorithm as one potential candidate to improve the network's lifetime, this study has investigated the firefly algorithm optimization where an optimal cluster head is selected from a group of nodes. The set-up process of the cluster head is based on a set of conditions. To measure the performance of the proposed approach, the number of dead nodes and data packets received by the base station (BS) or sink node are considered. The results are tested on 100 nodes for 5000 transmission rounds, the amount of data transported is 20 million bits a little more than the other methods. It has been shown that the proposed solution outperformed the traditional low energy adaptive clustering hierarchy (LEACH), threshold sensitive energy efficient sensor network (TEEN), and developed distributed energy-efficient clustering (DEEC) approaches.

ESSD: Energy Saving and Securing Data Algorithm for WSNs Security

The Wireless Sensor Networks (WSNs) are characterized by their widespread deployment due to low cost, but the WSNs are vulnerable to various types of attacks. To defend against the attacks, an effective security solution is required. However, the limits of these networks’ battery-based energy to the sensor are the most critical impediments to selecting cryptographic techniques. Consequently, finding a suitable algorithm that achieves the least energy consumption in data encryption and decryption and providing a highly protected system for data remains the fundamental problem. In this research, the main objective is to obtain data security during transmission by proposing a robust and low-power encryption algorithm, in addition, to examining security algorithms such as ECC and MD5 based on previous studies. In this research, the Energy Saving and Securing Data algorithm (ESSD) algorithm is introduced, which provides the Message Digest 5 (MD5) computation simplicity by modifying the Elliptic Curve Cryptography (ECC) under the primary condition of power consumption. These three algorithms, ECC, MD5, and ESSD, are applied to Low Energy Adaptive Clustering Hierarchy (LEACH) and Threshold-sensitive Energy Efficient Sensor Network Protocol (TEEN) hierarchical routing algorithms which are considered the most widely used in WSNs. The results of security methods under the LEACH protocol show that all nodes are dead at 456, 496, and 496, respectively, to ECC, MD5, and ESSD. The results of security methods under the TEEN protocol show that the test ends at 3743, 4815, and 4889, respectively, to ECC, MD5, and ESSD. Based on these results, the ESSD outperforms better in terms of increased security and less power consumption. In addition, it is advantageous when applied to TEEN protocol.

Energy efficient routing in wireless sensor network based on mobile sink guided by stochastic hill climbing

In Wireless Sensor Networks (WSNs), the reduction of energy consumption in the batteries of a sensor node is an important task. Sensor nodes of WSNs perform three significant functions such as data sensing, data transmitting and data relaying. Routing technique is one of the methods to enhance the sensor nodes battery lifetime. Energy optimization is done by using one of the heuristic routing methods for sensing and transmitting the data. To enhance the energy optimization mainly concentrated on data relaying. In this work stochastic hill climbing is adapted. The proposed solution for data relaying utilizes geographical routing and mobile sink technique. The sink collects the data from cluster heads and movement of the sink is routed by stochastic hill climbing. Network simulator 2 is used for experimentation purpose. This work also compares with the existing routing protocols like Energy-efficient Low Duty Cycle (ELDC), Threshold sensitive Energy Efficient sensor Network (TEEN) and Adaptive clustering protocol. The proposed work shows promising results with respect to lifetime, average energy of nodes and packet delivery ratio.

Performance Review of Selected Topology-Aware Routing Strategies for Clustering Sensor Networks

In this paper, cluster-based routing (CBR) protocols for addressing issues pertinent to energy consumption, network lifespan, resource allocation and network coverage are reviewed. The paper presents an indepth performance analysis and critical review of selected CBR algorithms. The study is domain-specific and simulation-based with emphasis on the tripartite trade-off between coverage, connectivity and lifespan. The rigorous statistical analysis of selected CBR schemes was also presented. Network simulation was conducted with Java-based Atarraya discrete-event simulation toolkit while statistical analysis was carried out using MATLAB. It was observed that the Periodic, Event-Driven and Query-Based Routing (PEQ) schemes performs better than Low-Energy Adaptive Clustering Hierarchy (LEACH), Threshold-Sensitive Energy-Efficient Sensor Network (TEEN) and Geographic Adaptive Fidelity (GAF) in terms of network lifespan, energy consumption and network throughput.Keywords: Wireless sensor network, Hierarchical topologies, Cluster-based routing, Statistical analysis, Network simulation

Optimization by Genetic Algorithm in Wireless Sensor Networks Utilizing Multiple Sinks

WSN (Wireless Sensor Network) comprises of small-sized and constraint-capability SN (Sensor Nodes) which record, send and receive data, sensed to a sink. The network lifetime and energy usability are important challenges to be dealt with. During the working of the SN, the maximum amount of energy is consumed than sensing and processing of data. Therefore, an efficient transmission of the data is required so that the energy can be saved. In this paper, a novel routing and scheduling method for WSNs using GA (Genetic Algorithm) is presented, where the sinks employed on four sides of the sensor field. These sinks collect the data from the SNs having the optimal distance towards the respective sink. The proposed scheme finds the optimized path using GA, during transmission of data from SN to the nearest sink. First, we run the GA for determination of routing paths, where a source SN finds the possible number of optimal hops. Second, the hops or intermediate relay SNs are assumed to relay the data towards the sink, efficiently. The performance is experimented and evaluated using MATLAB R2016b. The simulations have carried out through comparing the proposed scheme with TEEN (Threshold Sensitive Energy Efficient Sensor Network Protocol). The results of simulation comprise of 10 and 20 number of SNs, discretely. Additionally, the direct distance of each node is calculated and the distance through multiple hops from/to the nearest sink is also evaluated. The achievements of the proposed technique are to save both energy and distance for the sake of network longevity and optimal and precise data delivery by multiple hops.

Optimization on TEEN routing protocol in cognitive wireless sensor network

In order to improve the energy efficiency of cognitive wireless sensor network, this paper introduces threshold-sensitive energy efficient sensor network (TEEN) routing protocol into cognitive wireless sensor network. To make routing and spectrum more stable, this paper presents advanced threshold-sensitive energy efficient sensor network (A-TEEN), which is the optimization of TEEN. A-TEEN optimized the cluster head election method compared with TEEN. Simulation result shows that compared with low-energy adaptive clustering hierarchy, TEEN increases the energy efficiency and extends life cycle of cognitive wireless sensor network. A-TEEN improves the energy efficiency and lifetime further operating in the same settings compared with the regular TEEN.

DEAD NODE DETECTION IN TEEN PROTOCOL: SURVEY

Now a day’s wireless sensor network has become an interesting research field. Network life time and energy efficiency are one of the main concerns for wireless sensor networks. Sensors are constrained in terms of battery power, storage, limited processing capacity etc. Because of these reasons new protocols are proposed for wireless sensor network. This paper only deals with cluster based hierarchical protocol TEEN (Threshold Sensitive Energy Efficient Sensor Network Protocol). The sensor network architecture in TEEN is based on a hierarchical clustering. TEEN is data-centric, reactive, event-driven protocol which is best suited for time critical application. It transmits data based on hard threshold and soft threshold values. If the thresholds are not reached, then nodes will never communicate. The user will not get any data from network and will not come to know if all the nodes die. So, user will not be able to distinguish between how many nodes are alive or dead in network and will not be able to know about network lifetime. This paper deals with that node will be able to tell base station or sink before leaving network and base station will be aware of alive and dead nodes in the network.

Key Schemes for Security Enhanced TEEN Routing Protocol in Wireless Sensor Networks

In wireless sensor networks (WSNs), hierarchical routing protocol is commonly used for energy efficiency. In particular, the TEEN (Threshold sensitive Energy Efficient sensor Network) protocol is used widely as a basic clustered multihop routing protocol. However, energy efficient routing protocols without proper security suffer from many security vulnerabilities. Hence, in this paper, we propose a hybrid key scheme specially for the TEEN protocol: a symmetric key scheme for the intracluster and a public key scheme for the intercluster. The simulation results show that network lifetime of the proposed hybrid key scheme decreases about 8% than the TEEN protocol and about 4% compared with the TEEN protocol with symmetric key scheme. On the other hand, a hybrid key scheme provides better probability of successful transmission than that of the symmetric key scheme.

Hybrid AODV protocol for energy efficient routing in wireless sensor networks

Energy efficiency is one of the major concerns in wireless sensor networks since it impacts the network lifetime. The trade-off between sensed information and the amount of energy expended in communication are considered in developing protocols as sensor networks are resource constrained. In this paper, the ad hoc on-demand distance vector (AODV) protocol and threshold-sensitive energy efficient sensor network (TEEN) protocol are integrated to form a hybrid AODV routing protocol. The hybrid protocol is based on the characteristics of both protocols. The primary design objective of this research is to determine the active nodes and enhance the energy efficiency. Extensive simulation results show that the proposed protocol is efficient in transmission of packets, reduction in latency, energy consumption and throughput.

Analytical query response time evaluation for a two-level clustering hierarchy based wireless sensor network routing protocol

In this letter, we analytically evaluate the average query response time of the Two-level Hierarchical Clustering based Hybrid-routing Protocol (THCHP) proposed recently for wireless sensor networks (WSNs). The accuracy of the average query response time analysis is verified via numerical simulations. Additionally, average query response time comparisons, between THCHP and a previously proposed Adaptive Periodic Threshold-sensitive Energy Efficient sensor Network (APTEEN) protocol, show that THCHP is better suited than APTEEN for delay sensitive WSN applications.

An analytical model for information retrieval in wireless sensor networks using enhanced apteen protocol

Wireless sensor networks are a new class of ad hoc networks that will find increasing deployment in coming years, as they enable reliable monitoring and analysis of unfamiliar and untested environments. The advances in technology have made it possible to have extremely small, low powered sensor devices equipped with programmable computing, multiple parameter sensing, and wireless communication capability. Because of their inherent limitations, the protocols designed for such sensor networks must efficiently use both limited bandwidth and battery energy. We develop an M/G/1 model to analytically determine the delay incurred in handling various types of queries using our enhanced APTEEN (Adaptive Periodic Threshold-sensitive Energy Efficient sensor Network protocol) protocol. Our protocol uses an enhanced TDMA schedule to efficiently incorporate query handling, with a queuing mechanism for heavy loads. It also provides the additional flexibility of querying the network through any node in the network. To verify our analytical results, we have simulated a temperature sensing application with a Poisson arrival rate for queries on the network simulator ns-2. As the simulation and analytical results match perfectly well, this can be said to be the first step towards analytically determining the delay characteristics of a wireless sensor network.