Showing papers on "Wi-Fi array published in 2018"
TL;DR: A hybrid framework that combines the two technologies - cluster heads are equipped with solar panels to scavenge solar energy and the rest of nodes are powered by wireless charging is proposed and can reduce battery depletion by 20 percent and save vehicles’ moving cost by 25 percent compared to previous works.
Abstract: The application of wireless charging technology in traditional battery-powered wireless sensor networks (WSNs) grows rapidly recently. Although previous studies indicate that the technology can deliver energy reliably, it still faces regulatory mandate to provide high power density without incurring health risks. In particular, in clustered WSNs there exists a mismatch between the high energy demands from cluster heads and the relatively low energy supplies from wireless chargers. Fortunately, solar energy harvesting can provide high power density without health risks. However, its reliability is subject to weather dynamics. In this paper, we propose a hybrid framework that combines the two technologies - cluster heads are equipped with solar panels to scavenge solar energy and the rest of nodes are powered by wireless charging. We divide the network into three hierarchical levels. On the first level, we study a discrete placement problem of how to deploy solar-powered cluster heads that can minimize overall cost and propose a distributed $1.61(1+\epsilon)^2$ -approximation algorithm for the placement. Then, we extend the discrete problem into continuous space and develop an iterative algorithm based on the Weiszfeld algorithm. On the second level, we establish an energy balance in the network and explore how to maintain such balance for wireless-powered nodes when sunlight is unavailable. We also propose a distributed cluster head re-selection algorithm. On the third level, we first consider the tour planning problem by combining wireless charging with mobile data gathering in a joint tour. We then propose a polynomial-time scheduling algorithm to find appropriate hitting points on sensors’ transmission boundaries for data gathering. For wireless charging, we give the mobile chargers more flexibility by allowing partial recharge when energy demands are high. The problem turns out to be a Linear Program. By exploiting its particular structure, we propose an efficient algorithm that can achieve near-optimal solutions. Our extensive simulation results demonstrate that the hybrid framework can reduce battery depletion by 20 percent and save vehicles’ moving cost by 25 percent compared to previous works. By allowing partial recharge, battery depletion can be further reduced at a slightly increased cost. The results also suggest that we can reduce the number of high-cost mobile chargers by deploying more low-cost solar-powered sensors.
165 citations
TL;DR: This paper provides a survey on various techniques to address the challenges in wireless sensor networks and suggests ways to improve the quality of services.
Abstract: Internet of Things is a proposed germinates of internet in which everyday objects had network connectivity, allowing them to send and receive patient data. Wireless sensor network (WSN) refers a group of stereo metrically scattered and devoted sensors for observing and recording the physical conditions of ambience and formulate the collected data at central location. Though tremendous work has been done in the field of IOT concept wireless sensor network plays an important role in monitoring the patients and providing a medication. It is hindered from being beneficial to quality of services. This paper provides a survey on various techniques to address the challenges in wireless sensor networks.
69 citations
01 Jan 2018
TL;DR: A distributed shortest path data collection algorithm for connected target coverage to maximize WSN lifetime pertaining to both static and mobile multi-hop WSNs is proposed.
Abstract: Wireless sensor networks (WSNs) employ numerous sensor nodes possessing sensing, processing, and wireless communication abilities to monitor a specified sensing field. As sensor nodes are mostly battery operated and are highly constrained regarding energy resources, it is essential to explore energy optimization methods to prolong WSN lifetime. Target tracking is a very conventional WSN application that demands both useful and coherent energy management. This paper proposes a distributed shortest path data collection algorithm for connected target coverage to maximize WSN lifetime pertaining to both static and mobile multi-hop WSNs. The performance is evaluated in TinyOS employing the TOSSIM simulator based on the parameters like percentage of alive nodes, load distribution of nodes, and network lifetime.
68 citations
TL;DR: This paper considers the finite-time chaos synchronization of Chua chaotic oscillators based on the secure communication scheme in wireless sensor networks and proposes a sliding mode controller applied to the wireless sensor network to increase the robustness of the controller.
Abstract: This paper considers the finite-time chaos synchronization of Chua chaotic oscillators based on the secure communication scheme in wireless sensor networks. The modified Chua oscillators are added to the base station and sensor nodes to generate the chaotic signals. Two methods are proposed for the finite-time synchronization of the modified Chua systems with uncertain parameters. In the first method, by using the Lyapunov stability theory, control law is suggested to achieve finite-time chaos synchronization. In order to increase the robustness of the controller, in the second method, a sliding mode controller is applied to the wireless sensor network. Synchronization between the base station and each of the sensor nodes is realized by multiplying a selection matrix by the specified chaotic signal, which is broadcasted by the base station to the sensor nodes. The mathematical proofs confirm that the proposed control law is correct and finally, the simulation results are presented to show the efficiency o...
59 citations
TL;DR: OrthoNoC is presented, a wired-wireless architecture that differs from existing proposals in that both network planes are decoupled and driven by traffic steering policies enforced at the network interfaces, proving that the value of Ortho noC goes beyond simply improving the performance of the on-chip interconnect.
Abstract: On-chip communication remains as a key research issue at the gates of the manycore era. In response to this, novel interconnect technologies have opened the door to new Network-on-Chip (NoC) solutions towards greater scalability and architectural flexibility. Particularly, wireless on-chip communication has garnered considerable attention due to its inherent broadcast capabilities, low latency, and system-level simplicity. This work presents OrthoNoC , a wired-wireless architecture that differs from existing proposals in that both network planes are decoupled and driven by traffic steering policies enforced at the network interfaces. With these and other design decisions, OrthoNoC seeks to emphasize the ordered broadcast advantage offered by the wireless technology. The performance and cost of OrthoNoC are first explored using synthetic traffic, showing substantial improvements with respect to other wired-wireless designs with a similar number of antennas. Then, the applicability of OrthoNoC in the multiprocessor scenario is demonstrated through the evaluation of a simple architecture that implements fast synchronization via ordered broadcast transmissions. Simulations reveal significant execution time speedups and communication energy savings for 64-threaded benchmarks, proving that the value of OrthoNoC goes beyond simply improving the performance of the on-chip interconnect.
53 citations
TL;DR: Large-scale simulation results demonstrate that PRD performs better than the widely used ETX metric as well as other two metrics devised recently in terms of energy consumption and end-to-end delay, while guaranteeing packet delivery ratio.
Abstract: This paper investigates the problem of energy consumption in wireless sensor networks. Wireless sensor nodes deployed in harsh environment where the conditions change drastically suffer from sudden changes in link quality and node status. The end-to-end delay of each sensor node varies due to the variation of link quality and node status. On the other hand, the sensor nodes are supplied with limited energy and it is a great concern to extend the network lifetime. To cope with those problems, this paper proposes a novel and simple routing metric, predicted remaining deliveries (PRD), combining parameters, including the residual energy, link quality, end-to-end delay, and distance together to achieve better network performance. PRD assigns weights to individual links as well as end-to-end delay, so as to reflect the node status in the long run of the network. Large-scale simulation results demonstrate that PRD performs better than the widely used ETX metric as well as other two metrics devised recently in terms of energy consumption and end-to-end delay, while guaranteeing packet delivery ratio.
50 citations
01 Jan 2018
48 citations
TL;DR: In this paper, the security issues of 5G wireless communication networks have been emphasized upon, with the game theoretic analysis of bandwidth spoofing attack on the multistage 5Gs wireless communication network.
Abstract: All over the world, there is a gigantic stir in the number of subscribers which gave rise to numerous challenges, like interference management and capacity enhancement. The enabling candidates to deal with this plight are the enabling technologies of the 5G wireless communication networks. Though the 5G technologies meet the mounting demands, yet, security remains a vital concern. In this paper, the security issues of 5G wireless communication networks have been emphasized upon, with the game theoretic analysis of bandwidth spoofing attack on the multistage 5G wireless communication network. The intrusion on the relay, small cell access point and base station, which are forming a multistage 5G wireless communication network, is detected using a proposed Adaptive Intrusion Detection System.
46 citations
TL;DR: The design and validation aspects of the optical layer of a bidirectional UOWC system developed in the framework of the European Project SUNRISE, able to provide wireless connectivity compliant to 10Base-T Ethernet protocol (Manchester-coded signal with 10 Mb/s data rate), are presented.
Abstract: Marine researchers and operators during their daily work need consistent data from the underwater environment to constantly monitor the habitat’s probes and the robots condition. For underwater applications, wireless communication is of paramount importance. Today, the needs for high-speed communication has prompted the exploration of the Underwater Optical Wireless Communications (UOWCs) method. This paper presents the design and validation aspects of the optical layer of a bidirectional UOWC system developed in the framework of the European Project SUNRISE, able to provide wireless connectivity compliant to 10Base-T Ethernet protocol (Manchester-coded signal with 10 Mb/s data rate). The designed modems are made of two similar optical transceivers, each including a transmitter, a receiver unit, and an optical power monitor part. The transmitter is based on an array of blue Light Emitting Diodes; the receiver exploits a commercially available Avalanche Photodiode (APD) and the monitoring relies on a pin-photodiode. The modems, after a deep characterization in controlled environments, were proved to work with the required 10Base-T Ethernet, up to 7.5 m distance in shallow harbor waters. The complete optical system is intended to become a node of the SUNRISE infrastructure.
41 citations
TL;DR: Simulations results show that the proposed algorithms can achieve superior network throughput performance over existing schemes.
Abstract: The medium access probability (MAP) of a random access protocol can severely impact network throughput especially for delay-sensitive applications, since it determines whether a node should transmit packets in a given slot or not. This paper focuses on network throughput maximization through optimizing the MAPs of all users under delay quality-of-service constraints in wireless interference-limited networks. Specifically, first, the total delay for transmitting one packet for a user is analyzed and derived based on an M/G/1 model. Then, the stochastic property of the aggregated interference is analyzed and its distribution is modeled as a log-normal distribution. Based on the delay and interference models, an optimization problem is formulated to derive the optimal MAPs so that the network throughput is maximized under the delay constraints. Two network traffic scenarios, homogeneous and heterogeneous user traffic, are discussed, respectively. For the case of homogeneous traffic, a closed-form expression of the optimal MAP is derived; for the case of heterogeneous traffic, a global $\epsilon $ -optimal algorithm based on the branch-and-bound framework and convex relaxation technology is proposed with relatively low complexity. Simulations results show that the proposed algorithms can achieve superior network throughput performance over existing schemes.
TL;DR: This paper establishes a theoretical framework for the study of eavesdropper-tolerance capability in a two-hop wireless network, where the cooperative jamming is adopted to ensure security defined by secrecy outage probability (SOP) and opportunistic relaying is adoption to guarantee reliability defined by transmission outage probabilities (TOP).
Abstract: Service Oriented Computing (SOC) has initially developed for the Internet, but also identified as an appealing computing paradigm for developing applications in distributed wireless environments. The open nature of wireless medium may expose services to a variety of unauthorized third parties (eavesdroppers), resulting in insecure service interactions, while cooperative jamming is promising to provide a strong form of security. This paper focuses on security performance study of wireless communications for service interactions among different parties in SOC. More specifically, this paper establishes a theoretical framework for the study of eavesdropper-tolerance capability (i.e., the maximum number of eavesdroppers that can be tolerated) in a two-hop wireless network, where the cooperative jamming is adopted to ensure security defined by secrecy outage probability (SOP) and opportunistic relaying is adopted to guarantee reliability defined by transmission outage probability (TOP). For the concerned network, exact modeling for SOP and fine approximation for TOP are first conducted based on the Central Limit Theorem. With the help of SOP and TOP models and also the Stochastic Ordering Theory, the model for eavesdropper-tolerance capability analysis is then developed. Finally, extensive simulation and numerical results are provided to illustrate the efficiency of our theoretical framework as well as the eavesdropper-tolerance capability of the concerned network from adopting cooperative jamming and opportunistic relaying.
Proceedings Article•
21 Sep 2018TL;DR: Initial experimental results in a wireless network scenario show that the Mockets middleware achieves better performance levels than traditional TCP-based infrastructure.
Abstract: Wireless networking is becoming increasingly important for ubiquitous access to the Internet and the Web. However, wireless networks exhibit significant reliability and performance problems, with frequent disconnections, congestions, and packet losses. For these reasons, the traditional TCP/IP suite, designed for wired networks, offers poor performance and inadequate communication semantics in this scenario. There are several research efforts in both protocols and communication infrastructures aimed at producing solutions better suited to wireless network characteristics. This paper presents Mockets, a novel communications middleware specifically designed for wireless networking scenarios. The Mockets middleware permits a communication endpoint to be moved from one node to another without interrupting the communication session. In addition, Mockets provides several delivery services with different communication semantics, semantic classification of data, cancellation/replacement of enqueued data, and priority/lifetime assignment to messages. Initial experimental results in a wireless network scenario show that the Mockets middleware achieves better performance levels than traditional TCP-based infrastructure.
01 Jan 2018
TL;DR: The main purpose is to create a new set of routing protocols optimized various factors from the major differences in the underwater wireless sensor network and terrestrial network.
Abstract: The underwater wireless sensor networks is a rapidly growing area of research as it monitors and collects data for environmental studies of seismic monitoring, flocks of underwater robots, equipment monitoring and control, pollution monitoring applications. The main purpose is to create a new set of routing protocols optimized various factors from the major differences in the underwater wireless sensor network and terrestrial network. Energy efficiency plays an important role in underwater wireless communication as underwater sensor nodes are powered by batteries which are difficult to replace or charge once the node is deployed. This paper surveys various routing techniques. Modern research trends focus to improve the performance on various issues like propagation delay, mobility, limited link capacity and limited battery power on the sea ground and sea surface.
01 Jan 2018
TL;DR: This paper presents design of precision agriculture system infrastructure aiming at a multi-parameter monitoring system using wireless sensor network based on low-power Intel's Galileo Gen-2 platform for monitoring, controlling and decision-making support using Internet of Things.
Abstract: This paper presents design of precision agriculture system infrastructure aiming at a multi-parameter monitoring system using wireless sensor network. Proposed infrastructure is based on low-power Intel’s Galileo Gen-2 platform for monitoring, controlling and decision-making support using Internet of Things (IoT). Collection of different farm field parameters is to be done using sensor nodes deployed in the farmland. Each node is connected wirelessly to the base station for the collection of data using wireless transreciever hardware platform. Data is then fed to the personal computer and displayed on screen, e.g. temperature, humidity, sprinkler water flow and soil moisture. From the collected data, decision-making and controlling action can be taken by the use of Internet of Things.
TL;DR: This letter investigates the joint power control and time allocation scheme in a wireless powered communication network, in which wireless sensors harvest the energy and then transmit information with a time switching protocol, and proposes an iterative resource management scheme to solve the formulated problem.
Abstract: In this letter, we investigate the joint power control and time allocation scheme in a wireless powered communication network, in which wireless sensors harvest the energy and then transmit information with a time switching protocol. Unlike the time-division-multiple-access scheme, the time switching protocol allows sensors transmit information signal simultaneously. Our purpose is to maximize sum of the user-centric energy efficiency (EE) of the system. However, due to the coupled time and power, the user-centric EE optimization problem is non-convex, which is difficult to be solved directly. We propose an iterative resource management scheme to solve the formulated problem. Numerical results are presented to illustrate the fast convergence and to show the advantage of our proposed algorithm compared with the previous studies.
TL;DR: This paper designs a proximal minimization algorithm that is capable of achieving the optimal allocation of network resources, source rates, and encoding and communication powers, while providing application-level quality of service represented by video distortion.
Abstract: Wireless video sensor networks (WVSNs) are opening the door for many applications, such as industrial surveillance, environmental tracking, border security, and infrastructure health monitoring. In WVSN, energy conservation is very essential because: 1) sensors are usually battery-operated and 2) each sensor node needs to compress the video prior to transmission, which consumes more power than conventional wireless sensor networks. In this paper, we study the problem of minimizing the total power consumption in a cluster-based WVSN, leveraging cross-layer design to optimize the encoding power, the transmission power, and the source rate at each sensor node. To realize this problem, we devise a resource optimization framework, which takes into account the video signal distortion due to compression, in addition to packet loss in the wireless channel while trying to allocate network resources among multiple video sensors. Leveraging duality theory, we design a proximal minimization algorithm that is capable of achieving the optimal allocation of network resources, source rates, and encoding and communication powers, while providing application-level quality of service represented by video distortion. The algorithm is extended for sensor nodes with hybrid energy sources, leveraging energy harvesting to minimize the aggregate power, while addressing the tradeoff between renewable versus grid energy sources.
TL;DR: This paper proposes a theoretical framework based on a variational inference algorithm to cluster various traffic patterns and design a threshold-based SU transmission strategy by taking into account the spectral access and energy harvesting opportunities for each traffic pattern, so as to optimize SU transmission.
Abstract: Traffic patterns associated with different primary users (PUs) might provide different spectral access and energy harvesting opportunities to secondary users (SUs) in wireless powered cognitive radio networks (WP-CRNs). Since the traffic applications have their own distinctive patterns, spectral access and energy harvesting opportunities are also expected to be distinctive. In this paper, we propose a novel approach to identify the PU traffic patterns and estimate the energy harvested from each traffic pattern so that SU can maximize its capacity accordingly. More specifically, we propose a theoretical framework based on a variational inference algorithm to cluster various traffic patterns and design a threshold-based SU transmission strategy by taking into account the spectral access and energy harvesting opportunities for each traffic pattern, so as to optimize SU transmission. Through simulations, we demonstrate the effectiveness of the proposed scheme in terms of throughput gains and show the transmission thresholds under various traffic applications (patterns). Further, we illustrate the effects of different collision costs on throughput for different traffic applications using real wireless traces.
Patent•
07 Aug 2018TL;DR: This work examines the applicability of wireless indoor quantum key distribution (QKD) in hybrid quantum-classical networks, and proposes practical configurations that would enable wireless access to such networks.
Abstract: We examine the applicability of wireless indoor quantum key distribution (QKD) in hybrid quantum-classical networks. We propose practical configurations that would enable wireless access to such networks. The proposed setups would allow an indoor wireless user, equipped with a QKD-enabled mobile device, to communicate securely with a remote party on the other end of the access network. QKD signals, sent through wireless indoor channels, are combined with classical ones and sent over shared fiber links to the remote user. Dense wavelength-division multiplexing would enable the simultaneous transmission of quantum and classical signals over the same fiber. We consider the adverse effects of the background noise induced by Raman-scattered light on the QKD receivers due to such an integration. In addition, we consider the loss and the background noise that arise from indoor environments. We consider a number of discrete and continuous-variable QKD protocols and study their performance in different scenarios.
TL;DR: A novel networking paradigm called Small-world SSDNet, servicing applications such as public safety, proximity based services, and fog computing based on device-todevice multi-hop wireless communications is proposed.
Abstract: In this article, we propose a novel networking paradigm called Small-world SSDNet, servicing applications such as public safety, proximity based services, and fog computing based on device-todevice multi-hop wireless communications. The "small-world" feature is determined by the service area, whose size is usually within a community level, and the well known small-world properties existing in SSDNets; the "super-dense" feature comes from the fact that the increased direct communication range and the popularity of 5G and IoT devices jointly result in a large number of devices within a single-hop communication range. This article first formally defines SSDNet. Then the challenges and the opportunities brought by the design and the implementation of the SSDNet protocols and applications are addressed. Finally, the broader discussions on issues relevant to modeling, engineering, and dissemination are provided.
TL;DR: This work proposes to build up the deep learning network to learn time-frequency analysis to instead of traditional STFT and DWT approaches, and demonstrates how to integrate learning time- frequencies analysis networks into practical IoT applications, signal detection in noisy environment, and classifying of various modulated wireless sensor signal.
Abstract: Time-frequency analysis is one of essential signal processing tool for wireless sensor signal in Internet of Things (IoT), but its traditional processing approaches, such as short time-frequency transformation (STFT) and discrete wavelet transformation (DWT), are challenged by the limitation of capability to self-learn from unknown environments and adjust parameters adaptively. To address this problem, we propose to build up the deep learning network to learn time-frequency analysis to instead of traditional STFT and DWT approaches. With using typical neural network layers to remodel STFT and DWT operations, the proposed models consider the efficiency on both training and processing procedures and show their parameter adaptability and capability of deep feature extraction from sensor signals. Moreover, we demonstrate how to integrate learning time-frequency analysis networks into practical IoT applications, signal detection in noisy environment, and classifying of various modulated wireless sensor signal, by which their performance are further evaluated in terms of computation complexity and efficiency.
TL;DR: A linear programming framework is proposed to explore the incomplete secure connectivity problem with respect to its impact on network lifetime, path length, queue size, and energy dissipation and the numerical results show that if any two nodes share a key with a probability of at least 0.3, then they should expect only a marginal drop in lifetime.
Abstract: Key predistribution schemes accommodate secure connectivity by establishing pairwise keys between nodes. However, ensuring security for all communication links of a wireless sensor network (WSN) is nontrivial due to the memory limitations of the nodes. If some of the links are not available due to the lack of a primary security association between the transmitter and the receiver, nodes can still send their data to the base station but probably not via the best route that maximizes the network lifetime. In this study, we propose a linear programming framework to explore the incomplete secure connectivity problem with respect to its impact on network lifetime, path length, queue size, and energy dissipation. The numerical results show that if any two nodes share a key with a probability of at least 0.3, then we should expect only a marginal drop (i.e., less than 3.0%) in lifetime as compared to a fully connected network.
TL;DR: A fully integrated system-on-chip wireless transmitter that has no need for an external quartz crystal frequency reference and constitutes a new approach for a fully integrated wireless sub-GHz transmitter that is competitive to state-of-the-art quartz crystal-based transmitters as well as to already existing crystal-less architectures.
Abstract: This paper presents a fully integrated system-on-chip wireless transmitter that has no need for an external quartz crystal frequency reference. Instead, a nontrimmable $LC$ oscillator (LCO) is implemented, operating at a fixed frequency of roughly 3.2 GHz. This LCO serves as the accurate frequency reference of the transmitter and is used to derive a frequency in the sub-GHz range for wireless applications via a fractional phase-locked loop. The digital functionality required for the frequency generation and thus for the wireless operation is performed by an 8-b microcontroller. The calibration data as well as the application specific firmware are stored in an integrated EEPROM. An initial frequency accuracy of ±52 ppm over a temperature of −20 °C to 85 °C is achieved using only two temperature insertions for the calibration. The device covers a continuous frequency range of 10–960 MHz and provides an ASK and GFSK operation. A low harmonic power amplifier was implemented to overcome design issues due to injection modulation effects. The chip is implemented in a 130 nm standard CMOS process and constitutes a new approach for a fully integrated wireless sub-GHz transmitter that is competitive to state-of-the-art quartz crystal-based transmitters as well as to already existing crystal-less architectures.
TL;DR: An architecture of wireless oceanographic system is proposed and a framework for the deployment planning is introduced and the power consumption profile of the sensor nodes in the system is investigated to investigate the system lifetime.
Abstract: A wireless oceanographic system is an underwater wireless-networked sensing system for oceanographic data collection, remote monitoring, and control. It represents a cutting-edge technology that could eliminate the need of long and expensive subsea cables while featuring real-time acquisition, flexible, and convenient deployment. Mainly powered by batteries, the wireless oceanographic system calls for power efficient deployment plans to extend the system lifetime. In this work, we first propose an architecture of wireless oceanographic system and then introduce a framework for the deployment planning. Specifically, we investigate the power consumption profile of the sensor nodes in the system. We employ a battery model for more accurate power estimation. Further, we analyzed the system lifetime with the consideration of the sensor node interactions. As a case study, the framework is applied to the Ocean-TUNE Long Island Sound (LIS) testbed, a real wireless oceanographic system with practical system configurations, and real data.
TL;DR: Virtual output queuing (VOQ) technique has been used to eliminate the head-of-line blocking issue and a novel and effective communication scheme has been introduced to alleviate the traffic load in wireless nodes and hence improving the efficiency of wireless communication.
TL;DR: A hybrid technique which combines both the Particle Filter (PF) method and the Time Difference of Arrival Technique (TDOA) is presented and results indicate that the proposed approach outperforms other techniques in terms of accuracy and robustness.
Abstract: The vivid success of the emerging wireless sensor technology (WSN) gave rise to the notion of localization in the communications field. Indeed, the interest in localization grew further with the proliferation of the wireless sensor network applications including medicine, military as well as transport. By utilizing a subset of sensor terminals, gathered data in a WSN can be both identified and correlated which helps in managing the nodes distributed throughout the network. In most scenarios presented in the literature, the nodes to be localized are often considered static. However, as we are heading towards the 5th generation mobile communication, the aspect of mobility should be regarded. Thus, the novelty of this research relies in its ability to merge the robotics as well as WSN fields creating a state of art for the localization of moving nodes. The challenging aspect relies in the capability of merging these two platforms in a way where the limitations of each is minimized as much as possible. A hybrid technique which combines both the Particle Filter (PF) method and the Time Difference of Arrival Technique (TDOA) is presented. Simulation results indicate that the proposed approach outperforms other techniques in terms of accuracy and robustness.
TL;DR: The main contribution of this paper is the introduction of an architecture for the interconnection of WSN and two medium access control protocols exclusively tailored to WSN-RoF architecture: scheduling of polling priority MAC and dynamic hybrid MAC for WSNs based on RoF access infrastructure.
Abstract: Radio-over-fiber (RoF) technology has been employed in network infrastructure due to its large capacity, low attenuation, and low operational costs, as well as due to the possibility of enlarging network coverage. This paper introduces a new approach for the interconnection of wireless sensor network (WSN) by employing RoF links, specifically wireless sensor network based on radio-over-fiber (WSN-RoF). The main contribution of this paper is the introduction of an architecture for the interconnection of WSN and two medium access control (MAC) protocols exclusively tailored to WSN-RoF architecture: scheduling of polling priority MAC and dynamic hybrid MAC for WSNs based on RoF access infrastructure. Both protocols deal with the main problems in WSN-RoF, i.e., the round-trip propagation delay in optical fiber links and the existence of two distinct collision domains: one wireless and the other optical. The performance of these two protocols shows their effectiveness in the interconnection of WSN through RoF links. Results of experiments demonstrate the benefits of using RoF links for the backhaul of WSN.
01 Jan 2018
TL;DR: There are various attack which is possible in the network, it may be from externally or internally but internal attacks are more dangerous than external, so, my mainly concern upon Wireless LAN and Wired LAN attacks which occurs internally.
Abstract: There are various attack which is possible in the network, it may be from externally or internally. But internal attacks are more dangerous than external. So, my mainly concern upon Wireless LAN and Wired LAN attacks which occurs internally. There are various Signature based tools, IDS/IPS (Intrusion detection or prevention system) available now-a-days for detecting these types of attacks but these are not sufficient due to high false alarm rate. So, I detect these types of attacks with three ways: through Wireshark, with signature based tools (Snort and Kismet) and with machine learning tools (WEKA). In wired LAN attack, my mainly concern on PING scan or PING flood, NMAP scan (portsweep) and ARP spoofing attacks. In wireless LAN attacks, I take care of Deauthentication attack, Disassociation attack and Access point (AP) spoofing attack. Signature based tools detect these types of the attacks based on the stored signature and timing threshold. But machine learning tools take several different feature to detect these types of attacks with more accuracy and low false positive rate.