International Journal of Sensors Wireless Communications and Control - Volume 10, Issue 1, 2020

Forest fire disasters have arisen each year due to a number of factors. The main interest of the authorities is to fight against these fires as early as possible with a minimum of damage, by exploiting recent technologies suitable for this field. In this paper, we present the design and the implementation of a forest fire detection system based on the Wireless Multimedia Sensor Networks (WMSN) technology applied to our region (M'sila forest, Oran city - Algeria) using a field experiment testbed with low cost hardware and software. In our previous study, the designed system detects the fire using a mono modal approach (the sensed data was scalar in nature such as the temperature and humidity). In this work, we enhanced this system by collecting, in addition, richer information sources using cameras as data sources (by capturing images) to eliminate the false alarms which present the main weakness of the first system. We call this new system as Multimedia Forest Fire System (M2FS). Field experiments that we have carried out using the testbed under different scenarios by evaluating the image compression, time constraint and energy consumption, allowed us to validate our chosen technology (Arduino mote) for any application (scalar or multimedia), and also revealed the supremacy of the multimodal approach to mitigate efficiently false alarms.

Background & Objective: In past few years, Cognitive Radio (CR) paradigm has emerged as a promising and revolutionary solution to avoid problems of spectrum paucity and inefficiency in spectrum usage. Efficiently utilization of the spectrum offers high network performance. CRs are proficient to identify and adopt the unused spectrum in order to allow secondary users to occupy it without interfering the primary user’s activity. Cognitive Internet on Things (CIoT) is an integration of several technologies and communication solutions which can be effectively realized as Cognitive Radio Adhoc Networks (CRAHN). In CRANH, on-demand routing protocols are the best suitable protocols due to their dynamic feature of available un-utilized channel/spectrum selection. Methods: Here, firstly, Ad-Hoc On-Demand Distance Vector (AODV) routing protocol has been modified and further evaluated to address route selection challenges in CIoT framework. Secondly, the effects on network performance under network layer routing attacks (i.e. blackhole attack, byzantine attack and flooding attacks) are evaluated. Conclusion: The simulations results demonstrate network performance increase with more channels and degrade differently under attacks.

Background: Nowadays, the use of wireless sensor networks is developing rapidly. these networks are applicable in many fields, including military, medical, and environment. these networks use hundreds or thousands of cheap sensor nodes with low power-low and low energy to perform large tasks. These networks have limitations that can lead to inefficiency or not cost - effective. Among these limitations, consumption of energy and issues related to the lifetime of the network. One of the solutions that can assist the load balancing between sensor nodes, increased scalability, improving energy consumption and consequently, increasing network lifetime, clustering of sensor nodes and placing a suitable cluster head in all clusters. Choosing the right cluster head, significantly reduces energy consumption in the network and increases network lifetime. Objective: The purpose of this paper is to increase network lifetime by using the efficient clustering algorithm, which is used in Meta-heuristic bee colony to select the cluster head. Simulation of this paper is performed by MATLB software and the proposed method is compared with LEACH and GACR approaches. Conclusion: The simulation findings in this study show that the intended study has remarkably increased the length of the network lifetime by LEACH and GACR algorithms. Due to the limitation of energy in the wireless sensor network such solutions and using Meta-heuristic algorithms can give rise a remarkable increasing in network lifetime.

Background: Deep Learning (DL) neural network methods have become a hotspot subject of research in the remote sensing field. Classification of aerial satellite images depends on spectral content, which is a challenging topic in remote sensing. Objective: With the aim to accomplish a high performance and accuracy of Egyptsat-1 satellite image classification, the use of the Convolutional Neural Network (CNN) is raised in this paper because CNN is considered a leading deep learning method. CNN is developed to classify aerial photographs into land cover classes such as urban, vegetation, desert, water bodies, soil, roads, etc. In our work, a comparison between MAXIMUM Likelihood (ML) which represents the traditional supervised classification methods and CNN method is conducted. Conclusion: This research finds that CNN outperforms ML by 9%. The convolutional neural network has better classification result, which reached 92.25% as its average accuracy. Also, the experiments showed that the convolutional neural network is the most satisfactory and effective classification method applied to classify Egyptsat-1 satellite images.

Background: In this work, Peak Average Power Ratio (PAPR) reduction is achieved in Filter Bank Multi-Carrier (FBMC) by using a Pretreated Partial Transmit Sequence (P-PTS) technique. High PAPR is seen as unitary of the major problems in FBMC. Aims: The proposed work present a double stage optimization technique termed P-PTS. Methods: In the first step, several overlying signals cooperative optimization method that the phase angle sequences of current signal is intended and improved according to preceding overlapped signals. An efficient PTS scheme for PAPR reduction is put through in the second form. Results: The suggested technique is carried out by changing the value of U and V to analyze the BER and PAPR performance of the system. It is likewise noted that increasing the value of V can significantly lessen the peak power. Conclusion: Simulation results reveal that the performance of the proposed P-PTS technique is better than conventional PAPR reduction techniques with simple computations and the design complication can be traded off further compliantly with PAPR diminution.

Background & Objective: In this paper, a modified pseudo domino configuration has been proposed to improve the leakage power consumption and Power Delay Product (PDP) of dynamic logic using Carbon Nanotube MOSFETs (CN-MOSFETs). The simulations for proposed and published domino circuits are verified by using Synopsys HSPICE simulator with 32nm CN-MOSFET technology which is provided by Stanford. Methods: The simulation results of the proposed technique are validated for improvement of wide fan-in domino OR gate as a benchmark circuit at 500 MHz clock frequency. Results: The proposed configuration is suitable for cascading of the high performance wide fan-in circuits without any charge sharing. Conclusion: The performance analysis of 8-input OR gate demonstrate that the proposed circuit provides lower static and dynamic power consumption up to 62 and 40% respectively, and PDP improvement is 60% as compared to standard domino circuit.

Background: Real Time Wireless Sensor Networks (RT-WSN) have hard real time packet delivery requirements. Due to resource constraints of sensors, these networks need to trade-off energy and latency. Objective: In this paper, a routing protocol for RT-WSN named “SPREAD” has been proposed. The underlying idea is to reserve laxity by assuming tighter packet deadline than actual. This reserved laxity is used when no deadline-meeting next hop is available. Methods: As a result, if due to repeated transmissions, energy of nodes on shortest path is drained out, then time is still left to route the packet dynamically through other path without missing the deadline. Result: Congestion scenarios have been addressed by dynamically assessing 1-hop delays and avoiding traffic on congested paths. Conclusion: Through extensive simulations in Network Simulator NS2, it has been observed that SPREAD algorithm not only significantly reduces miss ratio as compared to other similar protocols but also keeps energy consumption under control. It also shows more resilience towards high data rate and tight deadlines than existing popular protocols.

Background: The blackhole infection can affect the collaborative communication in mobile networks. It is man-in-middle attack that seizes and deflects the route and avoids packet-forwarding in the network. The occurrence of collaborative-blackhole reduces the trust and trustworthiness over the network. Objectives: A probabilistic and weighted analysis based protocol is proposed in this research for detection of cooperative blackhole nodes and generating the preventing route over the network. The aim of the work is to improve the communication reliability. Methods: In this paper, the communication behaviour is analyzed under associated and probabilistic measures using Data Routing Information (DRI) table to discover the blackhole attack. It applies a dual check based on participation and communication constraints to estimate the node criticality. The evaluation is performed by neighbours and neighbour-on-neighbour nodes with weights and threshold specific decisions. These measures are evaluated through composite and integrated measures and presented as decision metrics. The parametric and probabilistic checks are conducted as a comprehensive evaluation within the proposed PSAODV (Probabilistic Secure Adhoc On Demand Distance Vector) protocol. Results: The simulation of PSAODV protocol is conducted in NS2 environment on various scenarios with mobility, density and traffic type variations. The scenarios are defined with a higher density of blackhole nodes within the network. The adaptive weights are identified by simulating the network with different weight combinations. These weights are employed within the PSAODV protocol to configure it with the maximum benefits. The analytical evaluations are taken against AODV and SAODV protocols and identified the performance enhancement in terms of Packet Delivery Ratio (PDR) Ratio, delay, attack detection ratio parameters. Conclusion: A significant improvement in attack detection is achieved by this proposed PSAODV protocol. The proposed protocol improved the reliability and effectiveness of mobile network.

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.