International Journal of Sensors Wireless Communications and Control - Volume 6, Issue 2, 2016

Dielectric contrast between normal and cancer tissues can be used for detection of cancer in early stage. Microwave Imaging is a technique which exploits this concept for cancer detection. The technique requires the development of precise simulation model showing scattering of microwave signals within the cancer tissues. The Finite Difference Time Domain (FDTD) method is generally used as numerical modeling technique applied to model the propagation of electromagnetic (EM) waves in biological tissues. However, it is crucial that an FDTD model so developed must precisely symbolize the dielectric properties of the constitutional tissues and the highly correlated distribution of these tissues within the cancer surroundings. Historical studies which examined the dielectric properties of the cancer tissues conclude that the cancer tissue is first placed in dielectrically homogeneous extension of normal tissues and attenuation features of the two, produce additional wave reflections from the cancer tissues. This paper presents a selective survey of microwave techniques which are being used for the diagnosis of cancer tissues and how FDTD has been used by researchers to model such systems. Furthermore, existing FDTD models of the cancer tissues are examined and compared.

In this paper we proposed a design of diamond shaped frequency reconfigurable microstrip patch antenna by altering the physical structure of the antenna. The design consists of two triangular shaped patches with a gap. The triangular shaped patches can be connected or disconnected by using Radio Frequecncy Micro Electro-Mechanical System (RF MEMS) switch. By making the switches OFF / ON, the length of radiating part of the patch antenna can be varied and thus antenna can be tuned to different frequencies from 7.38 GHz to 7.58 GHz.

Background: Wireless Sensor Networks (WSNs) consist of sensor nodes which are able to sense a variety of physical phenomenon. It is a well-known fact that in most of the real world applications related to WSNs, the deployment is random as manual deployment is not possible due to harsh environments and other complexities. Therefore, there is no prior knowledge about the position of the sensor nodes that are deployed to form a wireless sensor network. In order to overcome this aspect related to position estimate of sensor nodes vari-ous localization schemes and algorithms have been proposed. The schemes and algorithms proposed so far also offer advantages like optimal routing, energy conservation, security, topology control besides providing the accurate position estimation of deployed sensor nodes. This paper explicitly presents a survey on the existing learning and non-learning based algorithms that have special role in localization of sensor nodes for WSNs. Methods: Comparative analysis of prominent learning and non-learning based algorithms. The analysis is based in terms of physical measurement, accuracy, computation and hardware cost and energy efficiency. Result: Detailed reporting of learning and non-learning based algorithms with their sub-categories. The study and survey of various algorithms throw light on their applicability and use for WSNs. Conclusion: Characteristics exhibited by the variants of the discussed algorithms are featured in order to make them application centric and cost effective.

Efficient management of bandwidth in wireless networks is a critical factor for a successful communication system. The provision of quality of service (QoS) guarantees in such networks is vital to the profitability of these networks and satisfaction of their users. In this paper, we present a model to expand the bandwidth capacity of a wireless network to meet user demand and to manage bandwidth efficiently based on bandwidth reservation and bandwidth adaptation in order to maximize net revenue while providing QoS guarantees. Our approach ensures zero call handoff dropping tolerance. The results of a simulation study show that the proposed method outperforms an existing method with respect to key performance measures such as call blocking and dropping probabilities and call time survivability. This survivability indicator is a new measure that is introduced for the first time in this paper. We also present a second tradeoff model to allow the network operator to control call dropping probability. The results of a second simulation study show that the network operator and users are better off if a zero call dropping policy is adopted as proposed in the first model.

Modeling and realization of Vehicular Ad-Hoc Network (VANET) applications and protocols are very challenging; due to VANET`s unique mobility, driver behavior, signaling and road topology requirements. Although network simulators are commonly used to evaluate wireless network per-formance, VANET applications require mobility simulators to mimic road traffic topology and mobility. However, network and mobility simulators fall short of evaluating Quality of Experience (QoE) and Quality of Service (QoS) of context-rich applications with multiple user interactions. Using real hardware provides a solid mechanism to evaluate QoE and QoS in real time, though it is very expensive to use in large networks and difficult to reproduce specific VANET scenarios such as collisions and signaling changes due to speed and road topology. Emulation techniques combine the benefits of using both simulation and hardware approaches. Recently, multiple Ad-Hoc emulators have been developed, but they are not tailored to VANET`s requirements. In this article, the most suitable network and mobility simulators and their integrations for VANET are surveyed. Subsequently, their features, popularity and challenges are compared, the best ones corresponding to VANET application conditions are rec-ommended. Moreover, a comprehensive review is performed on Ad-Hoc emulators showing the benefits and suitability of each one for VANET applications. This article serves as a starting point for the development of comprehensive VANET emulators and testbeds; it also acts as a start-up guide for researchers to select the best tools for VANET application, protocol modeling, simulation, and emulation.

Background: Nowadays, wireless sensor networks are commonly used in healthcare applications. Congestion is one of the main challenges in these networks, which causes the network efficiency to be decreased considerably. Most of the existing congestion control methods are presented for wireless sensor networks and the least of them are discussed on wireless body sensor networks. Moreover, they usually use one of the basic controlling factors instead of considering a group of such factors. Objective: Congestion is one of the main problems in wireless body sensor networks that can be carefully avoided and controlled by a group of basic controlling parameters. Methods: The goal of this work is to propose an optimized prioritized congestion avoidance and control protocol in wireless body sensor networks. The proposed protocol uses a hop-to-hop delivery to transmit data packets from sensor nodes to a base station. Data packets are prioritized by source nodes based on node priority and data volatility. They are also prioritized by intermediate nodes through three prioritized queues. Each node selects one of its neighbors by a dynamic congestion aware routing strategy to transmit data packets to the base station. Increasing the data reliability and decreasing the network traffic on transmission paths are some of the main goals of the proposed protocol. Results: Simulation results show that the proposed protocol surpasses one of the existing congestion protocols in terms of system throughput, network lifetime, number of lost packets, traffic load, and number of delivered packets. Conclusion: The proposed protocol can avoid and control the congestion problem in wireless body sensor networks.

Background: Wireless Sensor Network (WSN) consists of a set of nodes that collect information from a given area, then cooperate with each other to send it to the Base Station (BS). Since the power resources of the nodes are restricted, a special treatment for their available power is mightily required. In MH routing algorithms, finding the optimal path to route data from a source to destination is one of the most interesting issues. This paper presents BEERAD, a new algorithm for multi-hop (MH) communication between nodes to conserve the energy consumption and extend the network lifetime of the nodes. Methods: Since the sensing, processing, transmitting and receiving tasks consume a valuable part of node energy over time, they must be considered during the path selection process. BEERAD is a Dijkstra-based algorithm which not only accepts the total power consumption at both nodes as the weight of the path but also considers the nodes' residual energy. Results: Several metrics are used to evaluate the available paths in order to select the optimal path, such as; Energy consumption, hop counts, and battery power. These metrics can be considered separately or in combination. BEERAD is tested with various scenarios of WSN. The Simulation results show that it has better performance in comparison with other existing ones from the previous metrics point of view. Conclusion: In the light of BEERAD, this proposal was incorporated as Multi-hop routing protocol being evaluated through simulation. The proposed protocol balances the energy of nodes all over the network over the network lifetime, avoiding the hot spot problem; hence the stability period of the network is enhanced. It also increases the total throughput of the network.