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Sensor nodes in wireless sensor networks (WSNs) are capable of sensing the surrounding conditions and transferring data to other nodes in the network. These nodes have limited capacity of in-out data transmission period. So to improve the flow, it becomes necessary to route data efficiently. As the network is self-organized, several security threats are presented to WSNs. In this paper, secure and efficient routing protocol applying Maximum Flow Technique (MFT) is proposed. This technique involves security alongside malicious attacks as well as utilizes the bandwidth efficiently to improve the Quality of Service (QoS). The presented approach is validated by using Network simulator (NS2).
Turki Ali Alghamdi. Enhanced QoS routing protocol using maximum flow technique. Computers & Electrical Engineering 2020, 89, 106950 .
AMA StyleTurki Ali Alghamdi. Enhanced QoS routing protocol using maximum flow technique. Computers & Electrical Engineering. 2020; 89 ():106950.
Chicago/Turabian StyleTurki Ali Alghamdi. 2020. "Enhanced QoS routing protocol using maximum flow technique." Computers & Electrical Engineering 89, no. : 106950.
Clustering is considered to be the most significant method for resolving conflicts of data transmission and maximizing the life span of the network in Wireless Sensor Networks (WSNs). The sensor nodes are densely deployed to satisfy the coverage requirement; this causes some nodes to lazy mode. Some algorithms of cluster heads (CHs) selection were already proposed for sufficient energy management. However, it remains as a challenging task in WSN due to network scalability, protocol characteristics, and data transfer rate. This paper aims to propose a novel clustering model is proposed by this research work for cluster head selection (CHS) that considers four primary constraints: namely energy consumption, delay, distance, and security. In addition, for optimal selection of CH, a novel algorithm, which is the hybridization of the Dragon Fly (DA) algorithm and firefly algorithm, is proposed. The proposed hybrid algorithm is named as FireFly replaced Position Update in Dragonfly (FPU-DA). The performance of the proposed work is compared with conventional algorithms. Subsequently, a parametric analysis is performed by varying the weight factor of the proposed FPU-DA model to investigate its impact on the performance of the CHS problem. The proposed FPU-DA model at round 2000 shows 9%, better than KNN and SOM. Thus, the analysis results proved that the proposed model attains a better life span when compared to that of other conventional models.
Turki Ali Alghamdi. Parametric analysis on optimized energy-efficient protocol in wireless sensor network. Soft Computing 2020, 25, 4409 -4421.
AMA StyleTurki Ali Alghamdi. Parametric analysis on optimized energy-efficient protocol in wireless sensor network. Soft Computing. 2020; 25 (6):4409-4421.
Chicago/Turabian StyleTurki Ali Alghamdi. 2020. "Parametric analysis on optimized energy-efficient protocol in wireless sensor network." Soft Computing 25, no. 6: 4409-4421.
The quality of communication between any two users in multi-hop wireless sensor networks directly depends upon the path selection among the available paths between end-users. The issue of selecting the optimized path from source to a destination becomes the necessary criteria for effective communication between end-users. The art of work mainly focuses on the selection of the path which has the best available bandwidth however they do not consider other network parameters such as distance, energy, the intensity of traffic which plays a critical role in routing. In this paper, an algorithm is presented for the selection of optimized route from source to destination by considering different network parameters along with the bandwidth and rank is given to all the available routes from source to destinations per their weights. The paper is validated using network simulator.
Turki Ali Alghamdi. Route optimization to improve QoS in multi-hop wireless sensor networks. Wireless Networks 2020, 1 -7.
AMA StyleTurki Ali Alghamdi. Route optimization to improve QoS in multi-hop wireless sensor networks. Wireless Networks. 2020; ():1-7.
Chicago/Turabian StyleTurki Ali Alghamdi. 2020. "Route optimization to improve QoS in multi-hop wireless sensor networks." Wireless Networks , no. : 1-7.
Internet of Things enabled Underwater Wireless Sensor Networks (IoT-UWSNs) are quite useful in monitoring different tasks including: from instrument monitoring to the climate recording and from pollution control to the prediction of natural disasters. However, there are some challenges, which affect the performance of a network, i.e., void hole occurrence, high Energy Consumption (EC) and low Packet Delivery Ratio (PDR). Therefore, in this work, two energy efficient routing protocols are proposed to maximize the PDR by minimizing the ratio of void hole occurrence. Scalability analysis of the proposed routing protocols is also performed. Additionally, feasible regions are computed to check the optimality of the proposed protocol in terms of EC. Furthermore, proposed protocols are compared with benchmark routing protocols in counterparts. Simulation results clearly show that proposed routing protocols achieved 80-81% higher PDR than GEographic and opportunistic routing with Depth Adjustment based topology control for communication Recovery (GEDAR) and Transmission Adjustment Neighbornode Approaching Distinct Energy Efficient Mates (TA-NADEEM). Moreover, the ratio of void hole occurrence is minimized upto 30% approximately.
Muhammad Awais; Ishtiaq Ali; Turki Ali Alghamdi; Muhammad Ramzan; Muhammad Tahir; Mariam Akbar; Nadeem Javaid. Towards Void Hole Alleviation: Enhanced GEographic and Opportunistic Routing Protocols in Harsh Underwater WSNs. IEEE Access 2020, 8, 96592 -96605.
AMA StyleMuhammad Awais, Ishtiaq Ali, Turki Ali Alghamdi, Muhammad Ramzan, Muhammad Tahir, Mariam Akbar, Nadeem Javaid. Towards Void Hole Alleviation: Enhanced GEographic and Opportunistic Routing Protocols in Harsh Underwater WSNs. IEEE Access. 2020; 8 (99):96592-96605.
Chicago/Turabian StyleMuhammad Awais; Ishtiaq Ali; Turki Ali Alghamdi; Muhammad Ramzan; Muhammad Tahir; Mariam Akbar; Nadeem Javaid. 2020. "Towards Void Hole Alleviation: Enhanced GEographic and Opportunistic Routing Protocols in Harsh Underwater WSNs." IEEE Access 8, no. 99: 96592-96605.
Energy efficiency has become a primary issue in wireless sensor networks (WSN). The sensor networks are powered by battery and thus they turn out to be dead after a particular interval. Hence, enhancing the data dissipation in energy efficient manner remains to be more challenging for increasing the life span of sensor devices. It has been already proved that the clustering method could improve or enhance the life span of WSNs. In the clustering model, the selection of cluster head (CH) in each cluster regards as the capable method for energy efficient routing, which minimizes the transmission delay in WSN. However, the main problem dealt with the selection of optimal CH that makes the network service prompt. Till now, more research works have been processing on solving this issue by considering different constraints. Under this scenario, this paper attempts to develop a new clustering model with optimal cluster head selection by considering four major criteria like energy, delay, distance, and security. Further, for selecting the optimal CHs, this paper proposes a new hybrid algorithm that hybridizes the concept of dragon fly and firefly algorithm algorithms, termed fire fly replaced position update in dragonfly. Finally, the performance of the proposed work is carried out by comparing with other conventional models in terms of number of alive nodes, network energy, delay and risk probability.
Turki Ali Alghamdi. Energy efficient protocol in wireless sensor network: optimized cluster head selection model. Telecommunication Systems 2020, 74, 331 -345.
AMA StyleTurki Ali Alghamdi. Energy efficient protocol in wireless sensor network: optimized cluster head selection model. Telecommunication Systems. 2020; 74 (3):331-345.
Chicago/Turabian StyleTurki Ali Alghamdi. 2020. "Energy efficient protocol in wireless sensor network: optimized cluster head selection model." Telecommunication Systems 74, no. 3: 331-345.
Underwater wireless sensor network (UWSN) is established in water bodies such as oceans, seas and rivers to observe the activity of military, to perform rescue operations and to do mining activity of resources. The sensor nodes communicate through acoustic channels. These nodes have limited battery life (energy), narrow bandwidth and a channel is incurred with delays and noise posing security thrust. The art of work presented different routing protocols in this era to utilize energy and bandwidth efficiently with less delay and to provide the security against black hole attack. However, these methods do not show an appropriate enhancement in the security and to utilize the bandwidth efficiently due to mobile environment. As a result of which, the delay also increases. In this paper a secured and bandwidth utilization path is enhanced using Bellman Inora Hex Hamming technique (BIHH), which not only improves the performance of the routing but also saves the energy. The presented approach is validated with network simulator.
Turki Alghamdi. Underwater Wireless Sensor Network Route Optimization using BIHH Technique. International Journal of Advanced Computer Science and Applications 2020, 11, 1 .
AMA StyleTurki Alghamdi. Underwater Wireless Sensor Network Route Optimization using BIHH Technique. International Journal of Advanced Computer Science and Applications. 2020; 11 (6):1.
Chicago/Turabian StyleTurki Alghamdi. 2020. "Underwater Wireless Sensor Network Route Optimization using BIHH Technique." International Journal of Advanced Computer Science and Applications 11, no. 6: 1.
The Internet of Things (IoT) industry is growing very fast to transform factories, homes, farms and practically everything else to make them efficient and intelligent. IoT is applied in different resilient scenarios and applications. IoT faces lots of challenges due to lack of computational power, battery and storage resources. Fortunately, the rise of blockchain technology facilitates IoT in many security solutions. Using blockchain, communication between IoT and emerging computing technologies is made efficient. In this work, we propose a secure service provisioning scheme with a fair payment system for Lightweight Clients (LCs) based on blockchain. Furthermore, an incentive mechanism based on reputation is proposed. We use consortium blockchain with the Proof of Authority (PoA) consensus mechanism. Furthermore, we use Smart Contracts (SCs) to validate the services provided by the Service Providers (SPs) to the LCs, transfer cryptocurrency to the SPs and maintain the reputation of the SPs. Moreover, the Keccak256 hashing algorithm is used for converting the data of arbitrary size to the hash of fixed size. AES128 encryption technique is used to encrypt service codes before sending to the LCs. The simulation results show that the LCs receive validated services from the SPs at an affordable cost. The results also depict that the participation rate of SPs is increased because of the incentive mechanism.
Turki Ali Alghamdi; Ishtiaq Ali; Nadeem Javaid; Muhammad Shafiq. Secure Service Provisioning Scheme for Lightweight IoT Devices With a Fair Payment System and an Incentive Mechanism Based on Blockchain. IEEE Access 2019, 8, 1048 -1061.
AMA StyleTurki Ali Alghamdi, Ishtiaq Ali, Nadeem Javaid, Muhammad Shafiq. Secure Service Provisioning Scheme for Lightweight IoT Devices With a Fair Payment System and an Incentive Mechanism Based on Blockchain. IEEE Access. 2019; 8 (99):1048-1061.
Chicago/Turabian StyleTurki Ali Alghamdi; Ishtiaq Ali; Nadeem Javaid; Muhammad Shafiq. 2019. "Secure Service Provisioning Scheme for Lightweight IoT Devices With a Fair Payment System and an Incentive Mechanism Based on Blockchain." IEEE Access 8, no. 99: 1048-1061.
In the last couple of decades, numerous energy management strategies have been devised to mitigate the effects of greenhouse gas emission, hence introducing the concept of microgrids. In a microgrid, distributed energy generators are used. Microgrid enables a point which ameliorates in exchanging power with the main grid during different times of day. Based on the system constraints, in this work, we aim to efficiently minimize the operating cost of the microgrid and shave the power consumption peaks. For this purpose, we introduce an improved binary bat (iBBat) algorithm which helps to schedule the load demand of smart homes and energy generation from distributed generator of microgrid to the load demand and supply. The proposed energy management algorithm is applied to both grid-connected and islanded modes of the microgrid. The constraints imposed on the algorithm ensure that the load of electricity consumer does not escalate during peak hours. The simulation results are compared with BBat and binary flower pollination algorithm, which validate that the iBBat reflects substantial reduction in operating cost of microgrid. Moreover, results also show a phenomenal reduction in the peak-to-average ratio of load demand from main the main grid.
Samia Abid; Turki Alghamdi; Abdul Haseeb; Zahid Wadud; Abrar Ahmed; Nadeem Javaid. An Economical Energy Management Strategy for Viable Microgrid Modes. Electronics 2019, 8, 1442 .
AMA StyleSamia Abid, Turki Alghamdi, Abdul Haseeb, Zahid Wadud, Abrar Ahmed, Nadeem Javaid. An Economical Energy Management Strategy for Viable Microgrid Modes. Electronics. 2019; 8 (12):1442.
Chicago/Turabian StyleSamia Abid; Turki Alghamdi; Abdul Haseeb; Zahid Wadud; Abrar Ahmed; Nadeem Javaid. 2019. "An Economical Energy Management Strategy for Viable Microgrid Modes." Electronics 8, no. 12: 1442.
An increase in the world’s population results in high energy demand, which is mostly fulfilled by consuming fossil fuels (FFs). By nature, FFs are scarce, depleted, and non-eco-friendly. Renewable energy sources (RESs) photovoltaics (PVs) and wind turbines (WTs) are emerging alternatives to the FFs. The integration of an energy storage system with these sources provides promising and economical results to satisfy the user’s load in a stand-alone environment. Due to the intermittent nature of RESs, their optimal sizing is a vital challenge when considering cost and reliability parameters. In this paper, three meta-heuristic algorithms: teaching-learning based optimization (TLBO), enhanced differential evolution (EDE), and the salp swarm algorithm (SSA), along with two hybrid schemes (TLBO + EDE and TLBO + SSA) called enhanced evolutionary sizing algorithms (EESAs) are proposed for solving the unit sizing problem of hybrid RESs in a stand-alone environment. The objective of this work is to minimize the user’s total annual cost (TAC). The reliability is considered via the maximum allowable loss of power supply probability ( L P S P m a x ) concept. The simulation results reveal that EESAs provide better results in terms of TAC minimization as compared to other algorithms at four L P S P m a x values of 0%, 0.5%, 1%, and 3%, respectively, for a PV-WT-battery hybrid system. Further, the PV-WT-battery hybrid system is found as the most economical scenario when it is compared to PV-battery and WT-battery systems.
Asif Khan; Turki Ali Alghamdi; Zahoor Ali Khan; Aisha Fatima; Samia Abid; Adia Khalid; Nadeem Javaid. Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System. Applied Sciences 2019, 9, 5197 .
AMA StyleAsif Khan, Turki Ali Alghamdi, Zahoor Ali Khan, Aisha Fatima, Samia Abid, Adia Khalid, Nadeem Javaid. Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System. Applied Sciences. 2019; 9 (23):5197.
Chicago/Turabian StyleAsif Khan; Turki Ali Alghamdi; Zahoor Ali Khan; Aisha Fatima; Samia Abid; Adia Khalid; Nadeem Javaid. 2019. "Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System." Applied Sciences 9, no. 23: 5197.
The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.
Aqib Jamil; Turki Ali Alghamdi; Zahoor Ali Khan; Sakeena Javaid; Abdul Haseeb; Zahid Wadud; Nadeem Javaid. An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory. Sustainability 2019, 11, 6287 .
AMA StyleAqib Jamil, Turki Ali Alghamdi, Zahoor Ali Khan, Sakeena Javaid, Abdul Haseeb, Zahid Wadud, Nadeem Javaid. An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory. Sustainability. 2019; 11 (22):6287.
Chicago/Turabian StyleAqib Jamil; Turki Ali Alghamdi; Zahoor Ali Khan; Sakeena Javaid; Abdul Haseeb; Zahid Wadud; Nadeem Javaid. 2019. "An Innovative Home Energy Management Model with Coordination among Appliances using Game Theory." Sustainability 11, no. 22: 6287.
Smart Grid (SG) plays vital role in modern electricity grid. The data is increasing with the drastic increase in number of users. An efficient technology is required to handle this dramatic growth of data. Cloud computing is then used to store the data and to provide numerous services to the consumers. There are various cloud Data Centers (DC), which deal with the requests coming from consumers. However, there is a chance of delay due to the large geographical area between cloud and consumer. So, a concept of fog computing is presented to minimize the delay and to maximize the efficiency. However, the issue of load balancing is raising; as the number of consumers and services provided by fog grow. So, an enhanced mechanism is required to balance the load of fog. In this paper, a three-layered architecture comprising of cloud, fog and consumer layers is proposed. A meta-heuristic algorithm: Improved Particle Swarm Optimization with Levy Walk (IPSOLW) is proposed to balance the load of fog. Consumers send request to the fog servers, which then provide services. Further, cloud is deployed to save the records of all consumers and to provide the services to the consumers, if fog layer is failed. The proposed algorithm is then compared with existing algorithms: genetic algorithm, particle swarm optimization, binary PSO, cuckoo with levy walk and BAT. Further, service broker policies are used for efficient selection of DC. The service broker policies used in this paper are: closest data center, optimize response time, reconfigure dynamically with load and new advance service broker policy. Moreover, response time and processing time are minimized. The IPSOLW has outperformed to its counterpart algorithms with almost 4.89% better results.
Zahoor Ali Khan; Ayesha Anjum Butt; Turki Ali Alghamdi; Aisha Fatima; Mariam Akbar; Muhammad Ramzan; Nadeem Javaid. Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms. IEEE Access 2019, 7, 157254 -157267.
AMA StyleZahoor Ali Khan, Ayesha Anjum Butt, Turki Ali Alghamdi, Aisha Fatima, Mariam Akbar, Muhammad Ramzan, Nadeem Javaid. Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms. IEEE Access. 2019; 7 (99):157254-157267.
Chicago/Turabian StyleZahoor Ali Khan; Ayesha Anjum Butt; Turki Ali Alghamdi; Aisha Fatima; Mariam Akbar; Muhammad Ramzan; Nadeem Javaid. 2019. "Energy Management in Smart Sectors Using Fog Based Environment and Meta-Heuristic Algorithms." IEEE Access 7, no. 99: 157254-157267.
Recently, power systems are facing the challenges of growing power demand, depleting fossil fuel and aggravating environmental pollution (caused by carbon emission from fossil fuel based power generation). The incorporation of alternative low carbon energy generation, i.e., Renewable Energy Sources (RESs), becomes crucial for energy systems. Effective Demand Side Management (DSM) and RES incorporation enable power systems to maintain demand, supply balance and optimize energy in an environmentally friendly manner. The wind power is a popular energy source because of its environmental and economical benefits. However, the uncertainty of wind power makes its incorporation in energy systems really difficult. To mitigate the risk of demand-supply imbalance, an accurate estimation of wind power is essential. Recognizing this challenging task, an efficient deep learning based prediction model is proposed for wind power forecasting. The proposed model has two stages. In the first stage, Wavelet Packet Transform (WPT) is used to decompose the past wind power signals. Other than decomposed signals and lagged wind power, multiple exogenous inputs (such as, calendar variable and Numerical Weather Prediction (NWP)) are also used as input to forecast wind power. In the second stage, a new prediction model, Efficient Deep Convolution Neural Network (EDCNN), is employed to forecast wind power. A DSM scheme is formulated based on forecasted wind power, day-ahead demand and price. The proposed forecasting model’s performance was evaluated on big data of Maine wind farm ISO NE, USA.
Sana Mujeeb; Turki Ali Alghamdi; Sameeh Ullah; Aisha Fatima; Nadeem Javaid; Tanzila Saba. Exploiting Deep Learning for Wind Power Forecasting Based on Big Data Analytics. Applied Sciences 2019, 9, 4417 .
AMA StyleSana Mujeeb, Turki Ali Alghamdi, Sameeh Ullah, Aisha Fatima, Nadeem Javaid, Tanzila Saba. Exploiting Deep Learning for Wind Power Forecasting Based on Big Data Analytics. Applied Sciences. 2019; 9 (20):4417.
Chicago/Turabian StyleSana Mujeeb; Turki Ali Alghamdi; Sameeh Ullah; Aisha Fatima; Nadeem Javaid; Tanzila Saba. 2019. "Exploiting Deep Learning for Wind Power Forecasting Based on Big Data Analytics." Applied Sciences 9, no. 20: 4417.
Zahoor Ali Khan; Muhammad Awais; Turki Ali Alghamdi; Adia Khalid; Aisha Fatima; Mariam Akbar; Nadeem Javaid. Region Aware Proactive Routing Approaches Exploiting Energy Efficient Paths for Void Hole Avoidance in Underwater WSNs. IEEE Access 2019, 7, 140703 -140722.
AMA StyleZahoor Ali Khan, Muhammad Awais, Turki Ali Alghamdi, Adia Khalid, Aisha Fatima, Mariam Akbar, Nadeem Javaid. Region Aware Proactive Routing Approaches Exploiting Energy Efficient Paths for Void Hole Avoidance in Underwater WSNs. IEEE Access. 2019; 7 ():140703-140722.
Chicago/Turabian StyleZahoor Ali Khan; Muhammad Awais; Turki Ali Alghamdi; Adia Khalid; Aisha Fatima; Mariam Akbar; Nadeem Javaid. 2019. "Region Aware Proactive Routing Approaches Exploiting Energy Efficient Paths for Void Hole Avoidance in Underwater WSNs." IEEE Access 7, no. : 140703-140722.
Wireless sensor networks (WSNs) consist of autonomous sensor nodes, which can predict the ambiance and act accordingly to transfer the data in adverse conditions. However, limited energy and security issues restrict the efficient communication in such networks. Art of the work presented energy-based approaches using cluster heads and security is provided using encryption. However, cluster head methodologies result in congestion, and security using encryption is difficult due to the self-organized structure. So, it degrades the performance of the network. In this paper, secure and energy-efficient method of optimization is being proposed using the Dij-Huff Method. The presented approach is validated by a network simulator.
Turki A. Alghamdi. Secure and Energy Efficient Path Optimization Technique in Wireless Sensor Networks Using DH Method. IEEE Access 2018, 6, 53576 -53582.
AMA StyleTurki A. Alghamdi. Secure and Energy Efficient Path Optimization Technique in Wireless Sensor Networks Using DH Method. IEEE Access. 2018; 6 ():53576-53582.
Chicago/Turabian StyleTurki A. Alghamdi. 2018. "Secure and Energy Efficient Path Optimization Technique in Wireless Sensor Networks Using DH Method." IEEE Access 6, no. : 53576-53582.
Reem Alshalawi; Turki Alghamdi. Forensic tool for wireless surveillance camera. 2017 19th International Conference on Advanced Communication Technology (ICACT) 2017, 536 -540.
AMA StyleReem Alshalawi, Turki Alghamdi. Forensic tool for wireless surveillance camera. 2017 19th International Conference on Advanced Communication Technology (ICACT). 2017; ():536-540.
Chicago/Turabian StyleReem Alshalawi; Turki Alghamdi. 2017. "Forensic tool for wireless surveillance camera." 2017 19th International Conference on Advanced Communication Technology (ICACT) , no. : 536-540.
This paper presents cooperative routing scheme to improve data reliability. The proposed protocol achieves its objective, however, at the cost of surplus energy consumption. Thus sink mobility is introduced to minimize the energy consumption cost of nodes as it directly collects data from the network nodes at minimized communication distance. We also present delay and energy optimized versions of our proposed RE-AEDG to further enhance its performance. Simulation results prove the effectiveness of our proposed RE-AEDG in terms of the selected performance matrics.
Tayyaba Liaqat; Mariam Akbar; Nadeem Javaid; Umar Qasim; Zahoor Ali Khan; Qaisar Javaid; Turki Ali Alghamdi; Iftikhar Azim Niaz. On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks. Sensors 2016, 16, 1391 .
AMA StyleTayyaba Liaqat, Mariam Akbar, Nadeem Javaid, Umar Qasim, Zahoor Ali Khan, Qaisar Javaid, Turki Ali Alghamdi, Iftikhar Azim Niaz. On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks. Sensors. 2016; 16 (9):1391.
Chicago/Turabian StyleTayyaba Liaqat; Mariam Akbar; Nadeem Javaid; Umar Qasim; Zahoor Ali Khan; Qaisar Javaid; Turki Ali Alghamdi; Iftikhar Azim Niaz. 2016. "On Reliable and Efficient Data Gathering Based Routing in Underwater Wireless Sensor Networks." Sensors 16, no. 9: 1391.
Background: Presently much attention is being paid to biometrics in the user authentication system, because multimodal is considered an accurate method to achieve higher degree of accuracy. Multimodal systems always give enhanced performance compared to unimodal. Methodology: The present study evaluated the performance of multimodal system by applying fusing face and palm print biometrics. Different levels of fusion schemes with optimal strategies were employed and the performance was evaluated over the all levels. Results: Overall, the best results of multimodal were obtained at the score level fusion by applying AND rule as 91 at 0.01% FAR, 94.5 at 0.1% FAR and 97.5 at 1.0% FAR. Whereas the best results of unimodal system were 42 at 0.01% FAR, 68 at 0.1% FAR and 84.75 at 1.0% FAR obtained with palmprint. The study showed that by fusing multimodal biometrics, a higher level of verification can be achieved. Conclusion: From the experimental results, it can be found that score level fusion with sum rules is reliable and feasible method for fusion of face and palmprint.
Turki Alghamdi. Evaluation of Multimodal Biometrics at Different Levels of Face and Palm Print Fusion Schemes. Asian Journal of Applied Sciences 2016, 9, 126 -130.
AMA StyleTurki Alghamdi. Evaluation of Multimodal Biometrics at Different Levels of Face and Palm Print Fusion Schemes. Asian Journal of Applied Sciences. 2016; 9 (3):126-130.
Chicago/Turabian StyleTurki Alghamdi. 2016. "Evaluation of Multimodal Biometrics at Different Levels of Face and Palm Print Fusion Schemes." Asian Journal of Applied Sciences 9, no. 3: 126-130.
Turki Alghamdi. Cluster Based Energy Efficient Routing Protocol for Wireless Body Area Network. Trends in Applied Sciences Research 2016, 11, 12 -18.
AMA StyleTurki Alghamdi. Cluster Based Energy Efficient Routing Protocol for Wireless Body Area Network. Trends in Applied Sciences Research. 2016; 11 (1):12-18.
Chicago/Turabian StyleTurki Alghamdi. 2016. "Cluster Based Energy Efficient Routing Protocol for Wireless Body Area Network." Trends in Applied Sciences Research 11, no. 1: 12-18.
We propose two routing protocols for Terrestrial Wireless Sensor Networks (TWSNs): Hybrid Energy Efficient Reactive (HEER) and Multihop Hybrid Energy Efficient Reactive (MHEER) routing protocol. The main purpose of designing these protocols is to improve the network lifetime and particularly the stability period of the underlying network. In MHEER, the node with the maximum energy in a region becomes cluster head (CH) of that region for that particular round (or cycle) of time and the number of the CHs in each round remains the same. Our techniques outperform the well-known existing routing protocols: LEACH, TEEN, and DEEC in terms of stability period and network lifetime. We also calculate the confidence interval of all our results which helps us to visualize the possible deviation of our graphs from the mean value. We also implement sink mobility on HEER and MHEER. We refer to them as HEER-SM and MHEER-SM. Simulation results show that HEER-SM and MHEER-SM yield better network lifetime and stability region as compared to the counterpart techniques. We have also carried out simulations with 500 and 1000 nodes in the same field dimensions besides 100 nodes. Simulations prove that the proposed schemes show the same behavior with 500 and 1000 nodes; that is, HEER and MHEER are scalable as well.1. IntroductionA Wireless Sensor Network (WSN) consists of a number of tiny wireless sensors dispersed throughout the network area. These sensors are very small in size and their basic function is to monitor any particular environment. A WSN can be used for security purposes, medical applications, environmental monitoring, and so forth. These sensor nodes monitor their environment and send the desired data to the base station (BS) via some routing protocol. As long as a sensor does not run out of power, it keeps sending its data to the BS. But a sensor cannot be recharged from time to time. Whenever its energy is completely consumed, it is no longer able to sense and send its data. So it is very important to implement an efficient routing protocol to improve the network lifetime and particularly its stability period. The network lifetime is the time period when a network starts working until the last node dies. On the other hand stability period is defined as time period from the start of a network till the death of very first node in the network. Very less energy is consumed in sensing data or aggregating it as compared to the energy consumed in transmission or reception of data. So a routing protocol plays a vital role in improving lifetime of a WSN.Many protocols use clustering as their routing scheme [1–7] as this technique is very effective for data transmission in WSNs. In this technique, the member nodes of a cluster select a CH among themselves for a particular round. All the cluster members send data to their respective CH. The CH receives that data, aggregates it, and then sends it to the BS. Aggregation gets rid of redundant data and only useful data is sent to base station which saves energy. Clustering can be done in two types of networks, that is, homogeneous and heterogeneous. In homogeneous WSNs, all nodes have the same energy level, whereas networks with different node energy levels are termed as heterogeneous networks. Multihoping between CHs is also a technique used for the extension of lifetime of large scale networks [8].Protocols can be classified as proactive and reactive. When the nodes periodically send their data to the BS, these are referred to as proactive. These protocols send information of relevant parameters after a fixed period of time. These types of networks are usually used for applications requiring periodic data monitoring. When the nodes react immediately to sudden and drastic changes in the value of the interested parameter then the protocols are said to be reactive. In reactive protocols, node does not have to wait for a fixed period of time to sense and transmit the data. Its sensors switch on their transmitters whenever there is a drastic change in the value of interested parameter. These protocols are suited for time critical applications.Our proposed protocol is a reactive one for homogeneous networks which uses initial energy and residual energy of a node for selecting a CH. After the selection of a CH, it will broadcast two threshold values. The transmission occurs if and only if the Current Value reaches the threshold value. This technique reduces the number of transmissions and prolongs the network lifetime and stability period.Clustering may be static or dynamic. In static clustering, the clusters do not change their size, whereas in dynamic clustering, depending upon the network characteristics, the clusters change their size during their lifetime period.Our scheme is based on static clustering. Whole area is divided into 10 regions. Each of these 10 regions acts as a cluster. Nodes are randomly deployed in each region and only a single node can become a CH in each region for a particular round. BS is located at the centre of the whole network area. Nodes send their data to the CH of their region via direct communication. The data from the CH to the BS is communicated through direct communication or multihoping depending upon its location. The CHs close to the BS send their data to the BS by using direct communication, whereas nodes which are farther from the BS send their data using Multihop Transmission between them and the CHs which are closer to the BS. The results suggest that it further enhances the network lifetime and stability period.Since communication distance has a significant impact on the energy consumption cost of nodes, we also implement sink mobility in our protocols to reduce the communication distance. In other words, networks with mobile sink remain alive for a longer period of time as compared to networks without sink mobility. In sink mobility, the sink moves in different locations of the network to collect the data. In our protocols, sink does not collect the data during its motion. It only collects data when it is at its sink locations in the network. It stops at its sink locations and collects the data from the nodes. These sink locations are also referred to as sojourn locations. The results depict that HEER-SM and MHEER-SM yield better network lifetime and stability region as compared to HEER and MHEER, respectively. It is worth mentioning here that this work is extended form of the work in [9].2. Related WorkMany researchers have reviewed and analyzed the performance of different protocols in WSNs [10, 11]. LEACH [1] is the first hierarchical clustering algorithm for WSNs. It is based on the dynamic clustering technique. After certain time period, nodes are organized into clusters and each CH is selected on the basis of probability. Due to cluster formation, the distance between CH and member nodes is reduced. Nodes transmit their data at minimum communication distance to minimize the energy consumption cost. This increases the network lifetime as well as throughput of the network. LEACH outperforms classical clustering algorithm by using adaptive clustering and rotating CHs. This saves energy as transmission will only be performed on that specific CH rather than all the nodes.Threshold Sensitive Energy Efficient Network (TEEN) [2] was proposed by Manjeshwar and Agrawal in 2000. It is a reactive protocol for time critical applications. Its CH selection and cluster formation of nodes are the same as those of LEACH. In this scheme, CH broadcasts two threshold values, that is, Hard Threshold (HT) and Soft Threshold (ST). HT is the absolute value of an attribute to trigger a sensor node. HT allows nodes to transmit the event, if the event occurs in the range of interest. Therefore, this not only reduces the number of transmissions but also increases network lifetime. TEEN is designed for time critical application; nodes only transmit data when it is needed according to HT. In the remaining time they switch off the transmitter and get active when HT arrives. The disadvantage of this scheme is that the network could not get operational until HT arrives. If network does not observe HT, user will not receive ant data from the network and even no information whether any node is alive.Smaragdakis et al. [3] proposed a two-level heterogeneous aware protocol, consisting of normal and advanced (high energy) nodes. It is based on the weighted election probabilities of each node according to their respective energy to become a CH. Intuitively, advanced nodes have more probability to become a CH than normal nodes, which seems logical according to their energy consumption. Stable Election Protocol (SEP) does not require any global knowledge of the network. The drawback of SEP is that it does not consider the changing residual energy of the node; hence, the probability of advanced nodes to become CH remains high irrespective of the residual energy left in the node. Moreover, SEP performs below par if the network is more than two levels.In 2006, Qing et al. [4] proposed Distributed Energy Efficient Clustering (DEEC) protocol for WSNs. This scheme minimizes the energy consumption of the nodes by considering average energy of the network and uses it as a reference energy. Due to this approach global knowledge of energy is not required. DEEC is a clustering protocol for two and multilevel heterogeneous networks. In DEEC the probability for a node to become CH is based on residual energy of the node and average energy of network. The epoch for nodes to become CH is set according to the residual energy of a node and average energy of the network. The node with higher initial and residual energy has more chances to become a CH than the low residual energy node. DEEC performs well in multilevel heterogeneous WSN as compared to LEACH and SEP.Efficient Scheduling for the Mobile Sink in Wireless Sensor Networks with Delay Constraint (ESWC) is proposed by Gu et al. in [12].
Mariam Akbar; Nadeem Javaid; Zahoor Ali Khan; Umar Qasim; Turki Alghamdi; Saad Noor Mohammad; Syed Hassan Ahmed; Majid Iqbal Khan; Safdar Hussain Bouk. Towards Network Lifetime Maximization: Sink Mobility Aware Multihop Scalable Hybrid Energy Efficient Protocols for Terrestrial WSNs. International Journal of Distributed Sensor Networks 2015, 2015, 1 -16.
AMA StyleMariam Akbar, Nadeem Javaid, Zahoor Ali Khan, Umar Qasim, Turki Alghamdi, Saad Noor Mohammad, Syed Hassan Ahmed, Majid Iqbal Khan, Safdar Hussain Bouk. Towards Network Lifetime Maximization: Sink Mobility Aware Multihop Scalable Hybrid Energy Efficient Protocols for Terrestrial WSNs. International Journal of Distributed Sensor Networks. 2015; 2015 ():1-16.
Chicago/Turabian StyleMariam Akbar; Nadeem Javaid; Zahoor Ali Khan; Umar Qasim; Turki Alghamdi; Saad Noor Mohammad; Syed Hassan Ahmed; Majid Iqbal Khan; Safdar Hussain Bouk. 2015. "Towards Network Lifetime Maximization: Sink Mobility Aware Multihop Scalable Hybrid Energy Efficient Protocols for Terrestrial WSNs." International Journal of Distributed Sensor Networks 2015, no. : 1-16.
To keep information recent between two nodes, two types of link sensing feed-back mechanisms are used: link layer (LL) and network layer (NL). In this paper, we model and evaluate these link sensing mechanisms in three widely used reactive routing protocols: ad hoc on-demand distance vector (AODV), dynamic source routing (DSR), and dynamic MANET on-demand (DYMO). Total cost paid by a routing protocol is the sum of cost paid in the form of energy consumed (in terms of packet reception/transmission) and time spent (in terms of processing route information). Routing operations are divided into two phases: route discovery (RD) and route maintenance (RM). These protocols majorly focus on broadcast cost optimization performed by expanding ring search (ERS) algorithm to control blind flooding. Hence, our model relates link sensing mechanisms in RD and RM for the selected routing protocols to compute consumed energy and processing time. The proposed framework is evaluated via NS-2, where the selected protocols are tested with different nodes' mobilities and densities.
N. Javaid; Zahoor Khan; U. Qasim; Mohsin Jamil; M. Ishfaq; Turki Alghamdi. Modeling Routing Overhead of Reactive Protocols at Link Layer and Network Layer in Wireless Multihop Networks. Mathematical Problems in Engineering 2015, 2015, 1 -14.
AMA StyleN. Javaid, Zahoor Khan, U. Qasim, Mohsin Jamil, M. Ishfaq, Turki Alghamdi. Modeling Routing Overhead of Reactive Protocols at Link Layer and Network Layer in Wireless Multihop Networks. Mathematical Problems in Engineering. 2015; 2015 ():1-14.
Chicago/Turabian StyleN. Javaid; Zahoor Khan; U. Qasim; Mohsin Jamil; M. Ishfaq; Turki Alghamdi. 2015. "Modeling Routing Overhead of Reactive Protocols at Link Layer and Network Layer in Wireless Multihop Networks." Mathematical Problems in Engineering 2015, no. : 1-14.