List of Articles Lifetime

• Open Access Article
  • Abstract Page
  • Full-Text
  
  1 - Increasing the lifetime of underwater acoustic sensor networks by optimal relay node placement
  zahra mihamadi mohadeseh soleimanpour daryush avasimoghaddam Siamak Talebi
  Underwater acoustic sensor networks (UASNs) have gained growing importance due to their desirable features and wide spread practical applications in many communication fields. Due to the high cost of underwater sensor nodes as well as implementation complexity, increasi More

  Underwater acoustic sensor networks (UASNs) have gained growing importance due to their desirable features and wide spread practical applications in many communication fields. Due to the high cost of underwater sensor nodes as well as implementation complexity, increasing the lifetime of UASNs is an important issue. Although relay nodes have an important role in reducing the transmission distance and energy consumption. But the efficient RNP (Relay Node Placement) to avoid the critical sensor nodes' elimination is the main problem, i.e., to preserve the connected network. For this aim this paper presents an innovative solution called an Efficient Relay node Setting (ERS) algorithm, which involves formulating the Relay Node Placement (RNP) as a non-convex optimization problem. Actually, due to the Difference Convex (DC) constraints the proposed RNP problem is a non-convex problem and finding an optimal solution is complicated. However, a novel transformation can be applied to DC constraints which converts the problem into its convex programming equivalent. Application of the convex programming offers the advantage of readily computing a global optimal solution. Simulation results confirm the superiority of the proposed scheme over the competing RA method in terms of network lifetime and efficiency. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  2 - Data Aggregation Tree Structure in Wireless Sensor Networks Using Cuckoo Optimization Algorithm
  Elham Mohsenifard Behnam Talebi
  10.7508/jist.2016.03.006
  Wireless sensor networks (WSNs) consist of numerous tiny sensors which can be regarded as a robust tool for collecting and aggregating data in different data environments. The energy of these small sensors is supplied by a battery with limited power which cannot be rech More

  Wireless sensor networks (WSNs) consist of numerous tiny sensors which can be regarded as a robust tool for collecting and aggregating data in different data environments. The energy of these small sensors is supplied by a battery with limited power which cannot be recharged. Certain approaches are needed so that the power of the sensors can be efficiently and optimally utilized. One of the notable approaches for reducing energy consumption in WSNs is to decrease the number of packets to be transmitted in the network. Using data aggregation method, the mass of data which should be transmitted can be remarkably reduced. One of the related methods in this approach is the data aggregation tree. However, it should be noted that finding the optimization tree for data aggregation in networks with one working-station is an NP-Hard problem. In this paper, using cuckoo optimization algorithm (COA), a data aggregation tree was proposed which can optimize energy consumption in the network. The proposed method in this study was compared with genetic algorithm (GA), Power Efficient Data gathering and Aggregation Protocol- Power Aware (PEDAPPA) and energy efficient spanning tree (EESR). The results of simulations which were conducted in matlab indicated that the proposed method had better performance than GA, PEDAPPA and EESR algorithm in terms of energy consumption. Consequently, the proposed method was able to enhance network lifetime. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  3 - Lifetime Maximization by Dynamic Threshold and Sensor Selection in Multi-channel Cognitive Sensor Network
  Asma Bagheri Ataollah Ebrahimzadeh maryam najimi
  10.7508/jist.2017.20.003
  The tiny and low-cost sensors cannot simultaneously sense more than one channel since they do not have high-speed Analog-to-Digital-Convertors (ADCs) and high-power batteries. It is a critical problem when they are used for multi-channel sensing in cognitive sensor netw More

  The tiny and low-cost sensors cannot simultaneously sense more than one channel since they do not have high-speed Analog-to-Digital-Convertors (ADCs) and high-power batteries. It is a critical problem when they are used for multi-channel sensing in cognitive sensor networks (CSNs). One solution for this problem is that the sensors sense various channels at different sensing periods. Due to the energy limitation in these scenarios, the lifetime maximization will become an important issue. In this paper, maximizing the lifetime of a CSN is investigated by selecting both the cooperative sensors and their detector threshold, such that the desired detection performance constraints are satisfied. This is a NP-complete problem, and obtaining the optimum solution needs exhaustive search with exponential complexity order. Here we have proposed two convex-based optimization algorithms with low order of complexity. First algorithm applies the known instantaneous Signal-to-Noise-Ratio (SNR) and obtains the proper detector thresholds by solving an equation for every channel. Investigation the effect of detector thresholds on the energy consumption, the false alarm probability and the detection probability shows that we can minimize the detector thresholds such that the detection constraints are met. In the second algorithm in order to reduce the complexity of the problem it is proposed the Bisection method for determining detector thresholds. Because knowing the instantaneous SNR is difficult, we have investigated the performance of the second algorithm by average value of SNR. Simulation results show that the proposed algorithms improve the performance of the network in case of lifetime and energy consumption. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  4 - Lifetime Improvement Using Cluster Head Selection and Base Station Localization in Wireless Sensor Networks
  maryam najimi Sajjad  Nankhoshki
  10.7508/jist.2018.02.006
  The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, a sensor network of nodes with wireless transceiver capabilities and limited energy is considered. Clustering is one of the most eff More

  The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, a sensor network of nodes with wireless transceiver capabilities and limited energy is considered. Clustering is one of the most efficient techniques to save more energy in these networks. Therefore, the proper selection of the cluster heads plays important role to save the energy of sensor nodes for data transmission in the network. In this paper, we propose an energy efficient data transmission by determining the proper cluster heads in wireless sensor networks. We also obtain the optimal location of the base station according to the cluster heads to prolong the network lifetime. An efficient method is considered based on particle swarm algorithm (PSO) which is a nature inspired swarm intelligence based algorithm, modelled after observing the choreography of a flock of birds, to solve a sensor network optimization problem. In the proposed energy- efficient algorithm, cluster heads distance from the base station and their residual energy of the sensors nodes are important parameters for cluster head selection and base station localization. The simulation results show that our proposed algorithm improves the network lifetime and also more alive sensors are remained in the wireless network compared to the baseline algorithms in different situations. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  5 - A New Game Theory-Based Algorithm for Target Coverage in Directional Sensor Networks
  Elham Golrasan marzieh varposhti
  10.52547/jist.9.34.103
  One of the challenging problems in directional sensor networks is maximizing target coverage while minimizing the amount of energy consumption. Considering the high redundancy in dense directional sensor networks, it is possible to preserve energy and enhance coverage q More

  One of the challenging problems in directional sensor networks is maximizing target coverage while minimizing the amount of energy consumption. Considering the high redundancy in dense directional sensor networks, it is possible to preserve energy and enhance coverage quality by turning off redundant sensors and adjusting the direction of the active sensor nodes. In this paper, we address the problem of maximizing network lifetime with adjustable ranges (MNLAR) and propose a new game theory-based algorithm in which sensor nodes try to adjust their working direction and sensing range in a distributed manner to achieve the desired coverage. For this purpose, we formulate this problem as a multiplayer repeated game in which each sensor as a player tries to maximize its utility function which is designed to capture the tradeoff between target coverage and energy consumption. To achieve an efficient action profile, we present a distributed payoff-based learning algorithm. The performance of the proposed algorithm is evaluated via simulations and compared to some existing methods. The simulation results demonstrate the performance of the proposed algorithm and its superiority over previous approaches in terms of network lifetime. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  6 - A RPL-based Routing Algorithm for Multimedia Traffic for the Internet of Things
  Mohammad Khansari Farzaneh Mortazavi
  According to enormous growths in communication networks, multimedia data will play a significant role on the Internet of Things in the near future. High volume of multimedia data leads to challenges such as reducing network lifetime and congestion. In this paper, a new More

  According to enormous growths in communication networks, multimedia data will play a significant role on the Internet of Things in the near future. High volume of multimedia data leads to challenges such as reducing network lifetime and congestion. In this paper, a new objective function for the RPL routing protocol is proposed which addresses the characteristics of multimedia data in the routing process. In the objective function, node’s remaining energy and the remaining buffer capacity of nodes measures are combined using a weighted pair. In order to evaluate this method, input data is generated based on a video trace. Packet delivery ratio, network lifetime, nodes availability over the lifetime of the network, node energy distribution, and end-to-end delay are used to evaluate the proposed method. The evaluation results show that the proposed method increases the package delivery ratio compared to the standard RPL. This method also improves the lifetime of the nodes by distributing energy between the nodes in comparison with standard RPL and extends the node's availability over the lifetime of the network. Finally, it reduces the network congestion which led to a lower end-to-end delay. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  7 - Design of a CDS Backbone Based Wireless Mesh Network Energy Aware Routing Method for Maximizing Lifetime
  A. Shafaroudi S. V. Azhari
  In many applications, wireless mesh networks work by battery as a power source. In this scenario, routing method has a great impact on the network lifetime. In this research a new backbone based wireless mesh network routing method for maximizing lifetime has been prop More

  In many applications, wireless mesh networks work by battery as a power source. In this scenario, routing method has a great impact on the network lifetime. In this research a new backbone based wireless mesh network routing method for maximizing lifetime has been proposed. This approach is compatible with the features provided by IEEE standard for wireless mesh networks. In this method, backbone routers are selected based on the maximum remaining energy. The proposed algorithm is compared with optimum and shortest path routing methods. Simulation results show acceptable increase in network lifetime in the proposed approach. Manuscript profile
• Open Access Article
  • Abstract Page
  • Full-Text
  
  8 - Improving Target Coverage in Visual Sensor Networks by Adjusting the Cameras’ Field-of-View and Scheduling the Cover sets Using Simulated Annealing
  B. Shahrokhzadeh M. Dehghan M. R. Shahrokhzadeh
  In recent years, target coverage is one of the important problems in visual sensor networks. An efficient use of energy is required in order to increase the network lifetime, while covering all the targets. In this paper, we address the Maximum Lifetime with Coverage Sc More

  In recent years, target coverage is one of the important problems in visual sensor networks. An efficient use of energy is required in order to increase the network lifetime, while covering all the targets. In this paper, we address the Maximum Lifetime with Coverage Scheduling (MLCS) problem that maximizes the network lifetime. We develop a simulated annealing (SA) algorithm that divides the sensors’ Field-of-View (FoV) to a number of cover sets that can cover all the targets and then applies a sleep-wake scheduling algorithm. On the other hand, we have to identify the best possible FoV of sensors according to the targets’ location using rotating cameras, to reduce the solution space and find a near-optimal solution. It also provides the balanced distribution of energy consumption by introducing a new energy and neighbor generating function as well as escaping from local optima. Finally, we conduct some simulation experiments to evaluate the performance of our proposed method by comparing with well-known solutions in the literature such as greedy algorithms. Manuscript profile