115 research outputs found

    AN ENERGY EFFICIENT CROSS-LAYER NETWORK OPERATION MODEL FOR MOBILE WIRELESS SENSOR NETWORKS

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    Wireless sensor networks (WSNs) are modern technologies used to sense/control the environment whether indoors or outdoors. Sensor nodes are miniatures that can sense a specific event according to the end user(s) needs. The types of applications where such technology can be utilised and implemented are vast and range from households’ low end simple need applications to high end military based applications. WSNs are resource limited. Sensor nodes are expected to work on a limited source of power (e.g., batteries). The connectivity quality and reliability of the nodes is dependent on the quality of the hardware which the nodes are made of. Sensor nodes are envisioned to be either stationary or mobile. Mobility increases the issues of the quality of the operation of the network because it effects directly on the quality of the connections between the nodes

    Transmission Delay of Multi-hop Heterogeneous Networks for Medical Applications

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    Nowadays, with increase in ageing population, Health care market keeps growing. There is a need for monitoring of Health issues. Body Area Network consists of wireless sensors attached on or inside human body for monitoring vital Health related problems e.g, Electro Cardiogram (ECG), ElectroEncephalogram (EEG), ElectronyStagmography(ENG) etc. Data is recorded by sensors and is sent towards Health care center. Due to life threatening situations, timely sending of data is essential. For data to reach Health care center, there must be a proper way of sending data through reliable connection and with minimum delay. In this paper transmission delay of different paths, through which data is sent from sensor to Health care center over heterogeneous multi-hop wireless channel is analyzed. Data of medical related diseases is sent through three different paths. In all three paths, data from sensors first reaches ZigBee, which is the common link in all three paths. After ZigBee there are three available networks, through which data is sent. Wireless Local Area Network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunication System (UMTS) are connected with ZigBee. Each network (WLAN, WiMAX, UMTS) is setup according to environmental conditions, suitability of device and availability of structure for that device. Data from these networks is sent to IP-Cloud, which is further connected to Health care center. Main aim of this paper is to calculate delay of each link in each path over multihop wireless channel.Comment: BioSPAN with 7th IEEE International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA 2012), Victoria, Canada, 201

    Analyzing Delay in Wireless Multi-hop Heterogeneous Body Area Networks

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    With increase in ageing population, health care market keeps growing. There is a need for monitoring of health issues. Wireless Body Area Network (WBAN) consists of wireless sensors attached on or inside human body for monitoring vital health related problems e.g, Electro Cardiogram (ECG), Electro Encephalogram (EEG), ElectronyStagmography (ENG) etc. Due to life threatening situations, timely sending of data is essential. For data to reach health care center, there must be a proper way of sending data through reliable connection and with minimum delay. In this paper transmission delay of different paths, through which data is sent from sensor to health care center over heterogeneous multi-hop wireless channel is analyzed. Data of medical related diseases is sent through three different paths. In all three paths, data from sensors first reaches ZigBee, which is the common link in all three paths. Wireless Local Area Network (WLAN), Worldwide Interoperability for Microwave Access (WiMAX), Universal Mobile Telecommunication System (UMTS) are connected with ZigBee. Each network (WLAN, WiMAX, UMTS) is setup according to environmental conditions, suitability of device and availability of structure for that device. Data from these networks is sent to IP-Cloud, which is further connected to health care center. Delay of data reaching each device is calculated and represented graphically. Main aim of this paper is to calculate delay of each link in each path over multi-hop wireless channel.Comment: arXiv admin note: substantial text overlap with arXiv:1208.240

    An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

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    Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

    ENERGY-EFFICIENT PROTOCOL DESIGN AND ANALYSIS FOR WIRELESS SENSOR NETWORKS

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    Wireless sensor networks are an emerging technology which has the promise of revolutionizing the way of collecting, processing and disseminating information. Due to the small sizes of sensor nodes, resources like battery capacity, memory and processing power are very limited. Wireless sensor networks are usually unattended oncedeployed and it is infeasible to replace batteries. Designing energy-efficient protocols to prolong the network life without compromising too much on the network performance is one of the major challenges being faced by researchers.Data generation in wireless sensor networks could be bursty as it is dictated by the presence or absence of events of interest that generate these data. Therefore sensor nodes stay idle for most of the time. However, idle listening consumes as much energy as receiving. To save the unnecessary energy consumption due to idlelistening, sensor nodes are usually put into sleep.MAC protocols coordinate data communications among neighboring nodes. We designed an energy-efficient MAC protocol called PMAC in which sleep-awake schedules are determined through pattern exchange. PMAC also adapts to different traffic conditions.To handle bursty traffic and meanwhile preserve energy, dual radio interfaces with different ranges, capacity and power consumption can be employed on each individual sensor node. We designed a distributed routing-layer switch agent which intelligently directs traffic between the dual radios. The low-power radio will be used for light traffic load to preserve energy. The high-power radio is turned on only when the traffic load becomes heavy or the end-to-end delay exceeds a certain threshold. Each radio has its own routing agent so that a better path can be found when the high-power radio is in use.Data gathering is a typical operation in wireless sensor networks where data flow through a data gathering tree towards a sink node. DMAC is a popular energyefficient MAC protocol specifically designed for data gathering in wireless sensor networks. It employs staggered sleep-awake schedules to enable continuous data forwarding along a data gathering tree, resulting in reduced end-to-end delays and energy consumption. we have analyzed end-to-end delay and energy consumption with respect to the source node for both constant bit rate traffic and stochastic traffic following a Poisson process. The stochastic traffic scenario is modeled as a discrete time Markov chain and expressions for state transition probabilities, the average delay and average energy consumption are developed and are evaluated numerically. Simulations are carried out with various parameters and the results are in line with the analytical results.Lots of work had been done on constructing energy-efficient data gathering trees at the routing layer. We proposed a sleep scheme at the routing layer called DGSS which could be incorporated into different data gathering tree formation algorithms. Unlike DMAC, in which nodes are scanned level by level, DGSS starts scanningfrom the leaf nodes and shrinks inward towards the sink node. Simulation shows that DGSS can achieve better energy efficiency than DMAC at relatively higher data rates

    A Novel Architectural Framework on IoT Ecosystem, Security Aspects and Mechanisms: A Comprehensive Survey

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    For the past few years, the Internet of Things (IoT) technology continues to not only gain popularity and importance, but also witnesses the true realization of everything being smart. With the advent of the concept of smart everything, IoT has emerged as an area of great potential and incredible growth. An IoT ecosystem centers around innovation perspective which is considered as its fundamental core. Accordingly, IoT enabling technologies such as hardware and software platforms as well as standards become the core of the IoT ecosystem. However, any large-scale technological integration such as the IoT development poses the challenge to ensure secure data transmission. Perhaps, the ubiquitous and the resource-constrained nature of IoT devices and the sensitive and private data being generated by IoT systems make them highly vulnerable to physical and cyber threats. In this paper, we re-define an IoT ecosystem from the core technologies view point. We propose a modified three layer IoT architecture by dividing the perception layer into elementary blocks based on their attributed functions. Enabling technologies, attacks and security countermeasures are classified under each layer of the proposed architecture. Additionally, to give the readers a broader perspective of the research area, we discuss the role of various state-of-the-art emerging technologies in the IoT security. We present the security aspects of the most prominent standards and other recently developed technologies for IoT which might have the potential to form the yet undefined IoT architecture. Among the technologies presented in this article, we give a special interest to one recent technology in IoT domain. This technology is named IQRF that stands for Intelligent Connectivity using Radio Frequency. It is an emerging technology for wireless packet-oriented communication that operates in sub-GHz ISM band (868 MHz) and which is intended for general use where wireless connectivity is needed, either in a mesh network or point-to-point (P2P) configuration. We also highlighted the security aspects implemented in this technology and we compare it with the other already known technologies. Moreover, a detailed discussion on the possible attacks is presented. These attacks are projected on the IoT technologies presented in this article including IQRF. In addition, lightweight security solutions, implemented in these technologies, to counter these threats in the proposed IoT ecosystem architecture are also presented. Lastly, we summarize the survey by listing out some common challenges and the future research directions in this field.publishedVersio

    AN ENERGY EFFICIENT CROSS-LAYER NETWORK OPERATION MODEL FOR MOBILE WIRELESS SENSOR NETWORKS

    Get PDF
    Wireless sensor networks (WSNs) are modern technologies used to sense/control the environment whether indoors or outdoors. Sensor nodes are miniatures that can sense a specific event according to the end user(s) needs. The types of applications where such technology can be utilised and implemented are vast and range from households’ low end simple need applications to high end military based applications. WSNs are resource limited. Sensor nodes are expected to work on a limited source of power (e.g., batteries). The connectivity quality and reliability of the nodes is dependent on the quality of the hardware which the nodes are made of. Sensor nodes are envisioned to be either stationary or mobile. Mobility increases the issues of the quality of the operation of the network because it effects directly on the quality of the connections between the nodes

    RPL Cross-Layer Scheme for IEEE 802.15.4 IoT Devices With Adjustable Transmit Power

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    Article number 9523554We propose a novel cross-layer scheme to reduce energy consumption in wireless sensor networks composed of IEEE 802.15.4 IoT devices with adjustable transmit power. Our approach is based on the IETF’s Routing Protocol for Low power and lossy networks (RPL). Nodes discover neighbors and keep fresh link statistics for each available transmit power level. Using the product of ETX and local transmit power level as a single metric, each node selects both the parent that minimizes the energy for packet transmission along the path to the root and the optimal local transmit power to be used. We have implemented our cross-layer scheme in NG-Contiki using the Z1 mote and two transmit power levels (55mW and 31mW). Simulations of a network of 15 motes show that (on average) 66% of nodes selected the low-power setting in a 25 m × 25 m area. As a result, we obtained an average reduction of 25% of the energy spent on transmission and reception of packets compared to the standard RPL settings where all nodes use the same transmit power level. In large scenarios (e.g., 150 m × 150 m and 40-100 motes), our approach provides better results in dense networks where reducing the transmit power of nodes does not translate into longer paths to the root nor degraded quality of service

    Energy-Efficient Routing Based on Dynamic Programming for Wireless Multimedia Sensor Networks (WMSNs)

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    Wireless Multimedia Sensor Networks (WMSNs) advances can route multimedia applications from source nodes to a sink. However, they require energy efficiency and network lifetime due to limited power resources in the sensor nodes. This paper proposes an energy–efficient routing optimization for multimedia transmission in WMSNs. The optimization utilizes a routing algorithm based on the dynamic programming. The routing optimization algorithm selects intermediary nodes which have minimum energy above 60%. Then, the priority selection of paths immediately finds neighboring nodes which have the greatest energy minimum. If there is the same minimum energy between the neighboring nodes, then the second priority selection is based on smaller link cost

    Energy-Efficient Communication in Wireless Networks

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    This chapter describes the evolution of, and state of the art in, energy‐efficient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Specifically, emphasis is placed on energy efficiency as critical to ensuring the feasibility of long lifetime, low‐maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traffic patterns is discussed, in addition to their combination and evaluation as full protocol stacks
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