Lifetime Maximization of Wireless Sensor Networks using Improved Genetic Algorithm based Approach (original) (raw)
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Hybrid Genetic Algorithm based Approach for Energy Efficient Routing in Wireless Sensor Networks
2013
The nodes in Wireless Sensor Networks have limited energy and are seriously constrained by the battery life. An energy aware routing scheme can greatly enhance the lifetime of WSNs. However the conventional mathematical formulations for energy efficient routing are computationally very time consuming and large and they are not suitable for practical sensor networks. In this paper the Elitist genetic algorithm with memory scheme and simulated annealing algorithms are combined to find an optimal energy efficient route for the sensor nodes towards the sink node to prolong the network lifetime. The proposed scheme selects a path which has got maximum of minimum power available among the alternative paths thus is able to find the optimal solution for larger networks. The proposed scheme proves to give a faster and significant solution compared to traditional routing schemes.
Chinese Journal of Engineering, 2014
Wireless sensor networks have gained worldwide attention in recent years due to the advances made in wireless communication. Unequal energy dissipation causes the nodes to fail. The factors causing the unequal energy dissipation are, firstly, the distance between the nodes and base station and, secondly, the distance between the nodes themselves. Using traditional methods, it is difficult to obtain the high precision of solution as the problem is NP hard. The routing in wireless networks is a combinatorial optimization problem; hence, genetic algorithms can provide optimized solution to energy efficient shortest path. The proposed algorithm has its inherent advantage that it keeps the elite solutions in the next generation so as to quickly converge towards the global optima also during path selection; it takes into account the energy balance of the network, so that the life time of the network can be prolonged. The results show that the algorithm is efficient for finding the optimal...
Energy Efficient Maximum Lifetime Routing For Wireless Sensor Network
International Journal of Advanced Smart Sensor Network Systems, 2012
In wireless sensor network, sensors or nodes are generally battery powered devices. These nodes have limited amount of initial energy that are consumed at different rates, depending on the power level. For maximizing the lifetime of these nodes most routing algorithm in wireless sensor networks uses the energy efficient path. These energy efficient routing algorithms select a best path for data transmission and consume less energy. But a single best path puts extra load to a specific node causing lower lifetime. This paper proposes an energy efficient maximum lifetime routing algorithm. It is based on a greedy heuristic technique to maximize lifetime of the system. For achieving maximum system lifetime proposed algorithm uses the energy cost of links for constructing energy efficient path. The Simulation results demonstrate that EEMLR algorithm significantly minimizes energy consumption of each node and balanced the energy for entire network as well as extend the network lifetime.
International Journal of Ad hoc, Sensor & Ubiquitous Computing, 2011
In wireless sensor network, devices or nodes are generally battery powered devices. These nodes have limited amount of initial energy that are consumed at different rates, depending on the power level. The lifetime of the network is defined as the time until the first node fails (or runs out of battery). In this paper different type of energy efficient routing algorithms are discussed and approach of these algorithms is to maximize the minimum lifetime of wireless sensor network. Special attention has been devoted for algorithms formulate the routing problem as a linear programming problem, which uses the optimal flow path for data transmission and gives the optimum results. Advantages, limitations as well as comparative study of these algorithms are also discussed in this paper.
Studies in Informatics and Control
For the last few decades, Wireless Sensor Networks (WSNs) has been drawing important considerations due to having application-specific characteristics. These WSNs are usually deployed in one of the following two manners: deterministic or random (ad hoc). In the ad hoc manner, the deployment is mostly subjected to a significant number of limitations such as limited bandwidth, routing failure, storage and computational constraints. The overall performance of the WSNs is determined by a robust routing scheme. Nevertheless, WSNs include prominent application parameters for routing such as energy usage and network longevity. Therefore, the routing scheme is the key element for the longevity and usability of WSNs. In the conventional WSNs, the routing design can be opted for the network longevity optimization, while, assuming all the other objectives to be the limitations are imposed on the optimization problem Genetic Algorithm (GA) performs the small-scale computation and large-scale computation as well. Performance of GA is robust in both small scale and large scale computations. The original GA is assumed with some modifications. In this paper, a GA based optimization in the stationary WSNs with the deployment of multiple sinks is proposed. It is assumed that the sensor nodes route the data towards the nearest sink through the multiple hops communication strategy. In our simulations results: routing is following the multiple hops to the sink by the optimized routing. Moreover, we've enhanced the Network lifespan. The proposed technique saved both the route distance through optimization and energy by routing the data through optimized neighbor sensor nodes.
Lifetime maximisation algorithm in Wireless Sensor Network
International Journal of Ad Hoc and Ubiquitous Computing, 2010
In a Wireless Sensor Network (WSN), nodes are battery powered and then they are energy constrained. Network lifetime is the most important characteristics of performance for these networks. In this paper, we propose routing protocols that take into account the battery residual energy in sensor nodes and the energy required for transmission along the path toward the sink, which allows the distribution of energy load among the whole network nodes. Simulation results show that the network lifetimes increases up to 50% for the first node die and up to 114% for the last node die over comparable schemes like MLER protocol.
Genetic Algorithm for Optimizing the Routing in the Wireless Sensor Network
International Journal of Computer Applications, 2013
Wireless sensor networks consist of large number of low cost sensor nodes. All the nodes in the network have a limited transmission range and their processing, storage capabilities and energy resources are limited. These sensor nodes collect the data from the particular area and transmit to the base station for the processing of sensed data. To perform routing in wireless sensor network with this limitation of low power, energy and storage capabilities is a major problem. Due to which the lifetime of the network decreases. To solve this problem of reduced lifetime of the network, an efficient algorithm is required to increase the lifetime of the network. In this paper the Genetic algorithm (GA) is purposed to enhance the lifetime of heterogeneous wireless sensor networks. The work is compared with the ETLE (Efficient Three Level Energy) in terms of the lifetime of the network.
Increasing the Life of Wireless Sensors Networks: Proposing a Novel Routing Method
Considering extensive applications of wireless sensors networks, many research studies have examined them in recent years and nearly all aspects in this regard have been investigated by the researchers. Since wireless sensors` nodes use their batteries to live, one important aspect in this regard is examining a method by which the energy consumption reduces so that network could live longer. Many different methods have been proposed, but the present study enjoys new routing method applying genetics algorithm and Steiner Tree to overcome previous routing shortcomings in nodes' energy as an important factor for data transformation. The simulation results revealed that the proposed method could increase the life of network to some acceptable degree.
Life time of Wireless device Networks (WSNs) has perpetually been a important issue and has received enlarged attention within the recent years. Typically wireless device nodes area unit equipped with low power batteries that area unit impossible to recharge. Wireless device networks ought to have enough energy to satisfy the specified necessities of applications. during this paper, we have a tendency to propose Energy economical Routing and Fault node Replacement (EERFNR) formula to extend the lifespan of wireless device network, cut back information loss and conjointly cut back device node replacement value. Transmission drawback and device node loading drawback is solved by adding many relay nodes and composition device node's routing mistreatment stratified Gradient Diffusion. The device node will save backup nodes to cut back the energy for re-looking the route once the device node routing is broken. Genetic formula can calculate the device nodes to exchange, apply the foremost on the market routing methods to replace the fewest device nodes.